Three of the five most common medical conditions reported in 2012 were musculoskeletal conditions: low back pain, chronic joint pain, and arthritis. The other most commonly reported medical conditions are chronic hypertension and chronic high cholesterol. One in three to four persons over the age of 18 report having these conditions. Back and joint pain, along with arthritis, cause a much higher level of disability and affect quality of life at higher rates than do hypertension and high cholesterol. Major respiratory conditions are reported at much lower rates than circulatory and musculoskeletal conditions. (Reference Table 1.3.1 PDF [25] CSV [26])

Females report slightly higher levels of musculoskeletal conditions than do males, but males have higher rates of hypertension and high cholesterol. Age is a factor in increasing prevalence of all major conditions related to musculoskeletal and circulatory diseases, but the rates of hypertension and high cholesterol are much lower in young adults (18 to 44 years) and higher in older age groups (65 and over) than for musculoskeletal conditions. (Reference Table 1.3.1 PDF [25] CSV [26]; Table 1.3.2 PDF [53] CSV [54]; Table 1.3.3 PDF [55] CSV [56]; and Table 1.3.4 PDF [57] CSV [58])

Trends

Over the last decade, little progress has been made in reducing the prevalence of the most common respiratory, circulatory, and musculoskeletal diseases. In fact, musculoskeletal conditions and chronic hypertension, already affecting a majority of the population, have all seen a slight growth in prevalence. As mentioned earlier, there has been major progress in reducing prevalence of several fatal conditions worldwide. The time has come to focus research on non-fatal diseases, such as musculoskeletal diseases, that can cause many years of pain and disability and have been growing in prevalence. (Reference Table 1.3.5 PDF [59] CSV [60])

As previously noted, musculoskeletal conditions are one of the most debilitating nonfatal health diseases, leading to chronic pain and disability and reduced quality of life. The most common musculoskeletal conditions leading to disability are back and neck pain and arthritis and chronic joint pain.

Back and Neck Pain

Back pain affects most people at some point in their lives. For the lucky, this pain has a known cause and is temporary, healing with time and rest. But for many, back pain is a constant in their life. Chronic back pain is considered to be back pain lasting three months or longer. While spinal changes that are the source of back pain may be known and understood, there remains a gap in understanding why some people are affected and others are not, and what can be done to prevent or repair damage done.

In 2015, 72.3 million people age 18 and older reported they experienced chronic back pain in the previous year. This is nearly one in three adults. Of this group, more than one-third (37%) had back pain severe enough that it created radiating leg pain. Two in four (39%) also reported chronic neck pain, but 61% of the 38.9 million with neck pain had chronic neck pain alone.

Females report low back and neck pain at slightly higher rates than males, with females accounting for 54% of low back pain cases, with a rate of 30.8 per 100 persons compared to 27.4 for males. There is an even greater discrepancy in reported neck pain, with females reporting a 33% higher rate per 100 persons than males. (Reference Table 1.3.1 PDF [25] CSV [26])

Low back and neck pain are common among all ages of adults, with reported prevalence leveling as people reach middle age (45 and older). There is an actual slight dip in back pain prevalence in the oldest population, age 75 and older, but back pain remains a significant source of pain and disability throughout people’s lives. (Reference Table 1.3.2 PDF [53] CSV [54])

Low back and neck pain is reported at slightly higher rates among non-Hispanic whites than found in other racial/ethnic populations. Persons of other/mixed non-Hispanic racial/ethnic groups report the lowest rates. (Reference Table 1.3.3 PDF [55] CSV [56])

Back pain is reported in similar numbers in all geographic regions, with some minor differences seen. Low back pain is reported at the highest rate (30.3/100) in the Midwest, while low back pain with radiating leg pain is slightly higher in the South (11.3/100). Neck pain is reported highest in the West (17.9/100).

Arthritis

About one in two persons reporting a doctor has “ever” told them they have arthritis report either chronic joint pain or low back/neck pain. It is unknown why some people with arthritis are more likely to report pain than others. More than 55.4 million report they have some type of arthritis, an overall prevalence rate of nearly one in four adults (22.4/100). Females report higher rates than males, accounting for 58% of those reporting they have arthritis. This represents a one-in-four prevalence ratio (25.4/100) compared to one-in-five (19.1/100) males. (Reference Table 1.3.1 PDF [25] CSV [26])

Age is clearly a factor in arthritis, with very low rates found in younger adults. By middle age (45-64) the prevalence rate has more than quadrupled (6.8 to 28.6/100). By the age of 65, the reported prevalence rate has again nearly doubled, to 48.1/100 adults. There is a slight increase again in the oldest population, age 75 and older. (Reference Table 1.3.2 PDF [53] CSV [54])

Persons of non-Hispanic white race/ethnic background report arthritis at a prevalence rate more than twice that of those of Hispanic ethnicity and non-Hispanic other/mixed race/ethnicity. Non-Hispanic blacks report a rate slightly lower than non-Hispanic whites, but still nearly double that of Hispanics and non-Hispanic other/mixed race ethnicity. Understanding why these racial/ethnic differences occur could aid in understanding why some persons get arthritis while others do not, as well as why some persons with arthritis report more pain than others. (Reference Table 1.3.3 PDF [55] CSV [56])

Residents of the Midwest, with a population median age of 38.0 years, report slightly higher rates of arthritis than persons residing in other geographic regions, with residents of the West region, which has the youngest median age (35.9), reporting the lowest rate.1  (Reference Table 1.3.4 PDF [57] CSV [58])

Arthritis is associated with both chronic joint and back pain. Roughly one-half of persons reporting chronic joint pain (54%), low back pain (53%), and radiating leg pain (52%) also report they have arthritis. About one-third (32%) reporting neck pain report they have arthritis.

Chronic Joint Pain

In recent years, chronic joint pain, defined as joint pain lasting three months or longer, has reached the prevalence level of low back pain as a common musculoskeletal condition. Chronic joint pain, was reported by 72.5 million adults age 18 and older, for a rate of 29.3 in 100 persons. Chronic joint pain and arthritis are not mutually exclusive and may be reported by the same individual. Although age is a general predictor of chronic joint pain and arthritis, with nearly one in two persons age 65 years and older reporting one or both of these conditions, the rate of reported chronic joint pain in younger persons is also of concern. In 2015, one in six persons ages 18 to 44 reported experiencing chronic joint pain in the past year, while more than one-third (37%) age 45 to 64 reported chronic joint pain. Long active lifestyles will continue to be a major cause of joint pain in the coming years. (Reference Table 1.4.1 PDF [65] CSV [66] and Table 1.4.2 PDF [67] CSV [68])

As with other musculoskeletal diseases, chronic joint pain is reported by a slightly higher rate of females than males, as well as among non-Hispanic whites, with one in three reporting chronic joint pain. Other racial/ethnic groups report a prevalence between 20 and 26 in 100 persons with chronic joint pain. Also, the Midwest geographic region reports a higher prevalence than other regions in the US. (Reference Table 1.4.3 PDF [69] CSV [70] and Table 1.4.4 PDF [71] CSV [72])

Chronic knee pain is reported by all ages older than 18 years, with nearly one in three persons age 65 and older reporting chronic knee pain, and one in four (23.9/100) among those 45 to 64 years old. Because only 1 in 10 persons age 18 to 44 reports knee pain, the overall prevalence is 19 in 100. Females report a slightly higher rate of knee pain than males do.

Shoulder pain, reported by 22.3 million of those age 18 and older in 2015, is the second most common joint site for chronic pain, with rates fairly equal for those age 45 and older. Shoulder pain is reported in fairly equal rates by males and females, with males having a slightly higher rate.

Hip pain was reported by 18.2 million people age 18 and older in 2105. Hip pain is much more common in females than in males. As with other sites of chronic joint pain, hip pain prevalence increases with age.

 

While multiple joints can be the source of chronic joint pain, overall, nearly one in three (29.3/100) people over the age of 18 reported chronic joint pain in 2015. The ratio jumps to nearly one in two (47/100) after the age of 65 years. However, even among younger adults age 18 to 44, about one in six (16.3/100) report chronic joint pain. (Reference Table 1.4.1 PDF [65] CSV [66] and Table 1.4.2 PDF [67] CSV [68])

Trends

Over the past eight years, a slight increase in the prevalence rate of reported chronic joint pain has been seen. This is primarily associated with knee pain, but other joints have also seen small increases.

• 1. United States Census Bureau. American Fact Finder. ACS DEMOGRAPHIC AND HOUSING ESTIMATES: 2010-2014 American Community Survey 5-Year Estimates. https://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml. [50] Accessed August 15, 2016.

Activities of daily living include walking, climbing steps, standing or sitting for extended periods of time, stooping, reaching, grasping, carrying or pushing/pulling large objects, shopping, and social activities or just relaxing. The number of adults with most major health conditions who have difficulty performing these activities is quite low, representing fewer than two or three adults out of 100. The exception is adults reporting musculoskeletal conditions, for whom the overall rate for a limitation in the performance of any ADL is nearly 15 in 100 persons. For individual ADL, those with musculoskeletal conditions report limitations at two to six times the rate found for other major health conditions. (Reference Table 1.7.1 PDF [99] CSV [100])

Among the adult population in the work force, 38 in 1000 report they are unable to work at all due to a musculoskeletal disease, with an additional 21 reporting they can do only limited work. This is two times or greater than the rate of the second most work limiting condition, circulatory diseases. (Reference Table 1.7.2 PDF [103] CSV [104])

More than one in four adults in the population (27%), a total of 54 million, reported at least one bed day in the previous 12 months because of a medical condition. More than one-half (14.7%) reported having a musculoskeletal condition, more than reported any other condition. Respondents could report multiple conditions, and bed days could be associated with more than one condition. The mean number of bed days reported with musculoskeletal conditions was 20.4, for a total of 1.1 billion bed days. While other conditions were likely the cause of a higher mean number of bed days, the share of the population reporting these conditions was much smaller.

Males and females reported a similar mean number of bed days due to musculoskeletal conditions (20 days vs 21 days), however, because more females report musculoskeletal conditions and bed days than males, the total bed days attributed to females is much greater. Adults in their middle years, age 45 to 64, report higher rates of bed days because of musculoskeletal conditions than do adults age 18 to 44 or over 65.

(Reference Table 1.8.1 PDF [107] CSV [108])

More than 35 million adults in the workforce with a musculoskeletal condition reported lost work days in the previous 12 months, totaling nearly 364 million days. Lost work days for persons with a musculoskeletal conditions accounted for more lost work days than any other major health condition, with workers losing an average of 10 days of work. Chronic circulatory conditions, including high blood pressure and heart conditions, accounted for 283 million lost work days, and were reported by an increasing share of the working age population.

As with bed days, females and males reported similar numbers of lost work days, but again, the number of females was higher. The youngest members of the work force, those age 18 to 44, accounted for the largest number of workers with lost work days due to a musculoskeletal condition, but they also represent the largest share of the work force population. They reported a mean of three fewer days lost than the older 45 to 64 worker population. The oldest workers, those age 65 and over, reported a mean of nearly 14 days lost, but comprised a very small share of the work force.

(Reference Table 1.8.2 PDF [109] CSV [110])

The increasing prevalence of musculoskeletal conditions, along with a growing and aging population, has resulted in more than a 44% increase in total aggregate direct cost to treat persons with a musculoskeletal condition over the past decade (2002-2004 to 2012-2014), in constant 2014 dollars. For the years between 2012 and 2014, the annual average direct cost in 2014 dollars for musculoskeletal health care—both as a direct result of a musculoskeletal disease and for patients with a musculoskeletal disease in addition to other health issues—is estimated to be $980.1 billion, the equivalent of 5.76% of the national gross domestic product (GDP).

Total medical care costs are the costs for treating all of an individual’s conditions, including musculoskeletal conditions. Incremental medical care costs are that part of total medical care costs attributable solely to the musculoskeletal conditions. Incremental medical costs for musculoskeletal conditions for the years between 2012 and 2014 are estimated to be $162.4 billion, in 2014 dollars. (Reference Table 8.14 PDF [147] CSV [148], and Table 8.6.1 PDF [143] CSV [144])

Indirect costs measure disease impact in terms of lost wages due to disability or death.  Indirect costs, like medical care costs, can be estimated and calculated in total for all the medical conditions an individual has, and as the increment attributable solely to musculoskeletal conditions.

Indirect cost for people age 18 to 64 with a work history add another $97.5 billion, or 0.5% of the GDP in between 2012 and 2014, to the cost for all persons with a musculoskeletal disease, either treated as a primary condition or in addition to another condition. Annual indirect costs attributable to musculoskeletal disease alone (incremental cost) account for an estimated $159.2 billion. Indirect costs attributable to musculoskeletal disease are greater than total indirect costs wage losses attributable to musculoskeletal conditions are greater than the mean difference in wages between the two groups, an indication that persons with musculoskeletal conditions work less than expected of persons their ages. (Reference Table 8.12 PDF [145] CSV [146])

For each of the years 2013 to 2015, an annual average of nearly 29% of the US population age 18 years and older self-reported having had low back pain during the past three months. Among persons reporting low back pain, one in three (35.7%) suffered from back pain radiating into the leg. Approximately one-third of persons reporting low back pain also reported experiencing neck pain. Lower back pain is reported in higher rates by females (30.5%) than males (26.4%). The highest rates for lower back pain reported for both genders occurred in the 45-64 years age group (33.3%); there is a slight decrease in low back and neck pain complaints in ages 65 years and older (32.8%). Low back pain is most prevalently reported in the non-Hispanic white ethnic group. The Midwest region of the United States is responsible for recording the highest prevalence of low back pain. With the exception of persons 18 to 44 years, the prevalence of lower back pain with or without radiating leg pain did not vary considerably across all measured demographic categories. (Reference Table 2A.1 PDF [158] CSV [159])

As discussed previously, healthcare utilization by people with low back pain, which represents 82% of back pain healthcare visits, is only understood in part due to the lack of information about visits to chiropractors, physical therapists, and others involved in the care of back pain. Even so, the reported numbers in the databases are very high. In 2013, nearly 62 million visits to hospitals, emergency departments, outpatient clinics, and physician offices included a diagnosis of low back pain. Three in four visits were to physician offices, but more than 2.3 million patients were hospitalized and almost 10 million patients were treated for low back pain at an emergency department. (Reference Table 2A.2.1 PDF [168] CSV [169] and Table 2A.4.1 PDF [172] CSV [173])

 

Demographics of Low Back Pain

The prevalence of low back pain healthcare visits is greatest in the 45-64 years age group, closely followed by the 18-44 years age group. Together, the 18-64 years age group represents 72% of all low back pain healthcare visits. However, adjusting for the 2013 US Census population estimates, healthcare visits for low back pain per 100 persons is highest in the 65 years and older age group, where it is 36.1%. In reviewing the three low back diagnostic categories, the category labeled "back disorders" dominates in all age groups. Disc disorders are uncommon in the younger than 18 years age group, but increase in frequency as the population ages, and are most prevalent in the 45-64 years age group. Back injuries are more common in patients younger than age 45 years (48%), declining to 14% in those 65 years and older. (Reference Table 2A.2.2 PDF [176] CSV [177])

The average age of persons hospitalized in 2013 for low back pain was 61.8 years. This compared to an average age of 47.2 years for persons visiting an emergency department, 49.4 years for visits to outpatient departments, and 54.5 years for visits to a physician. These numbers are essentially unchanged since 2010, with the exception of the average age of persons visiting an emergency department, which increased by 4.5 years. (Reference Table 2A.2.2 PDF [176] CSV [177])

Low back pain is found more frequently among females than males, with females representing 55% of healthcare resource visits. Back disorders, in particular, are more common in females, while disc disorders and back injuries are recorded similarly between sexes. Over 8 in 10 (84.4%) female healthcare visits in 2013 for low back pain were classified as back disorders, compared to 80.4% for males. This is probably a reflection of the prevalence of spinal stenosis and degenerative spondylolisthesis in both sexes. (Reference Table 2A.2.1 PDF [168] CSV [169])

Ethnic groups show preferences in where they might go to receive healthcare for low back pain, as exemplified by the rate of visits per 100 persons per race/ethnicity in the population. Overall, three out of four (74%) patients seen at a hospital were non-Hispanic whites, totaling approximately 1.8 million visits. This is in comparison to a combined total of 380,000 inpatient visits for non-Hispanic black (10%) and Hispanic (6%) visits. In contrast, for outpatient healthcare visits, non-Hispanic black (15%) and Hispanic (13%) ethnic groups reported an increase in percentage of visits compared to the hospital setting, a total of 1.2 million visits. Non-Hispanic white (66%) patients reported 2.8 million outpatient low back pain visits. Race/ethnicity is not reported in the NEDS database on emergency department visits. (Reference Table 2A.2.3 PDF [184] CSV [185])

Total healthcare visits for low back pain reflected differences between regions regarding back injuries (7.2 million) and back and disk disorders (50.9 million; 10 million). The southern United States recorded the highest percentage of total visits for back and disc disorders (31%; 40%), while the western United States recorded the highest percentage of total visits for back injuries (31%). (Reference Table 2A.2.4 PDF [186] CSV [187])

 

Hospitalization

Length of Stay

Persons hospitalized for low back pain in 2013 spent, on average, nearly 5 days in the hospital. Persons hospitalized for low back injuries were hospitalized for the longest period, an average of 6.8 days. When comparing the total days of hospitalization for all causes with those for low back pain are similar. As a proportion of hospitalizations for all causes, back pain constitutes 7% of both discharges and of total hospital days. The length of hospital stays has remained relatively stable since 2004. (Reference Table 2A.8 PDF [188] CSV [189] and Table 2A.9 PDF [190] CSV [191])

The mean length of stay for all low back pain discharges was similar between sexes. Regarding back injuries, length of stay of males is 1.5 days longer than for females (7.6 vs 6.1 days). (Reference Table 2A.10.1 PDF [192] CSV [193])

Age is an important factor influencing length of stay. Although they constitute a small proportion of back pain hospitalizations, persons younger than 18 years have longer stays for back pain, a ratio of 1.56 days longer, when compared to the average length of stay for all causes for this age group. After the age of 18 years, the length of hospital stays for back pain tend to increase as the population ages, however, similar patterns are seen with other diagnoses. (Reference Table 2A.10.2 PDF [194] CSV [195])

When comparing length of stay for all causes with those for low back pain, non-Hispanic white patient back pain visits compose 8% of both discharges and of total hospital days, approximately twice the proportion of discharges and of total hospital days reported by all other ethnic groups. However, the average length of stay tended to be slightly longer for non-Hispanic black (5.2 days) and Hispanic (5.1) patients than for non-Hispanic white patients (4.7 days). No considerable difference is observed in length of stay among geographic regions. (Reference Table 2A.10.3 PDF [196] CSV [197] and Table 2A.10.4 PDF [198] CSV [199])

Hospital Charges

Average hospital charges are provided along with length of stay in the HCUP NIS database. On average, hospital charges for a low back pain inpatient visit were 129% that of the average inpatient visit for any cause. In 2013, an estimated $120 million in charges were assessed against the 2.3 million inpatient stays for low back pain, 9% of the estimated total $1.2 billion in hospital charges for that year. Mean charges at $80,800 are highest for lumbar back injuries and, at $46,100, lowest for lumbar back disorders. When comparing male and female differences in the proportion of low back pain inpatient visit to total inpatient visit charges, no significant differences were found. Patients age 45-64 years and 65 years and older represent 83.7% of the total expenditure for low back pain hospital charges among the population. These age groups also demonstrate the highest proportion of total charges for all causes to those for low back pain, 10% on average. (Reference Table 2A.9 PDF [190] CSV [191]; Table 2A.10.1 PDF [192] CSV [193]; and Table 2A.10.2 PDF [194] CSV [195])

Variations in hospital charges by US geographic location are observed. The South region, whhich has the largest population, records the highest total hospital charges as well as total discharges among the geographic locations. Across ethnic groups, non-Hispanic white patients account for 76.7% of total charges for hospitalized persons with a diagnosis of back pain while comprising 65.5% of the population. However, the highest mean charges are found among thoses of Hispanic ethnicity. (Reference Table 2A.10.3 PDF [196] CSV [197] and Table 2A.10.4 PDF [198] CSV [199])

Cervical/neck pain is another common reason for visiting a doctor. In 2013, 21.4 million patient visits, or 1.8% of all healthcare visits to hospitals and physician offices, were for neck pain. Three out of four (73%) of these were physician visits, while only a small number (3%) of patients with neck pain were hospitalized. (Reference Table 2A.4.1 PDF [172] CSV [173])

Cervical disorders accounted for the majority (72%) of healthcare visits for neck pain in 2013. Neck disorders are primarily treated in outpatient clinics or physician offices but are also responsible for the highest percentage of hospital discharges (65%) for neck pain. Cervical disc disorders accounted for only 16% of all neck pain healthcare visits in 2013 but were responsible for one-third of hospitalizations (32%). Neck injuries accounted for 22% of all neck pain healthcare visits. This is a much higher percentage than that reported for low back injuries. Patients with neck injuries were primarily treated in an outpatient setting and represented 46% of all emergency department visits for neck pain and approximately one out of every five hospital outpatient and physician office visits. (Reference Table 2A.3.1 PDF [206] CSV [207])

 

Demographics of Cervical/Neck Pain

The data on cervical/neck pain shows that hospital discharges are rare in people younger than age 18 years. When adjusted for the US 2013 Census population, estimates for hospital discharges are highest in the 45-64 years age group. The average age for persons hospitalized for neck pain was 59.8 years. Emergency department visits occurred most frequently in patients aged 18-44 years with an average age of 44.3 years. The average age of patients for hospital outpatient and physician office visits was 49.9 years and 51.9 years of age, respectively. (Reference Table 2A.3.2 PDF [210] CSV [211])

Almost four of five neck pain diagnoses (77.2%) in 2013 occurred in persons between ages of 18 and 64 years. Almost one in five patients (19.7%) were older than 65 years, and only 3.1% were younger than 18 years of age, although this group represents 24% of the US population. The diagnosis category of "cervical disorders" dominated over cervical disc disorders and cervical injury diagnoses categories among total healthcare visits for neck and cervical spine disorders in all age groups. When comparing age groups, patients younger than 18 and patients aged 18-44 years experienced a larger percentage of neck injuries relative to all neck pain visits, 33.3% and 36.4%, respectively. (Reference Table 2A.3.2 PDF [210] CSV [211])

In 2013, females accounted for 59% of the healthcare visits for neck pain overall, 59% of cervical disorder visits, and 62% of neck injury visits. Males accounted for 53% of the visits for cervical disc disorders. (Reference Table 2A.3.1 PDF [206] CSV [207])

Non-Hispanic black and Hispanic patients display differences in choice of healthcare utilization for neck pain. Non-Hispanic black patients account for 29% of all outpatient visits; 20% are treated in a hospital outpatient clinic and 9% are treated in the physician office setting. In contrast, although Hispanic patients utilize outpatient settings to a similar degree (32%), 14% receive treatment in a hospital outpatient setting and 18% receive treatment in a physician’s office. When evaluating total healthcare visits for neck pain, non-Hispanic white patients account for most of the visits (57%), followed by Hispanic and non-Hispanic black patients (14%; 8%). (Reference Table 2A.3.3 PDF [218] CSV [219])

When adjusted for the US 2013 Census population, estimates for hospital discharges for cervical disorders are similar throughout the four US regions analyzed, but were highest in the South region for emergency department visits (3% of all visits for any diagnoses) and in the West region for outpatient visits (2.7%) and physician office visits (2.3%). Overall, healthcare visits for cervical disorders are highest in the western United States, representing 2.1% of visits for any diagnoses. (Reference Table 2A.3.4 PDF [220] CSV [221])

 

Hospitalization

Length of Stay

Persons hospitalized for neck pain in 2013 spent an average of 4.6 days in the hospital. Those hospitalized for neck injuries had the longest stay, on average 7.2 days. When comparing total days of hospitalization for all causes with those for neck pain, the average length of stay is similar. Overall, hospitatl stays for neck pain constituted 2% of both discharges and total hospital days in 2013. The length of hospital stays has remained relatively stable since 2004. (Reference Table 2A.8 PDF [188] CSV [189] and Table 2A.9 PDF [190] CSV [191])

Although females are likely to have slightly shorter hospital stays for all causes of neck pain, it is only for neck injuries that a significant difference is seen: 8.0 days for males versus 6.2 days for females. (Reference Table 2A.10.1 PDF [192] CSV [193])

Age is a greater factor in length of stay than gender. Although persons younger than 18 years of age constitute a small proportion of back pain hospitalizations, they have, on average, a stay that is 1.62 times longer than the average length of stay for persons in this age group for all causes. Hospital stays for neck pain are consistent between ages 18 to 64 years at 4.2 days, increasing to 5.1 days in the 65 years and older age group. (Reference Table 2A.10.2 PDF [194] CSV [195])

Average length of stay for non-Hispanic white patients for all cervical/neck pain is 4.4 days compared with 5.2 days for non-Hispanic black, non-Hispanic other, and Hispanic patients. The length of stay for neck injuries is longer by a day or more for non-Hispanic black, non-Hispanic other, and Hispanic patients compared with non-Hispanic white patients (6.9 to ≥ 8.0) . There is no significant difference in length of stay among geographic regions. The southern region of the United States reports the highest number of discharges and total hospital days for all causes, but this region also has a larger share of the population. (Reference Table 2A.10.3 PDF [196] CSV [197] and Table 2A.10.4 PDF [198] CSV [199])

 

Hospital Charges

Average hospital charges are provided along with length of stay in the HCUP NIS database. Hospital charges are not what is actally paid, but the initial charges from the hospital, which provide a measure for comparison purposes. On average, hospital charges for a neck pain inpatient visit were 148% that of the average inpatient visit for any cause. In 2013, an estimated $36 million in charges were assessed against the 614,200 inpatient stays for neck pain, 3% of the estimated total $1.4 billion in hospital charges for that year. Mean charges of $97,400 were highest for neck injuries and, at $52,900, lowest for neck disorders. (Reference Table 2A.9 PDF [190] CSV [191])

In patients with neck pain, the 45-64 and 65 years and older age groups collectively represent 81.8% of the total hospital charges among the population. Of note, the ratio of mean charges for cervical/neck pain to all hospital charges is highest in ages 18 years and younger (3.24), decreasing as the population ages. No considerable differences are reported between males and females in relation to hospital charges. (Reference Table 2A.10.1 PDF [192] CSV [193] and Table 2A.10.2 PDF [194] CSV [195])

Hispanic patients show the largest ratio of mean hospital charges for neck pain-related visits to total hospital visits, at 1.91. This is in comparison to the ratio of 1.53 and 1.42 for non-Hispanic blacks and non-Hispanic whites, respectively. Non-Hispanic white patients account for 73.2% of total spending for neck pain visits, primarily because they compose a larger share of the total population. (Reference Table 2A.10.3 PDF [196] CSV [197])

There is only a slight variation among geographic regions with regard to the ratio of hospital charges for neck pain visits to total hospital visit charges, with the West region of the US displaying the largest ratio of 1.57 based on mean charges per visit of $81,200. The northeastern United States has the smallest ratio,1.36, indicating charges were closer to the overall US average. The Midwest region had the lowest mean charges per visit. Reference Table 2A.10.4 PDF [198] CSV [199])

As discussed on previous pages, back pain was the most common reason for healthcare visits among musculoskeletal disorders in 2013. In 2013, nearly 1 in 4 persons (24.7%) in the United States had a healthcare visit with a diagnosis of back pain, accounting for 6.4% of healthcare visits for any cause. Three out of four visits (73%) were physician office visits and the number of physician office visits for back pain continues to increase. In 1998 there were 32 million visits in 2004 nearly 45 million, and in 2013 more than 57 million. Physician office visits for back pain not only show a rapid increase in number, but also continue to include a larger share of the population. In 1998, 11.8 in 100 persons visited a physician because of back pain. In 2004, this had increased to 15.1 persons in 100. Although a slight decrease was seen through 2008, by 2013 the ratio had increased to 18.1 persons in 100. Low back pain accounted for most of the increase in visits. (Reference Table 2A.4.1 PDF [172] CSV [173] and Table 2A.5 PDF [156] CSV [157])

With respect to sex, females accounted for 58% of total back pain healthcare visits in 2013, however, the rate of total back pain visits per 100 patients was slightly less than that of males (6.4 vs. 6.5). Persons ages 45 to 64 years had the highest rate of total back pain diagnosis per 100 patient visits (9.5), but those aged 65 and older had the highest rate per 100 persons in their age group (43.7). The rate of total back pain visits per 100 patient visits was similar across all race/ethnic groups and geographic regions, with non-Hispanic whites and residents of the northeastern United States having the highest rates per 100 persons (23.2 and 29.5, respectively). (Reference Table 2A.4.1 PDF [172] CSV [173]; Table 2A.4.2 PDF [228] CSV [229]; Table 2A.4.3 PDF [230] CSV [231]; and Table 2A.4.4 PDF [232] CSV [233])

 

Discharge Status

Most patients who present to a hospital emergency department with back pain are treated and routinely discharged to home from the emergency department (83.2%), with only a minority requiring admission to an inpatient unit (13.4%). These statistics are similar to all other emergency department discharges. When discharged from the hospital after a diagnosis of back pain, whether as a transfer patient from the emergency department or a direct hospital admission, routine discharges drop to about 60%, with 1 in 5 (22%-25%) discharged to another care facility and 13%-14% discharged with home health care. These numbers are somewhat higher than those found among all hospital discharges for any diagnoses. (Reference Table 2A.6 PDF [234] CSV [235])
 
No significant differences are observed in disposition of back pain visits to the emergency department or hospital between sexes, but females are slightly more likely to be discharged to another care facility or have home health care provided. When comparing age groups, a large majority of routine discharges are observed in patients aged 45 years or younger. The percentage of routine discharges is decreased by 10% to 82.6% for the 45 to 64 years age group, and is reduced by another 20% in the 65 years and older age group (60.6%). By age 65 and older, more than half of the discharges are to another care facility or with home health care. No meaningful differences are observed in the disposition of patients with respect to race/ethnicity. Residents of the Northeast region are the most likely to be discharged to additional care (40.5%). (Reference Table 2A.7.1 PDF [236] CSV [237]; Table 2A.7.2 PDF [238] CSV [239]; Table 2A.7.3 PDF [240] CSV [241]; and Table 2A.7.4 PDF [242] CSV [243])
 

 

Functional Limitations

Approximately 6% of the working age population, persons age 18 years and older, report they are unable to work or limited in the type of work they can perform because of a medical condition. Among this group, 25.8% reported they are unable to work due to back or neck problems. Similar ratios of limitations related to daily living are also found. Approximately 1 in  22 persons of working age has difficulty walking without equipment due to a medical condition; 24.8% report that condition to be back or neck pain. Overall, 13.5% of working-age persons report at least one limitation with activities of daily living, which include eating, preparing food, bathing, rising from a chair, walking up steps, etc. For one in five of these persons, the cause of their limitation is back or neck pain. (Reference Table 2A.11.1 PDF [164] CSV [165])

Age groups account for major differences in limitations due chronic back or neck problems. One in three patients age 65 years and older report they have limitations in activities of daily living (ADL), with 1 in 5 (19.2%) reporting ADL due to chronic back or neck pain. Among the 17% of persons with ADL for any cause in the 45 to 64 years age group, 29.9% list the cause is due to chronic back or neck problems. Of note, in this age group, chronic back or neck pain is the cause of each type of limitation, including inablity to work at all or type of work, for approximately 1 in 3 with limitations from any cause. No considerable differences are reported between males and females. (Reference Table 2A.11.1 PDF [164] CSV [165] and Table 2A.11.2 PDF [248] CSV [249])

Although the race/ethnic group classified as non-Hispanic others represents a small proportion of the total population, they report the lowest rates of limitations in activities of daily life. Hispanic patients report fewer limitations due to any health condition (9.8%) than non-Hispanic whites (15.1%) and non-Hispanic blacks (16.1%). Among persons with limitations due to any cause, non-Hispanic whites (20.8%) and non-Hispanic black patients (19.5%) have comparatively higher percentages of limitations due to chronic back or neck problems compared with Hispanic patients (15.1%), with the exception of difficulty walking without equipment. No significant differences are seen among geographic regions in ADL. (Reference Table 2A.11.3 PDF [250] CSV [251] and Table 2A.11.4 PDF [252] CSV [253])

 

Lost Work Days/Bed Days

Self-reported bed days and work days lost due to back or neck pain have fluctuated over the past decade. Both recorded their highest totals in 2008, registering 385,000 lost work days and 671,000 bed days. Both bed days and work days lost have remained steady since 2012. (Reference Table 2A.12 PDF [254] CSV [255])

Work days lost due to spine pain or spine problems were more frequently reported by females than males during 2015 (17.4% vs. 13.5%). However, females, on average, lose one less day of work than do men (9.9 to 11.2, respectively).  (Reference Table 2A.13.1 PDF [256] CSV [257])

Back pain severe enough to keep people from working in any occupation is most likely to occur in the 18 to 64 years age group, accounting for 14.8% of persons in the 18 to 44 years age group, and 16.9% of persons in the 45 to 64 years age group. This is, of course, not surprising since those are the most common years in which people work. The average number of workdays lost was 8.6 and 12.5 days for the two age groups, respectively. The oldest group of workers, age 65 years and older, report more than 16 days of work lost due to spine pain or problems, but they constitute such a small group that their impact is less than that of younger workers. (Reference Table 2A.13.2 PDF [260] CSV [261])

When comparing ethnic groups, Hispanic persons record the highest average number of work days lost due to spine pain (14.1), followed by non-Hispanic whites and non-Hispanic blacks (10.1 days; 9.9 days). No meaningful difference by share of workforce is observed in average number of work days lost due to spine pain according to geographic region, but workers in the Northeast and Midwest regions of the US lose the most days, on average (11.6 and 12.1, respectively). (Reference Table 2A.13.3 PDF [262] CSV [263] and Table 2A.13.4 PDF [264] CSV [265])

The National Health Care Interview Survey also provides information about the incidence of bed days, days in which a person was in bed for a half day or more due to injury or illness, during 2015. The average number of bed days per worker for all spine pain or problems was 7.8 days. On average, males reported taking 8.5 bed days compared to 7.3 bed days taken by females. The percent of people in the workforce reporting bed days due to spine pain or problems is higher in the 18 to 44 years and 45 to 64 years age groups (13.8% and 15.3%, respectively) than for those age 65 and over. This is likely due to the health status of older workers, who tend to be healthy if they are still in the workforce. Between these two age groups, persons 45 to 64 take approximately 3 more bed days than persons 18 to 44 (9.0 vs 6.2). Persons in the 65-year and older age group have the highest average bed days lost per worker due to spine pain or problems (14.9) however, a smaller proportion (11.8%) of this already small workforce reported having bed days from spine pain. Non-Hispanic white and non-Hispanic black persons recorded more bed days due to spine pain or problems (8.2; 8.7) than Hispanic persons (6.3). Comparing geographic regions, patients in the Midwest report the most bed days for spine pain (10.1), more than all other regions. (Reference Table 2A.13.1 PDF [256] CSV [257]; Table 2A.13.2 PDF [260] CSV [261]; Table 2A.13.3 PDF [262] CSV [263]; and Table 2A.13.4 PDF [264] CSV [265])

In total, 52.2 million adults in the US workforce spent more than 182 million days in bed in 2015 because of back pain, and during the same time period, almost 264 million work days were lost. The corresponding numbers of days in bed and work days lost in 2012 were 171 million and 291 million, respectively. Approximately one-third of the total workforce (31.9%) reported bed or lost work days due to back pain, but accounted for more than half of total bed days (54%0 and nearly half of total lost work days (47%). The 111.4 million workers not reporting back pain as the cause had 152.9 million bed days and 299.5 million lost work days in 2015. (Reference Table 2A.13.1 PDF [256] CSV [257])

 

While nonsurgical treatment for back pain is the treatment of choice, spine surgery becomes an option when neck and low back pain is disabling and not responding to nonoperative treatment alternatives. Further, in some cases such as certain fractures, infections, tumors, and severe neurologic deficits, surgery is the first treatment choice. As mentioned in earlier sections, the information we have with respect to surgical procedures is limited to that obtained from hospitals using the Nationwide Inpatient Sample. Unfortunately, the information is procedure-related and only indirectly patient-related.

In 2007, just under 1.2 million procedures for the eight most common spine procedures were performed on 662,400 patients in hospitals. In 2011, the number of patients had increased to 741,700 with a corresponding  increase in the number of hospital procedures to 1.4 million. In 2013, the number of patients receiving the most common procedures, which added epidural injections to the earlier list of eight procedures, decreased to 692,585, while total procedures decreased slightly to 1.3 million. (Reference Table 2A.15 PDF [272] CSV [273])

The number of spinal decompression procedures performed, along with other procedures for which inpatient hospitalization is not always required, may not be reflected accurately because an increasing number of these patients are operated on in outpatient surgicenters and facilities. This can be, in part, illustrated here. In 2011, there were 369,900 diskectomies performed compared with 316,700 in 2013. Spinal fusion procedures were listed as the main hospital procedure, being performed 457,500 times in 2011 and 434,500 times in 2013. The majority of insertions of spinal devices, the third most common procedure group, likely occurred in patients with spinal fusions. Spinal decompression, which may or may not be performed in conjunction with a spinal fusion or in conjunction with a diskectomy, accounted for 12.5% of all procedures in 2011 and 11.8% in 2013. Changes in procedure codes for decompression between 2011 and 2013 may have partly been the cause of fewer reported decompression procedures. (Reference Table 2A.15 PDF [272] CSV [273])

Compared to the inpatient hospital setting, other healthcare sites offer a limited variety of spinal procedures. In the emergency department (ED) setting, epidural injections accounted for over 6,000 procedures, more than half of the 12,000 total procedures reported in the ED. The only procedures recorded in physician office visits were epidural injections, but they accounted for the majority of epidural injections in 2013 and reflect the variety of healthcare sites in which epidural injections can be administered. (Reference Table 2A.14 PDF [276] CSV [277])

 

Spinal Fusion

The rate of spinal fusion procedures has risen rapidly over the past several decades. Spinal fusion is performed either alone or in conjunction with decompression and/or reduction of a spinal deformity. Fusions are performed on all regions of the spine. Lumbar fusion rates and cervical fusion rates are both increasing rapidly, while thoracic fusions continue to be less frequent. Lumbar fusions remain the most common, constituting 52% of all spine fusion procedures in 2013. Spinal refusion occurs most often to the lumbar region, accounting for 65% of both refusion procedures and refusion patients. (Reference Table 2A.16.1 PDF [280] CSV [281])

Between the years 1998 and 2013, the number of spinal fusion procedures more than doubled, from 220,000 in 1998 to 445,000 in 2013. This is a 137% increase in procedures over a 16-year period. The period from 2004 to 2011 reflected an increase of 61%, but from 2011-2013 there was a 15% decrease in recorded spinal fusions performed, most likely due to a larger proportion of these procedures being performed at an outpatient site. The rate of adult patients undergoing spinal fusion has increased from 110 per 100,000 persons in 1998 to 183 per 100,000 in 2013. During the same time period, refusion rates increased by 187% and from 6 to 13 persons per 100,000. Between 1998 and 2013, the average age of patients undergoing a fusion procedure has increased from 49.0 years to 56.4 years. (Reference Table 2A.16.2 PDF [284] CSV [285])

 

Length of Stay/Hospital Charges

Although the mean length of stay for spinal fusion has decreased from 4.7 days in 1998 to 3.9 days in 2013, the mean hospital charge for these patients has increased significantly. The mean hospital charge in 1998 was $26,000 ($37,200 in 2013 dollars); while in 2013 the mean charge was $112,000. Increased use of instrumentation and biologicals (mainly bone substitutions) contribute to the higher cost. The total increase in hospital charges rose from $5.4 billion ($7.6 billion in 2013 dollars) to $48.7 billion over this 16-year period, an increase of more than 542%. Spinal refusion procedures are even more expensive, with an average charge of $129,000 in 2013, while the length of stay remained relatively constant. This, of course, does not mean that cost or reimbursement was even close to these dollar numbers. These charges are based on what hospitals set as their charges, and do not reflect the contractual agreements they have with the payer community. (Reference Table 2A.16.2 PDF [284] CSV [285])

Likely explanations for the increase in spinal fusions include advances in technology, such as the development of new diagnostic techniques and new implant devices that allow for better surgical management. In addition, there has been increased training in spinal surgery and the population has aged, presenting an increase in age-related medical problems. Further, higher expectations regarding quality of life makes patients less accepting of an ongoing back problem and more likely to look for a surgical solution.

Using the Nationwide Inpatient Sample in 2013, a broad estimate can be made of fusion procedures as it relates to admissions. In 2013, 14.6% of patients discharged with a diagnoses of back pain had a spinal fusion procedure. Males (15.4% of back pain discharges) and females (13.9%) are almost equally likely to have a fusion. Patients in the 45- to 64-year age group were slightly more likely to have a fusion procedure (19.2%) than those in the 18- to 44- years age group (15%), or in the 65- years and older age group (10.5%). Patients younger than age 18, at 24.2%, were most likely to undergo a fusion procedure when hospitalized with a diagnosis of back pain, but they constitute a very small group of patients (1.6%) among those discharged with a diagnoses of back pain. Non-Hispanic white patients hospitalized with back pain were most likely to receive a fusion (15%) when compared to non-Hispanic black (12%) and Hispanic (13%) patients. Patients in the southern United States were most likely to undergo a fusion procedure (15.7%). Patients in the western United States were second most likely to receive a spinal fusion, followed by patients in the Northeast (13.8%) and Midwest (13.3%). The length of stay was shorter if a fusion was performed than if no fusion was performed (3.9 days vs. 4.8 days), but the mean charges were more than doubled for a back pain diagnosis when a fusion was performed ($52,630 vs $110,960). (Reference Table 2A.17 PDF [290] CSV [291])

 

Primary Diagnosis

Information on the top twenty primary diagnoses and accumulative first five diagnoses for spinal fusion procedures performed in 2013 illustrates the procedure is most frequently performed in patients with lumbar spinal stenosis with or without neurogenic claudication. Lumbar disc degeneration or cervical disc displacement account for 9.6% and 9.5% of fusion procedures, respectively. (Reference Table 2A.18 PDF [294] CSV [295])

 

Disk Displacement and Spinal Diskectomy

Diskectomy procedures, a surgical procedure to remove the damaged portion of a herniated disk, occurred in approximately 317,000 hosptial inpatients in 2013, with slightly more females than males undergoing the procedure. This number is likely misleading because many diskectomy procedures now occur in an outpatient setting. Of those undergoing the procedures, 35.3% had a diagnosis of either lumbar or cervical disc displacement, while 12% had a diagnosis of either lumbar or cervical disk degeneration. Approximately half of all diskectomy procedures were performed on persons in the 45 to 64 years age group, with an average age of 55.3 years. Across ethnic groups, the average age of presentation when undergoing diskectomy procedure was in the mid-50s. Non-Hispanic white patients accounted for 76% of total discharges, followed by non-Hispanic black (7.7%) and Hispanic (5.8%) patients. When comparing geographic regions, a discrepancy in charges per diskectomy was observed. The South region of the US reported the highest number of total discharges, roughly 41% of all diskectomy procedure discharges, bu this is non-unexpected given the larger share and older age of the population in the South. The Midwest ranked second in total discharges with 21%, followed by the West (20%) and Northeast (17%). (Reference Table 2A.19 PDF [298] CSV [299] and Table 2A.20 PDF [300] CSV [301])

Patients spent, on average, 3.0 days in the hospital for diskectomy procedures, a surprising number given the recent trends in discharge the same day. Although accounting for a very small number of procedures, persons younger than age 18 years had an average length of stay of 6.8 days. The mean charge for these procedures in 2013 dollars was $87,280. The western United States reported the highest charges, averaging $116,000 per procedure. This is significantly higher than the rest of the country, with the South at an averaged of just below $88,000, while the Northeast and Midwest regions were approximately $72,000. Hispanic patients averaged the highest mean charges for diskectomy procedures, estimated at $110,180. This is in comparison with a $92,730 mean charge for non-Hispanic black patients and a $86,740 mean charge for non-Hispanic white patients. (Reference Table 2A.19 PDF [298] CSV [299])

Table 2A.21 shows the diskectomy procedure trend in the United States from 1996 to 2013. It may seem surprising that the number is fairly stable given the population increase and the change in aging of the population. This is a reflection of the fact that more and more of these procedures are done in the outpatient setting and therefore not captured by the inpatient National Hospital Discharge Survey. (Reference Table 2A.21 PDF [304] CSV [305])

 

Persons aged 45-64 years self-report the presence of back and neck pain during a previous 3-month period in the highest numbers, at almost 27.9 million cases. Although a smaller number due to the smaller population cohort, when comparing the prevalence of all back pain, age groups 45-64 years and 65 years and older are almost identical, roughly 39% of each age group. (Reference Table 2A.1 PDF [158] CSV [159])

Healthcare visits for back disorders to doctors, emergency departments, outpatient clinics, and hospital discharges show a steady rise as the population ages up to 64 years. After that, it drops slightly. Older persons with back pain disorder are more likely to be hospitalized than are younger persons, and to stay an average of 0.5 days longer than younger persons aged 18 to 64 years. Average charges for hospital stays with a diagnosis of back pain also increase with age. While the prevalence of neck disorders is significantly lower, aging also has a large impact on the number of healthcare visits for neck pain. (Reference Table 2A.2.2 PDF [176] CSV [177] and Table 2A.10.2 PDF [194] CSV [195])

Limitations of daily living due to chronic back pain increase in prevalence as the population ages. Back pain is listed as a cause of limitations by 6.4% of persons 65 and older, compared to 2.7% of the total population. Back pain represents the cause of limitations for roughly 1 in 5 persons with limitations due to any cause for both all persons and those age 65 and older (19.7% and 19.2%, respectively). (Reference Table 2A.11.2 PDF [248] CSV [249])

Back pain is a major health concern to older people. As the population ages, back pain becomes an increasing burden on the healthcare system.

Economic burden in The Burden of Musculoskeletal Diseases (BMUS) is based on data from the AHRQ Medical Expenditure Panel Survey (MEPS). The MEPS, which began in 1996, is a set of large-scale surveys of families and individuals, their medical providers (doctors, hospitals, pharmacies, etc.), and employers across the United States. MEPS collects data on the specific health services that Americans use, how frequently they use them, the cost of these services, and how they are paid for, as well as data on the cost, scope, and breadth of health insurance held by and available to US workers. Data reported in BMUS is based on three-year averages for each sequence of years.

Between the years 1996 to 1998 and 2012 to 2014, the number of persons in the population reporting a spine condition rose from 27.4 million to 34.9 million, but the proportion of total population with a spine condition (10.1% vs 11.0%) increased only slightly over the nearly two decades. However, distribution of the population with a spine condition, by age group, showed a consistent shift upward as the population ages, reflecting the overall aging of the US population. (Reference Table 8.12 PDF [145] CSV [146])

Healthcare treatments and visits contribute to the burden of spine conditions. Ambulatory physician visits, home health care visits, and hospital discharges all rose by 34%, 46%, and 28%, respectively, between the years 1996 to 1998 and 2012 to 2014. Mean visits for these three healthcare providers and share of spine patients using them remained relatively steady, indicating the primary reason for the increase is population growth. While still accounting for a relatively small number of visits, ambulatory non-physician care visits rose from 101 million in the earlier time frame to 220 million in the most recent years, an increase of 117%, due to both an increase of spine patients using this resource and a jump in mean visits.

However, prescription medications for spine conditions show the most dramatic rise, jumping from 353 million prescription fills to 789 million between the time frames, an average increase per year of 7.3% with a total increase of 123%. This increase was due primarily to the increase in mean number of refills per person, from 12.0 to 22.6, rather than the share of persons with a spine condition obtaining prescriptions, an increased share of only 3.5%.  (Reference Table 8.2.2 PDF [310] CSV [311])

 

Direct Medical Costs

Overall, ambulatory care visits (physician office visits, non-physician visits, and home health care visits) accounted for the largest share of per person direct cost for persons with a spine condition. At an average cost of $3,220 per person between 2012 and 2014, an increase of 82% from 1996 to 1998 in 2014 dollars, ambulatory care accounted for 36% of per person direct cost between 2012 and 2014. While the share of mean per person cost for inpatient care dropped from 36% to 25% between 1996 and 1998 and 2012 and 2014, the mean cost rose from $1,823 to $2,258 in 2014 dollars, an increase of 24%. At the same time, the average per person cost for prescriptions rose from $675 to $2,263, in 2014 dollars, an increase of 235%. (Reference Table 8.4.2 PDF [314] CSV [315])

Total direct per person healthcare costs for persons with a spine condition were $9,035, an increase of 80% since 1996 to 1998 based on 2014 dollars. Incremental direct per person costs, those costs most likely attributable to a spine condition, rose from $970 to $1,615, in 2014 dollars, an increase of 66%. (Reference Table 8.6.2 PDF [166] CSV [167])

Total aggregate direct costs for all persons with a spine condition were $315.4 billion in 2012 to 2014, a rise of 129% from the $13 billion in 1996 to 1998, in 2014 dollars. Incremental aggregate direct costs increased from $26.6 billion in 1996 to 1998 to $56.4 billion in 2012 to 2014, an increase of 112%. (Reference Table 8.6.2 PDF [166] CSV [167])

 

Indirect Costs (Society/Employers)

Indirect costs associated with lost wages for persons ages 18 to 64 years are not calculated for persons with a spine condition. However, back pain is often cited as the reason for bed days and lost work days by persons in the labor force. In 2015, 4.9 million persons in the prime working ages of 18 to 64 years reported they are unable or limited in work at the time due to chronic back or neck problems. (Reference Table 2A.11.2 PDF [248] CSV [249])

Also, in 2015, 14.3% of the workforce age population reported an average of 7.8 bed days in the previous 12 months, for a total of 182 million bed days, due to chronic back or neck pain. In addition, 15.4% of this same population reported an average of 10.5 lost work days in the previous year due to chronic back or neck pain, or approximately 264 million work days lost due to back pain. (Reference Table 2A.13.1 PDF [256] CSV [257])

 

The financial cost associated with back pain is obviously enormous and, unfortunately, rising. At the current rate of increase, back pain treatment will quickly become unsustainable. Greater understanding of the underlying causes of back pain, ability to sub-classify patients based on accurate pain generators (eg, discogenic pain, facet mediated pain, radicular pain) and what factors lead to disability (ie, biological, psychological, or social) is needed to reduce this continually increasing trend. Ideally, understanding the variability of individual sources of and contributions to back pain could direct clinicians to specific treatments that best address the diagnosis. 

The cost and difficulty of back pain research is also a major challenge. The complexity of back pain diagnosis and treatment options make high quality clinical research with meaningful results very difficult to fund and complete. This requires large scale multi-center trials with well-educated research staff and patients willing to stick with randomized modes of treatment. The latter consideration is often very difficult to obtain in a system where patients want immediate results. In addition, many non-surgical, non-pharmacological providers use a multimodal approach to care rather than an isolated intervention, complicating efforts to identify which treatment is most effective.

Adding to this challenge may be the subjective nature of pain. It is often very difficult, if not impossible, to separate psychological or emotional pain that is greatly influenced by the social environment from physiologic pain caused by a specific physical source. Differentiating between the two categories will play a tremendous role in our ability to treat patients in pain. Societal perceptions about back pain have been shown to lead to catastrophization, a common cognitive distortion extensively studied in psychology that is an irrational thought or belief that something is far worse than it actually is. Studies in pain patients have found catastrophization to be a significant factor in their disability and response to treatment.

System integration of historically fringe practitioners is a challenge as we attempt to grow effective non-surgical management strategies such as acupuncture, massage, tai chi, yoga, and chiropractic. Training practitioners to provide evidence-based informed care plans and appropriate referrals for other services or emergent conditions should start early in medical training. Improved graduate and post-graduate education which includes integrating educational tracks to better understand different disciplines of care and what they can offer can create a shared common base of critical thinking. For example, Denmark provides the first year medical school education to chiropractors and physicians jointly before diverging to more specific training.

Another challenge to the future is our healthcare financial system. Treatment decisions are too often made based on financial limitation rather than best clinical practice. Clinical decisions may be limited by insurance authorizations or treatment decisions, and could be influenced by highest reimbursement. Cost-effectiveness and risk/benefit discussions for alternative options are essential to providing successful treatments and reducing costs.

Understanding why the degenerative cascade causes pain in some, yet not in others, is needed to address the burden of pain and disability and the significant economic impact low back pain treatments create on healthcare resources each year.

One of the greatest unmet needs related to back pain is the ability to clearly diagnose the source of back pain. There are so many physical and non-physical sources of back pain that patients are often treated inappropriately before they are clearly diagnosed. Thousands of dollars are often spent on diagnostic evaluations without finding a clear source of back pain, a process that needs to be broken by earlier diagnosis, earlier definitive treatment, and maintenance of the ability to continue working.

Most patients with back and neck pain are treated non-operatively, often with alternative treatments, including such treatments as acupuncture, homeopathy, and massage. We know that enormous amounts of money are spent on many of these treatments, yet no quantifiable measures of cost or effect are yet available. Furthermore, the lack of information about treatments by chiropractors, physical therapists, and other care providers results in underestimated cost estimates for treatment of low back pain. There is also a lack of information on medical procedures done in offices or surgicenters, limiting estimates of cost and effectiveness of many interventional procedures, including many surgical procedures. These gaps in knowledge should be filled to obtain accurate estimates of the impact of back and neck pain on society.

As such, there remains debate regarding the most effective treatment for low back pain. Increased recommended alternatives to non-surgical options adds credence for improved informed consent, creating conversation about benefits and risks and leading to a better shared decision making process for the patient. Though research is limited, per Zaina et al, informing the patient of anticipated outcomes of not only surgery but other options is vital. In a systematic review performed by Zaina et al, the authors evaluated the effectiveness of different types of surgery compared with different types of non-surgical intervention in the treatment of low back pain secondary to lumbar spinal stenosis (LSS).1 The authors’ analysis demonstrated no differences in pain-related disability improvement between surgical (decompression with or without fusion) and non-surgical care. However, due to the low quality of available studies, the authors were unable to confidently recommend a preferable treatment method for symptomatic LSS.

To begin addressing these needs, there has been an increase in research on the efficacy of non-surgical interventions for low back pain. Ammendolia et al investigated the safety and effectiveness of epidural injections to other treatments for symptomatic LSS.2 Due to the low overall evidence (only 4 randomized controlled trials), the authors were only able to conclude that epidural injections provide improved pain, function, and quality of life for only up to 2 weeks.

Another area of increased interest is the effect of pre- and postoperative spinopelvic parameters (the relationship of the pelvic position to the spine) on treatment outcomes. Several previous investigations have described the magnitude of parameter correction afforded by surgical and non-surgical treatment modalities. However, many of these studies have featured small sample sizes and have rarely offered level I or II evidence. As such, there exists a need for large, prospective studies that investigate the true impact of influence of spinopelvic parameters on treatment outcomes for low back pain.

Acupuncture has been utilized in the treatment of low back pain for centuries, and has recently been established as a non-operative complimentary treatment in the United States.3 A meta-analysis evaluating the use of acupuncture in the treatment of low back pain demonstrated the use of acupuncture as a complimentary, highly cost-effective treatment.4 According to the World Health Organization (WHO) cost-effectiveness threshold values, the cost of complimentary acupuncture treatment was determined to be $48,562 per disability-adjusted life year (DALY) avoided. Interestingly, in patients where comorbid depression was also alleviated at the same rate as pain, the cost was revealed to be $18,960 per DALY avoided. The authors concluded that acupuncture, as a substitute for standard care, was most cost-effective when used in patients with comorbid depression.

As noted in the previous discussion of Indirect Costs [322], back pain was the cause of close to 264 million lost work days in a 12-month period during 2014-2015. In addition, over 4%, or 1 in 25, persons in the prime working ages of 18 to 64 report they are either limited in the type or amount of work they can do or are unable to work at all due to back pain. It is clear that back pain has a substantial impact on the workforce, and that finding ways to reduce or repair causes of back pain is needed. (Reference Table 2A.11.2 PDF [164] CSV [165])

In general, there is a need for high quality clinical research in treatment of low back pain. This includes addressing the lack of evidence for best practices for non-surgical active care approaches and surgical treatment. Additionally, work-related back pain has the potential to become "chronic" back pain, often with co-morbid dependence on narcotic pain medications. This process needs to be broken by earlier diagnosis, maintenance of ability to continue working, and earlier definitive treatment.

There is a need to promote a culture of "stopping back pain before it starts" by adopting spine care procedures, such as proper posture and balance exercise regimes, by persons of all ages as a counter to back pain. In addition to BMUS, the World Spine Care and Global Spine Care Initiative are coalitions all working to find ways to reduce back pain and back pain costs.

• 1. Zaina F, Tomkins-Lane C, Carragee E, Negrini S. Surgical versus non-surgical treatment for lumbar spinal stenosis. Cochrane Database Syst Rev. 2016(1):CD010264.
• 2. Ammendolia C, Stuber KJ, Rok E, et al. Nonoperative treatment for lumbar spinal stenosis with neurogenic claudication. Cochrane Database Syst Rev. 2013(8):CD010712.
• 3. Chao R, Qaseem A, Snow V, et al. Diagnosis and treatment of low back pain: A joint clinical practice guideline from the American College of Physicians and the American Pain Society Ann Intern Med. 2007;147(7):478-491.
• 4. Taylor P, Pezzullo L, Grant SJ, Bensoussan A. Cost-effectiveness of acupuncture for chronic nonspecific low back pain. Pain Pract. 2014;14(7):599-606.

Back Pain (Lumbar and Low Back):
    Back Disorders:
        Ankylosing spondylitis and other inflammatory spondylopathies:  720*
        Spondylosis and allied disorders:  721.2-721.9
        Other and unspecified disorders of back:  724
    Disk Disorders:
        Displacement of intervetebral disc:  722.10, 722.11
        Schmorl's nodes:  722.30-722.39
        Degeneration of intervetebral disc:  722.51, 722.52, 722.60
        Intervertebral disc disorder with myelopathy:  722.72, 722.73
        Postlaminectomy syndrome:  722.80, 722.82, 722.83
        Other and unspecified disc disorder:  722.90, 722.92, 722.93
    Back Injury:
        Closed fracture of vertebra without mention of spinal cord injury:  805.20-805.80
        Closed fracture of vertebra with spinal cord injury:  806.20-806.90
        Closed dislocation, vertebra:  839.20-839.49
        Sprains and strains of sacroiliac region:  846
        Other sprains and strains of back:  847.10-749.90

Cervical (Neck) Pain:
    Neck Disorders:
        Cervical spondylosis:  721.00, 721.11
        Disorders of cervical region:  723.00-723.90
    Disk Disorders:
        Displacement of cervical intervertebral disc:  722.00
        Degeneration of cervical intervertebral disc:  722.40
        Intervertebral disc disorder, with myelopathy:  722.71
        Postlaminectomy syndrome of cervical region:  722.81
        Other and unspecified disc disorders of cervical region:  722.91
    Neck Injury:
        Closed fracture of cervical vertebra without mention of spinal cord injury:  805
        Closed fracture of cervical vertebra with spinal cord injury:  806
        Closed dislocation, cervical vertebra:  839
        Neck sprain:  847.00

Spine Procedures (ICD-9-CM Procedures Code)
        Cervical fusion:  81.02, 81.03
        Thoracic fusion:  81.04, 81.05
        Lumbar fusion:  81.06-81.08
        Other fusion:  81.00, 81.01
        Fusion/refusion multiple vertebrae:  81.62-81.64
        Spine refusion:  81.30-81.39
        Spinal decompression:  03.09
        Spinal diskectomy:  80.50, 80.51

 

ICD-9-CM to ICD-10-CM CODE CONVERSION

Direct conversions between the ICD-9-CM codes used in this analysis to ICD-10-CM codes is difficult due to the greatly expanded diagnosis codes in ICD-10-CM. For example, converting the six codes included in the Lumbar/Low Back Back Disorders group returns only six general or unspecified codes related to the spondylopathies whereas, in reality, there are five major classifications (M45, M46, M47, M48, M49) each of which is broken down into specific conditions that are further broken down by site. For example, using only the M45 and M46 codes (shown below) there are 80 new codes.

     M45 Ankylosing spondylitis
        M45.0 Ankylosing spondylitis of multiple sites in spine
        M45.1 Ankylosing spondylitis of occipito-atlanto-axial region
        M45.2 Ankylosing spondylitis of cervical region
        M45.3 Ankylosing spondylitis of cervicothoracic region
        M45.4 Ankylosing spondylitis of thoracic region
        M45.5 Ankylosing spondylitis of thoracolumbar region
        M45.6 Ankylosing spondylitis lumbar region
        M45.7 Ankylosing spondylitis of lumbosacral region
        M45.8 Ankylosing spondylitis sacral and sacrococcygeal region
        M45.9 Ankylosing spondylitis of unspecified sites in spine

    M46 Other inflammatory spondylopathies
        M46.0 Spinal enthesopathy
            M46.00 …… site unspecified
            M46.01 …… occipito-atlanto-axial region
            M46.02 …… cervical region
            M46.03 …… cervicothoracic region
            M46.04 …… thoracic region
            M46.05 …… thoracolumbar region
            M46.06 …… lumbar region
            M46.07 …… lumbosacral region
            M46.08 …… sacral and sacrococcygeal region
            M46.09 …… multiple sites in spine
        M46.1 Sacroiliitis, not elsewhere classified
        M46.2 Osteomyelitis of vertebra
            M46.20 …… site unspecified
            M46.21 …… occipito-atlanto-axial region
            M46.22 …… cervical region
            M46.23 …… cervicothoracic region
            M46.24 …… thoracic region
            M46.25 …… thoracolumbar region
            M46.26 …… lumbar region
            M46.27 …… lumbosacral region
            M46.28 …… sacral and sacrococcygeal region
        M46.3 Infection of intervertebral disc (pyogenic)
            M46.30 …… site unspecified
            M46.31 …… occipito-atlanto-axial region
            M46.32 …… cervical region
            M46.33 …… cervicothoracic region
            M46.34 …… thoracic region
            M46.35 …… thoracolumbar region
            M46.36 …… lumbar region
            M46.37 …… lumbosacral region
            M46.38 …… sacral and sacrococcygeal region
            M46.39 …… multiple sites in spine
        M46.4 Discitis, unspecified
            M46.40 …… site unspecified
            M46.41 …… occipito-atlanto-axial region
            M46.42 …… cervical region
            M46.43 …… cervicothoracic region
            M46.44 …… thoracic region
            M46.45 …… thoracolumbar region
            M46.46 …… lumbar region
            M46.47 …… lumbosacral region
            M46.48 …… sacral and sacrococcygeal region
            M46.49 …… multiple sites in spine
        M46.5 Other infective spondylopathies
            M46.50 …… site unspecified
            M46.51 …… occipito-atlanto-axial region
            M46.52 …… cervical region
            M46.53 …… cervicothoracic region
            M46.54 …… thoracic region
            M46.55 …… thoracolumbar region
            M46.56 …… lumbar region
            M46.57 …… lumbosacral region
            M46.58 …… sacral and sacrococcygeal region
            M46.59 …… multiple sites in spine
        M46.8 Other specified inflammatory spondylopathies
            M46.80 …… site unspecified
            M46.81 …… occipito-atlanto-axial region
            M46.82 …… cervical region
            M46.83 …… cervicothoracic region
            M46.84 …… thoracic region
            M46.85 …… thoracolumbar region
            M46.86 …… lumbar region
            M46.87 …… lumbosacral region
            M46.88 …… sacral and sacrococcygeal region
            M46.89 …… multiple sites in spine
        M46.9 Unspecified inflammatory spondylopathy
            M46.90 …… site unspecified
            M46.91 …… occipito-atlanto-axial region
            M46.92 …… cervical region
            M46.93 …… cervicothoracic region
            M46.94 …… thoracic region
            M46.95 …… thoracolumbar region
            M46.96 …… lumbar region
            M46.97 …… lumbosacral region
            M46.98 …… sacral and sacrococcygeal region
            M46.99 …… multiple sites in spine

and so on. Future analysis for BMUS will require identification of new categories for analysis of spine low back and neck diagnoses.

Conversion of the spine procedure codes was made and can be viewed by clicking HERE [323]. Again, the number of codes is greatly expanded, with more than 650 new codes representing the 25 spine procedure codes analyzed in this Fourth Edition of The Burden Of Musculoskeletal Diseases in the United States.

 

Conditions related to the spine and spinal deformity often sound similar but affect the spine in different ways. Key conditions discussed in this section include the following.

Curvature of the spine: Spine curvature can refer to two distinct conditions. The human spine normally curves, but more commonly the term "spinal curvature" refers to abnormalities from the standard spinal.
•    Idiopathic: Of unknown cause. Any disease that is of uncertain or unknown origin may be termed idiopathic; usually associated with children who develop an abnormal curvature at a young age.
•    Acquired: Curvature that develops over many years, usually associated with adults and older persons.
•    Secondary: Curvature caused by another condition, such as osteoporosis.

Sagittal imbalance: Deformity where loss of the normal lordosis of the lumbar spine or increased kyphosis of the thoracic and thoracolumbar spine causes the torso and head to pitch forward relative to the hips and pelvis. Loss of lordosis in the lumbar spine is also known as flat back syndrome.

Scoliosis: Side-to-side abnormal curvature of the spine.

Spondylolisthesis: Forward movement of one vertebra in relationship to a vertebra below it.

Spondylosis: Degeneration of the disc spaces between the vertebrae. Spondylosis is common with aging and affects virtually everyone to some degree after the age of 60 years. When severe, it can cause local pain and decreased range of spinal motion, requiring pain and/or anti-inflammatory medications.

Stenosis: A narrowing of the open spaces within the spine, which can put pressure on the spinal cord and the nerves that travel through the spine. Spinal stenosis occurs most often in the neck and lower back.

Kyphosis: An abnormal, convex curvature of the spine, with a resultant bulge at the upper, middle or lower back.

Spinal fractures:
•    Traumatic spine fractures (TF): High-energy fractures resulting from accidents, falls, and sports.
•    Vertebral compression fractures (VCF): Low-energy fractures in the aging as a result of reduced bone density and strength (osteoporosis and osteopenia).

Spinal infection:
•    Tuberculosis of spine: An infection that usually occurs in the lungs, but can also occur in the spine, resulting in destruction of the intervertebral disk space and adjacent vertebral bodies. It is more common in children and young adults.
•    Intraspinal abscess: A collection of pus and infectious material in the spine.
•    Osteomylitis: A bone infection normally caused by bacteria but sometimes by fungus. The infection can occur in any bone but typically affects the arms, legs, spine, and pelvis. The bacteria usually reach the bone from an injury or wound. It can be either acute, where symptoms of pain, swelling, and fever last only a few months, or chronic.
•    Discitis: Infection exists in the small spaces between these bones (the intervertebral disc spaces), which puts pressure on the discs and causes pain. Discitis is relatively uncommon and mostly affects young children.
•    Postoperative infections: Infections after surgical procedures (operations) can cause pain, poor wound healing, need for further treatment including antibiotics, longer hospital stays, and increased healthcare costs.
Complications of surgery: Common surgery complications, including excessive blood loss, pain, infection, neural injury, anesthesia effects, blood clots, and other medical complications (heart attack, stroke).

Spondylopathies: Any disease of the vertebrae or of the spinal column.

Surgical procedures: Often performed to reduce pain and deformity from spinal curvature including osteotomies ( complete or partial removal of the vertebral bodies), spinal instrumentation, and fusion.
•    Spinal fusion: A surgical procedure in which two or more vertebrae are permanently joined into one solid bone with no space between them.
•    Osteotomies: A surgical procedure in which a portion of the vertebral body is removed to help restore the normal alignment of the spine. The procedure is utilized to reduce the amount of kyphosis or increase lordosis.

 

The normal spine viewed from the side forms a gentle "S" shape. When viewed from the back, the normal spine appears straight. The naturally occurring soft curves of the spine are designed to distribute mechanical stress in the body when at rest and during movement. When the curvature is even slightly abnormal, a person may experience occasional mild or annoying discomfort. If the curve is severely abnormal, the pain is usually severe and accompanied by disability. Scoliosis occurs in both children, where it is generally idiopathic, and adults, where it is often acquired.

In 2013, there were nearly 2 million healthcare visits with a diagnosis of scoliosis, the majority of which 1.3 million were to a physician’s office. However, 166,600 hospital discharges had a scoliosis diagnosis. The number of  hospital discharges with a scoliosis diagnosis has remained relatively steady for five years (2010 thru 2014) and represents approximately 56 persons in every 100,000 US population. Females accounted for three out of four (73%) of healthcare visits with a scoliosis diagnosis. (Reference Table 2B.2.0 PDF [326] CSV [327] and Table 2B.2.1 PDF [328] CSV [329])

Recent emphasis has been placed on sagittal plane balance and restoring normal sagittal alignment with regards to the three dimensional deformity of adult spinal deformity (ASD), and is a primary condition leading to the high prevalence (68%) of persons age 60 and over with adult spinal deformity.1^,2 The impact of sagittal plane alignment on the treatment of spinal disorders is of critical importance. A failure to recognize malalignment in this plane can have significant consequences for the patient not only for pain and deformity, but also social interaction due to deficient forward gaze. A good understanding of the principles of sagittal balance is vital to achieve optimum outcomes when treating spinal disorders. Even when addressing problems in the coronal plane (front from back), an awareness of sagittal balance is necessary to avoid future complications.3

Sagittal plane deformity presents as an exaggeration or deficiency of normal lumbar lordosis (inward curving of the lumbar spine just above the buttocks) or kyphosis (exaggerated curvature of the upper (thoracic) spine). There are variations on the degree of normal curvature, still this shape allows equal distribution of forces across the spinal column. It is the disruption of this equilibrium by pathological processes or, as in most cases, ageing that results in deformity. This leads to adaptive changes in the pelvis and lower limbs. The effects of limb alignment on spinal posture are well documented. Changes in pelvic posture also affect spinal alignment.3

 

 A lordosis deformity is usually iatrogenic (illness or condition caused by medication or treatment), and often follows lumbar fusion, thoracolumbar fusion, and, in some cases, lumbar decompressive procedures. Nonsurgical causes include ankylosing spondylitis, degenerative changes, or adult presentation of adolescent idiopathic scoliosis. The deformity may lead to neurogenic radicular symptoms secondary to stenosis, paraspinal muscular fatigue, and low back pain. Nonoperative treatment options fail for most patients. Surgical interventions are aimed at restoring lumbar lordosis, which is typically accomplished with revision decompression, fusion, and various osteotomies.4

Kyphosis is often secondary to inflammatory, degenerative, or post- traumatic disorders, and can be caused by poor posture, slouching, osteoporosis, birth defects, or disease. They may also be secondary to infection or tumors. There is usually pain and functional disability along with concerns about self-image and social interaction due to inability to maintain a horizontal gaze. The resultant pelvic and lower limb posture is an attempt to restore normal alignment. Addressing this complex problem requires detailed expertise and awareness of the potential pitfalls surrounding its treatment.1

Increasingly positive sagittal imbalance has been shown to correlate with poor functional outcome and poor self-image along with poor psychological function. Restoring normal spinopelvic alignment is paramount to the treatment of complex spinal deformity with sagittal imbalance. Understanding of whole spinal alignment and dynamics of spinopelvic alignment is essential to restore sagittal balance while minimizing the risk of developing sagittal decompensation after surgical intervention.1^,3

Management of Sagittal Deformity

The goal of sagittal deformity management is to maintain the body in an energy-efficient, ergonomically favorable erect position. The larger the deviation from a balanced alignment, the more energy an individual uses to stand upright without external suport. Patients with symptomatic sagittal plane deformity often present with a sagittal balance at the periphery of this balanced alignment, leading to an increased effort of accessory musculature to maintain the head over the pelvis. This leads to fatigue and pain, especially with prolonged activity. As sagittal imbalance progresses, different compensatory mechanisms such as the pelvic retroversion, hip extension, and knee flexion are used in order to restore and maintain sagittal balance. Once a spinal deformity surpasses these compensatory mechanisms surgical intervention is often requested.5

Operative management of sagittal deformity in the adult encompasses a spectrum of procedures with fusion the most common. In 2013, a query of the Healthcare Costs and Utilization Project (HCUP) Nationwide Inpatient Survey (NIS) resulted in approximately 190,500 hospitalizations associated with a discharge diagnosis of sagittal deformity. The largest share (76%), or 144,600 patients, were diagnosed with spondylolisthesis. Hospitalization with a sagittal deformity diagnosis was higher among the elderly, accounting for more than one-half (54%) among all ages for those 65 and older. Females accounted for 69% of all sagittal deformity hospitalizations. Race/ethnicity and region in the US did not show significant differences. (Reference Table 2B.2.1 PDF [328] CSV [329], Table 2B.2.2 PDF [341] CSV [342], Table 2B.2.3 PDF [359] CSV [360], Table 2B.2.4 PDF [361] CSV [362])

In 2013, more than nearly three-fourths (72.3%) of patients with a diagnosis of sagittal deformity had a surgical procedure. A diagnosis of spondylolisthesis had the highest rate (84.6%) of surgical procedure. The most common procedure performed on sagittal deformity patients was spinal fusion, with 67.4%, having this procedure. More than one-half (56%) had fusion of less than four levels. Sex of the patient was not a factor in having a procedure, but persons age 45 to 64 were most likely to have a procedure. (Reference Table 2B.5.0.1 PDF [363] CSV [364], Table 2B.5.0.2 PDF [365] CSV [366], Table 2B.5.1 PDF [367] CSV [368], Table 2B.5.2 PDF [345] CSV [346])

Sagittal balance is an independent predictor of clinical outcomes in spinal care. Surgical treatment is challenging and jeopardized by frequent complications. Guidelines for surgical treatment are currently not based on a classification of the disease. A comprehensive classification of sagittal balance based on regional deformities and compensatory mechanisms combined in deformity patterns is proposed. Though the sagittal shape of the spine can change due to degeneration or trauma, correlations between sagittal shape parameters and pelvic incidence (PI) have been described. PI is not changed by degeneration, thus representing a permanent source of information on the original sagittal shape of the spine.6

Burden of Sagittal Deformity

The national mean cost of a hospitalization, including surgical treatment, for patients with a primary diagnosis of sagittal imbalance was $94,500 in 2013 for an average hospital stay of 4.3 days. The HCUP NIS database does not provide hospitalization costs associated with secondary discharge diagnoses, and does not include fees to doctors, tests, and other typical charges associated with hospitalization. Therefore, the most conservative estimate of only hospital charges for adult sagittal imbalance in 2013 was an estimated $18.0 billion (166,600 hospitalizations). Charges are not necessarily actual costs paid. Mean charges for sagittal imbalance diagnosed patients are significantly higher than for all hospital discharge patients. (Reference Table 2B.3.2 PDF [349] CSV [350])

In 2013, slightly more one-half (56%) of patients with a sagittal imbalance diagnosis were discharged to home, compared to 70% of patients with any diagnosis. Patients with a sagittal imbalance diagnosis are more likely to be transferred to a skilled nursing or intermediate care facility (long-term care) than are patients with all other diagnoses. This is particularly true for the elderly population, with 36% of persons age 65 and older with a sagittal imbalance diagnosis moving to a long-term care facility. (Reference Table 2B.4.2 PDF [355] CSV [356])

The real cost of the management of adult sagittal imbalance to our healthcare system is significant, and the value of care measured by change in health status remains incompletely defined for both nonsurgical and surgical care.

• 1. a. b. c. Makhni MC, Shillingford JN, Laratta JL, et al. Restoration of Sagittal Balance in Spinal Deformity Surgery. J Korean Neurosurg Soc 2018;61(2):167–179. doi:10.3340/jkns.2017.0404.013.
• 2. Schwab F, Dubey A, Gamez L, et al. Adult scoliosis: prevalence, SF-36, and nutritional parameters in an elderly volunteer population. Spine (Phila Pa 1976) 2005;30:1082–1085.
• 3. a. b. c. Roussouly P, Nnadi C. Sagittal plane deformity: an overview of interpretation and management. Eur Spine J 2010:19(11);1824-1836.
• 4. Moshirfar A, Rand FF, Kebaish KM. Fixed sagittal plane deformity: causes, prevention, and treatment options. Seminars in Spine Surgery 2011:23(2);135-141.
• 5. Cavanilles-Walker JM, Ballestero C, Iborra M, Ubierna MT, Tomasi SO. Adult Spinal Deformity: Sagittal Imbalance. International Journal of Orthopaedics 2014:1(3).
• 6. Lamartina C, Berjano. Classification of sagittal imbalance based on spinal alignment ad compensatory mechanisms. European Spine Journal 2014:23(6):1177-1189.

Spinal deformity can be caused by congenital conditions and due to aging wear and tear on the back. Medical conditions and poor bone quality may also contribute to spinal deformity, however, in many cases the cause remains unknown.

Several conditions known to contribute to spinal deformity were examined as cross diagnoses with spinal deformity at the time of a healthcare visit. The most frequent diagnosis with one in ten (9.3%) hospital discharges and a scoliosis diagnosis was congenital spinal disorders. Four other conditions – trauma/spinal fractures, spinal infections, spondylopathies, and complications of surgery – were found in less than 2% of scoliosis and between 2% and 4% of sagittal imbalance hospital discharge diagnoses. Looking at all healthcare resources, the cross-diagnosis of spinal deformity and a contributing cause dropped to 0.3% among scoliosis discharges and 0.2% among sagittal imbalance visits. (Reference Table 2B.6.0 PDF [385] CSV [386])

Several studies have examined the relationship between spinal deformity and contributing causes, but until identification of multiple conditions is made, no clear relationship can be established.

The burden of spinal deformity includes healthcare costs, pain management, therapy, alternative care, and lost workdays due to pain. The total cost of spinal deformity is difficult to determine because hospital charges are the only expenditures available in the databases. In addition, not all persons suffering from spinal deformity seek medical care.

In 2013, charges for 357,000 hospital discharges for spinal deformity were $29.5 billion. Spinal deformity charges accounted for 2.1% of all hospital charges in 2013, but only 1% of hospital discharges. (Reference Table 2B.3.1 PDF [389] CSV [390])

In addition to direct and indirect costs, persons afflicted with spinal deformity experience a reduced quality of life, which may include major constraints on mobility and activity for those with the most serious conditions.

While technical outcomes of surgery are well known and show obvious benefits for those with significant deformity, long-term health related outcomes have yet to be precisely documented. The lack of quality, long-term studies of sufficient size hampers our understanding of the mortality and morbidity rates for patients with congenital and idiopathic scoliosis, with and without treatment. Fifty years of follow-up studies of children and adolescents with untreated scoliosis have shown conflicting results, with some studies indicating a higher risk of mortality and respiratory compromise.1^,2

Another study shows compromise only in patients with early reduced lung function and a large curvature.3  Yet another study has shown no differences in untreated childhood scoliosis and a control group.4 Several articles from the 1960s and one recent article report that low back pain does not occur more frequently in untreated scoliosis patients than in the general population4^,5^,6 unless the curvature is greater than 40°.7^,8 It has also been shown that persons treated with surgery rather than bracing for adolescent idiopathic scoliosis have less pain at 10- to 20-year follow-up, although function remains similar.9^,10 The cosmetic/self-image aspect of scoliosis is obvious and important, and often a major factor affecting the lives of individuals with this condition.

• 1. Goldberg CJ, Gillic I, Connaughton O, et al. Respiratory function and cosmesis at maturity in infantile-onset scoliosis. Spine 2003;28:2397-2406.
• 2. Pehrsson K, Larsson S, Oden A, Nachemson A. Long-term follow-up of patients with untreated scoliosis: A study of mortality, causes of death, and symptoms. Spine 1992;17:1091-1096.
• 3. Pehrsson K, Bake B, Larsson S, Nachemson A. Lung function in adult idiopathic scoliosis: A 20-year follow- up. Thorax 1991;46:474-478.
• 4. a. b. Weinstein SL, Dolan LA, Spratt KF, et al. Health and function of patients with untreated idiopathic scoliosis: A 50-year natural history study. JAMA 2003;289:559-567.
• 5. Nachemson A. A long-term follow-up study of non-treated scoliosis. Acta Orthop Scand 1968;39:466-476.
• 6. Nilsonne U, Lundgren KD. Long-term prognosis in idiopathic scoliosis. Acta Orthop Scand 1968;39:456-465.
• 7. Kostuik JP, Bentivoglio J. The incidence of low-back pain in adult scoliosis. Spine 1981;6:268-273.
• 8. Haefeli M, Elfering A, Kilian R, et al. Nonoperative treatment for adolescent idiopathic scoliosis: a 10- to 60-year follow-up with special reference to health-related quality of life. Spine 2006;31:355-366.
• 9. Andersen MO, Christensen SB, Thomsen K. Outcome at 10 years treatment for adolescent idiopathic scoliosis. Spine 2006;31:350-354.
• 10. Danielsson AJ, Romberg K, Nachemson AL. Spinal range of motion, muscle endurance, and back pain and function at least 20 years after fusion or brace treatment for adolescent idiopathic scoliosis: A case-control study. Spine 2006;31:275-283.

Scoliosis in the adult has an impact that is similar to other common medical conditions including osteoarthritis, coronary artery disease, and chronic obstructive pulmonary disease. Overall, the burden of scoliosis on health-related quality of life is severe relative to other common medical conditions. With the aging demographic profile of the US, the burden of adult scoliosis is increasing and has a significant impact on the health of our population, and on the cost of care for spinal disorders.

Likewise, vertebral compression fractures, which may contribute to adult degenerative scoliosis, are also a growing concern for the aging population, particularly when associated with kyphosis and/or disabling pain.

With the sagittal profile of the spine, conventional thinking has been to categorize it into different segments based on the anatomical differentiation of the vertebrae. This delineation does not take into account the true surface contour of the spine. The disadvantage of this overly simplistic categorization is that when attempting to restore what is perceived as a ‘normal thoracolumbar spine,’ a ‘one size fits all’ approach is used.1

Increased understanding of sagittal plane deformity will lead to earlier identification. As the life expectancy of the population increases along with the patients desire to lead more active lives well into advanced years, so will the demand for appropriate expertise and skill in dealing with this complex problem. Spinal osteotomies remain complicated procedures. This treatment strategy must be the subject of specific training and must be practiced by specialist surgeons for the best outcomes.1

• 1. a. b. Makhni MC, Shillingford JN, Laratta JL, et al. Restoration of Sagittal Balance in Spinal Deformity Surgery. J Korean Neurosurg Soc 2018;61(2):167–179. doi:10.3340/jkns.2017.0404.013.

Curvature of Spine:
Idiopathic Scoliosis: 737.30-737.32
Acquired Kyphosis and Lordosis: 737.0, 737.10, 737.12, 737.19, 737.20-737.29, 737.34, 737.39
Secondary Scoliosis, Kyphosis, and Lordosis: 737.11, 737.33, 737.40-737.43, 737.8, 737.9
Spondylolisthesis: 737.40, 756.12
Adolescent Postural Kyphosis: 737.00
Kyphosis: 737.10-737.19, 737.41
Lordosis: 737.20-737.29, 737.42
Scoliosis: 737.30-737.39, 737.40, 737.43, 737.8, 737.9

Trauma: Spinal Fractures Contributing to Deformity:
Vertebral Compression Fractures: 805.00-805.08, 805.2, 805.4, 805.6, 805.8
Traumatic Fractures: 805.10-805.18, 805.3, 805.5, 805.7, 805.9, 806.00-806.09, 806.10-806.19, 806.20-806.29,806.30-806.39, 806.4, 806.5, 806.60-806.02, 806.69, 806.70-806.72, 806.79, 806.8, 806.9

Infection/Complications Codes:
Tuberculosis of Vertical Column: 015.00 to 015.06
Tuberculosis Unspecified: 015.90 to 015.96
Intracranial and Intraspinal Abscess (Epidural abscess): 324.1, 324.9
Acute Osteomyelitis: 730.00, 730.08, 730.09
Chronic Osteomyelitis: 730.10, 730.18, 730.19
Discitis: 722.90 to 722.93
Complications of Surgery: 996.2, 996.59, 996.63, 996.72
 
Spondylopathies:
Ankylosing Spondylitis: 720.00
Spinal Enthesopathy: 720.1
Sacroiliitis, not elsewhere classified: 720.2
Other Inflammatory Spondylopathies: 720.81, 820.89
Unspecified Inflammatory Spondylopathy: 720.9
Cervical Spondylosis with Myelopathy: 721.1
Thoracic or Lumbar Spondylosis with Myelopathy: 721.4
Spondylosis with Myelopathy, Thoracic Region: 721.41
Spondylosis with Myelopathy, Lumbar Region: 721.42
Intervertebral Disc Disorder with Myelopathy: 722.70 to 722.73
Spinal Stenosis in Cervical Region: 723.00
Cervicalgia: 723.1
Cervicocranial Syndrome: 723.2
Cervicobrachial Syndrome (diffuse): 723.3
Brachial Neuritis or Radiculitis NOS: 723.4
Torticollis, Unspecified: 723.5
Panniculitis Specified as Affecting Neck: 723.6
Ossification of Posterior Longitudinal Ligament in Cervical Region: 723.7

Spinal Deformity Procedures:
Decompression: 0309, 8050, 8051
Cervical Fusion: 8102, 8103
Thoracic/Dorsal or Dorsolumbar Fusion: 8104, 8105
Lumbar and Lumbosacral Fusion: 8106, 8107, 8108
Other Fusion: 8100, 8101
Cervical Refusion: 8132, 8133
Thoracic, Dorsal or Dorsolumbar Refusion: 8134, 8135
Lumbar and Lumbosacral Refusion: 8136, 8137, 8138
Other Refusion: 8130, 8131, 8139
Fusion/Refusion of Multiple Vertebrae: 8162, 8163, 8164
Instrumentation/Insertion of Spinal Device: 8451, 8452, 8459
Vertebraplasty: 8165
Kyphoplasty [Percutaneous Vertebral Augmentation]: 8166 Decompression: 0309
Diskectomy: 8050, 8051
Epidural injection: 8192, 8396, 8397

 

While AORC occurs in children, it is difficult to acquire population data on them, so most of the estimates presented in this report are for adults unless otherwise noted.

 In the general population, prevalence is better estimated by DDA than AORC. For the years 2013-2015, DDA affected an unadjusted average of 54.4 million adults, or 23 in 100 adults.1 Estimates show the typical distribution of higher prevalence among females and older adults, and lower prevalence among Hispanics and Asians. Absolute estimates show that most of these adults (59%, or 32.2 million) are of working age (younger than age 65).1 (Reference Table 3A.1.1 PDF [397] CSV [398])

 

Specific types of AORC  

Clinical data are required to provide some measure of validity for estimating the prevalence of specific types of arthritis because many people are not sure what type of arthritis they have. Data from the National Arthritis Data Workgroup provided 2005 national prevalence estimates for some of the ten specific types of arthritis used in later tables.2^,3 Respondents could have reported more than one type.

Osteoarthritis:  Osteoarthritis (OA) is the most common type of arthritis, characterized by progressive damage to cartilage and other joint tissues. Joint injury is a risk factor for OA, but most cases occur without a specific history of injury. Obesity is a risk factor for knee OA, and to a lesser extent for hip and hand OA. Clinical OA was estimated to affect 26.9 million in 20053 and over 30 million for 2008-2011.4 The joints most affected with radiographic OA and symptomatic OA were hands, knees, and hips.3  

Rheumatoid arthritis:  Rheumatoid arthritis (RA) is the prototypical inflammatory arthritis. It is a chronic autoimmune disease that causes pain, aching, stiffness, and swelling in multiple joints, especially the hands, in a symmetrical fashion. In 2005, RA was estimated to affect 1.3 million adults.2
 
Gout and other crystal arthropathies:  Gout is a recurrent inflammatory arthritis that occurs when excess uric acid collects in the body. Gout has been recognized for centuries and often affects the big toe. In 2005, an estimated 6.1 million adults reported having gout at some time, with 3.0 million affected in the past year.3 More recent studies of self-reported gout and hospitalizations show the prevalence of gout increasing in the last two decades.5^,6

Joint pain/effusion/other unspecified joint disorders: Joint pain can result from several causes, including inflammation, degeneration, crystal deposition, infection, and trauma. Joint pain is often accompanied by swelling and effusion. A joint effusion is the presence of increased intra-articular fluid within the synovial compartment of a joint. Determining the cause of joint pain is primary to treatment.

Spondylarthropathies:  Spondylarthropathies (or spondylarthritides) are a family of diseases that includes ankylosing spondylitis, reactive arthritis, psoriatic arthritis, enteropathic arthritis (associated with ulcerative colitis or Crohn’s disease), juvenile spondylarthritis, and undifferentiated spondylarthritis. In 2005, spondylarthropathies affected an estimated 639,000 to 2.4 million adults ages 25 and older.2

Fibromyalgia:  Fibromyalgia (FM) is a syndrome of widespread pain and tenderness. The diagnosis is difficult to make, so relevant prevalence data are hard to come by. In 2005, FM was estimated to affect around 5 million adults.3 A more recent estimate by the National Fibromyalgia Association puts the estimate at 10 million people in the US, with 75%-90% of the affected adult women. However, due to the difficulty in diagnosing fibromyalgia and the potential for including other causes of pain, this estimate should be used with caution.7  

Diffuse connective tissue diseases include the next four diseases.
Systemic lupus erythematosus:  Systemic lupus erythematosus (SLE) is the prototypical autoimmune disease in which the body’s immune system can attack many body systems, especially the skin, kidneys, and joints. In 2005, definite and suspected SLE was conservatively estimated to affect 322,000.2 Population-based registries have provided more recent estimates for various racial/ethnic groups.8^,9^,10

Systemic Sclerosis:  Systemic sclerosis (SSc), or scleroderma, is an autoimmune disease that primarily affects the skin, but can affect any organ system. In 2005, SSc affected an estimated 49,000 adults.2

Primary Sjögren’s Syndrome:  Primary Sjögren’s Syndrome (SS) is a syndrome of dry eyes, dry mouth, and arthritis. Secondary SS can occur in association with other rheumatologic diseases such as rheumatoid arthritis and lupus. Prevalence data are very limited. In 2005, an estimated 0.4 to 3.1 million adults had SS.2

Polymyalgia rheumatica and giant cell (temporal) arteritis: Polymyalgia rheumatica (PMR) is a syndrome of sudden aching and stiffness in older adults that responds to treatment with anti-inflammatory medications (e.g., corticosteroids). Giant cell arteritis (GCA), which often occurs with PMR, is a type of vasculitis that affects medium-size arteries and results in headache, vision loss, and other symptoms. In 2005, PMR was estimated to affect 711,000 adults;3 a more recent analysis from the same data source found that the incidence of PMR had increased slightly with mortality not unlike the general population,11 suggesting that prevalence may have increased slightly as well. In 2005, GCA was estimated to affect 228,000 adults.4  

Carpal tunnel syndrome: Carpal tunnel syndrome (CTS) occurs when the median nerve becomes compressed at the wrist and causes numbness, pain, or weakness in part of the hand. Thickened tendons and other rheumatic conditions are a common cause. General population prevalence has been reported between 1% and 5%.12

Soft tissue disorders (excluding back): These are a variety of problems of the tendons, bursa, muscle, ligaments, and fascia that cause pain and dysfunction. Prevalence of soft tissue disorders is difficult to determine due to the variety of conditions included.

Other specific rheumatic conditions: These are other conditions that the National Arthritis Data Workgrop considered to be rheumatic conditions.

Juvenile arthritis:  Arthritis and other rheumatic conditions are relatively uncommon in children, although they can be particularly severe when they do occur. One estimate using significant pediatric arthritis and other rheumatologic conditions (SPARC) codes put the average annual prevalence at 103,000 children for the years 2001-2004 for the combined codes for rheumatoid arthritis and other inflammatory polyarthropathies, allergic purpura, arthropathy associated with infections, other and unspecified arthropathies, polyarteritis nodosa and allied conditions, and rarer inflammatory conditions.The prevalence for all SPARC codes, including synovitis and myalgia, was 294,000.13 A more in-depth discussion can be found in the Juvenile Arthritis (click HERE [401] to open new page) section later in this document.

• 1. a. b. Barbour KE, Helmick CG, Boring M, Brady TJ.  Prevalence of doctor-diagnosed arthritis and arthritis-attributable activity limitation—United States, 2013-2015.  MMWR 2017;66(9):246-253.
• 2. a. b. c. d. e. f. Helmick CG, Felson DT, Lawrence RC, et al., for the National Arthritis Data Workgroup. Estimates of the prevalence of arthritis and other rheumatic conditions in the United States:  Part I. Arthritis Rheum 2008;58(1):15-25.
• 3. a. b. c. d. e. f. Lawrence RC, Felson DT, Helmick CG, et al., for the National Arthritis Data Workgroup. Estimates of the prevalence of arthritis and other rheumatic conditions in the United States:  Part II. Arthritis Rheum 2008;58(1):26-35.
• 4. a. b. Cisternas MG, Murphy L, Sacks J, et al.,  Alternative methods for defining osteoarthritis and the impact on estimating prevalence in a US population-based survey. Arthritis Care Res 2016;68(5):574-580.
• 5. Lim SY, Lu N, Oza A, et al., Trends in gout and rheumatoid arthritis hospitalizations in the United States, 1993-2011. JAMA. 2016:315(21);2345-2346.
• 6. Roddy E, Choi H. Epidemiology of gout. Rheum Dis Clin North Am. 2014:40(2);155-175. Doi: 10.1016/j.rdc.2014.01.001.
• 7. National Fibromyalgia Association.  http://www.fmaware.org/about-fibromyalgia/prevalence [402]/ Accessed April 18, 2017.
• 8. Lim SS, Bayakly AR, Helmick CG, et al., The incidence and prevalence of systemic lupus erythematosus, 2002-2004: The Georgia Lupus Registry. Arthritis Rheum 2014;66(2):357-368.  DOI 10.1002/art.38329.
• 9. Somers EC, Marder W, Cagnoli P, et al., Population-based incidence and prevalence of systemic lupus erythematosus: The Michigan Lupus Epidemiology & Surveillance Program. Arthritis Rheum 2014;66(2):369-378.  DOI 10.1002/art.38328.
• 10. Ferucci ED, Johnston JM, Gaddy JR, et al., Prevalence and incidence of systemic lupus erythematosus in a population-based registry of American Indian and Alaska Native people, 2007-2009. Arthritis Rheum 2014;66(9):2494-2502. DOI 10.1002/art.38720.
• 11. Raheel S, Shbeeb I, Crowson CS, Matteson EL.  Epidemiology of polymyalgia rheumatica 2000-2014 and examination of incidence and survival trends over 45 years: A population-based study.  Arthritis Care Res (Hoboken). 2016 Oct 21. doi: 10.1002/acr.23132. [Epub ahead of print] PMID: 27768840.
• 12. Dale AM, Harris-Adamson C, Rempel D. et al. Prevalence and incidence of carpal tunnel syndrome in US working populations: Pooled analysis of six prospective studies. Scand J Work Environ Health. 2013 Sep 1; 39(5): 495–505. doi:  10.5271/sjweh.3351.
• 13. Sacks JJ, Helmick CG, Luo Y-H, et al., Prevalence of and annual ambulatory healthcare visits for pediatric arthritis and other rheumatologic conditions in the US in 2001–2004. Arthritis Rheum (Arthritis Care Res) 2007;57(8):1439-1445.

AORC prevalence continues to increase in the aging US population, with related increases in healthcare utilization. The increase in total ambulatory care visits, together with the increasing number of joint replacements and related hospitalizations, both impact healthcare utilization. The AORC case definition is more appropriate to use within the healthcare system, which is based on health condition codes. However, the AORC case definition will miss adults with mild arthritis that is not mentioned at the visit, or for whom arthritis may not be a priority when multiple conditions are present. For estimates in the following discussions, AORC condition codes, found in ICD-9-CM Codes [403] section are used.

In 2013, AORC-related diagnoses were listed in 105.7 million healthcare visits and represented more than 10% of all healthcare visits. Hospitalizations accounted for 6% of AORC visits, while ambulatory care accounted for 94% (77% physician office, 6% outpatient, and 11% emergency department). (Reference Table 3A.3.0.1 PDF [404] CSV [405])

When looking at how the ten subtypes of AORC affect the four types of healthcare utilization below, remember that the estimates are not mutually exclusive due to the potential for multiple diagnoses in a single visit. (Reference Table 3A.3.0.2 PDF [408] CSV [409]; Table 3A3.0.3 PDF [410] CSV [411]; Table 3A.3.0.4 PDF [412] CSV [413]; and Table 3A.3.0.5 PDF [414] CSV [415])

Hospitalizations

The Healthcare Cost and Utility Project (HCUP) 2013 Nationwide Inpatient Sample (NIS) estimates that 6.4 million hospitalizations were associated with a diagnosis of AORC, or 21.4% of all hospitalizations that year. AORC was the presenting or first-listed diagnosis for only 1% of all hospitalizations, suggesting the role of AORC is more of an important comorbidity or contributor to other conditions which are the reason for the hospitalization. Nearly one-half of the 6.4 million AORC hospitalizations were associated with osteoarthritis (46%), while joint pain/effusion/other unspecified joint disorders, gout, and soft tissue disorders were each listed in more than 10% of hospitalizations. Multiple AORC diagnoses are coded in 17% of hospitalizations with an AORC diagnosis. Osteosteoarthritisrthritis is the least likely to have another AORC diagnosis, while carpal tunnel syndrome is most likely to include multiple diagnoses. (Reference Table 3A.3.0.1 PDF [404] CSV [405] and Table 3A.3.0.2 PDF [408] CSV [409])

AORC-associated hospitalizations by sex, race/ethnicity, and geographic region resembled those for all 2013 hospitalizations; however, they differed in age, skewing toward the 65 & older age group (59.1% vs. 41.7%). (Reference Table 3A.3.1.0.1 PDF [416] CSV [417]; Table 3A.3.1.0.2 PDF [418] CSV [419]; Table 3A.3.1.0.3 PDF [420] CSV [421]; Table 3A.3.1.0.4 PDF [422] CSV [423])  

Hospitalizations for specific types of AORC differed by demographic variables. Women comprised 59% of total AORC hospitalizations, but much more for hospitalizations with rheumatoid arthritis (75%), fibromyalgia (89%), and diffuse connective tissue disease (87%).  Men comprised 41% of total AORC hospitalizations, but much more for hospitalizations with gout (67%) and soft tissue disorders (52%). (Reference Table 3A.3.1.0.1 PDF [416] CSV [417])

Those younger than age 65 comprised 41% of total AORC hospitalizations, but much more for hospitalizations with fibromyalgia (68%), diffuse connective tissues disease (67%), and carpal tunnel syndrome (61%). (Reference Table 3A.3.1.0.2 PDF [418] CSV [419])

 Non-Hispanic blacks comprised 12% of total AORC hospitalizations, but much more for hospitalizations with gout (18%) and diffuse connective tissue disease (24%). (Reference Table 3A.3.1.0.3 PDF [420] CSV [421])  

Hospitalizations for specific types of AORC did not differ much by geographic region. (Reference Table 3A.3.1.0.4 PDF [422] CSV [423])

Length of Stay (LOS)

The mean LOS for AORC-associated hospitalizations in 2013 was slightly greater than that for all hospitalizations (4.9 vs 4.7 days); differences by demographic groups were greater for AORC hospitalizations (than all hospitalizations) for women (4.8 vs 4.4 days), those 18 to 44 years (5.0 vs. 3.6 days), non-Hispanic blacks (5.6 vs 4.4 days), Hispanics (5.3 vs. 3.6 days), and those in the western geographic region (4.8 vs. 4.3 days). Among the 10 specific types of AORC the mean LOS was strikingly longer for those with soft tissue disorders and other specified rheumatic conditions both overall (6.5 and 6.5 vs. 4.9 days) and by every demographic subgroup. (Reference Table 3A.3.1.1.1 PDF [428] CSV [429]; Table 3A.3.1.1.2 PDF [430] CSV [431]; Table 3A.3.1.1.3 PDF [432] CSV [433]; Table 3A.3.1.1.4 PDF [434] CSV [435]) 

 

Hospital Charges

Hospital charges are based on individual record discharges. The fees included may vary from patient to patient, but generally include hospital room, supplies, medications, laboratory fees, and care staff, such as nurses. They generally do not include professional fees (doctors) and non-covered charges. Emergency charges incurred prior to admission to the hospital may be included in total charges. It is important to note that charges are not necessarily the actual amount paid by Medicare, insurers, or patients. However, they are the only medical expenditure cost available in the major databases based on ICD-9-CM diagnostic codes and provide an overall picture for comparison purposes. Because multiple diagnoses are often made with an admission, actual charges related to a specific AORC may be much smaller. This is true of cost estimates provided in the Economic Burden [438] section also.

Mean hospital charges for AORC-associated hospitalizations generally paralleled, but were consistently higher than charges for all hospitalizations, both overall (+$5,900) and for all demographic subgroups. Higher mean charges among demographic subgroups were most striking for women (+$8,200), persons 18-44 years (+$18,800), non-Hispanic whites (+$9,900), non-Hispanic blacks (+$10,900), Hispanics (+$33,700), other non-Hispanics (+$10,700), and those in the South (+$9,500) and West (+$16,100).

Total charges for AORC-associated hospitalizations were $310.9 billion in 2013, comprising 24% of all hospital charges for the year. This percentage was relatively consistent for all sex and age groups except those 18 to 44 years, where it was only 11%. Among racial/ethnic groups, AORC total charges were 19% for non-Hispanic others, while they were 30% among non-Hispanic whites. AORC-associated hospitalization total charges were 29% of all hospitalizations in the Midwest in 2013.

Among the 10 AORC subgroups, hospitalizations with osteoarthritis accounted for $138.4 billion, or 45% of total charges for AORC-associated hospitalizations, while hospitalizations with joint pain/effusion/other, gout, and soft tissue disorders accounted for 16%, 13%, and 13% respectively). (Reference Table 3A.3.1.1.1 PDF [428] CSV [429]; Table 3A.3.1.1.2 PDF [430] CSV [431]; Table 3A.3.1.1.3 PDF [432] CSV [433]; Table 3A.3.1.1.4 PDF [434] CSV [435])

 

Discharge Status

Discharge from the hospital to long-term care, which includes skilled nursing facilities, intermediate care, and other similar facilities, or to home health care occurred more frequently among AORC-associated hospitalizations than among all hospitalizations (44% vs 29%). This was true regardless of sex, age, race/ethnicity, or region of residence. By demographic characteristics, the highest proportion of discharge to long-term care or home health care was found among females (48%), age 65 and over (55%), and residents of the Northeast region (52%).

Among the 10 AORC subgroups there were no striking differences in discharge to long-term care or home health care compared with all AORC hospitalizations. Discharge to home was more frequent, and resembled all hospitalizations (66%), among those with carpal tunnel syndrome (68%), fibromyalgia (67%), diffuse connective tissue disease (64%), and spondylarthropathies (59%). (Reference Table 3A.3.1.3.1 PDF [441] CSV [442]; Table 3A.3.1.3.2 PDF [443] CSV [444]; Table 3A.3.1.3.3 PDF [445] CSV [446];Table 3A.3.1.3.4 PDF [447] CSV [448])

 

Ambulatory Care Visits

From the 2013 surveys on ambulatory care, there were an estimated 99.3 million ambulatory care visits associated with a diagnosis of AORC, more than 10% of all ambulatory care visits that year, for a rate of 40.1/100 adults in the general population. An AORC-related condition was listed as the presenting (first) diagnosis for between 2.8% and 5.4% of all ambulatory care visits, depending on the healthcare site visited. Physicians’ offices accounted for 82% of all ambulatory AORC visits, vastly exceeding emergency department (12%) or outpatient (7%) sites. (see Table 3A.3.0.1 PDF [404] CSV [405]) As with hospital discharges, multiple AORC diagnoses were given in 15% to 20% of patient ambulatory visits. (Reference Table 3A.3.0.3 PDF [410] CSV [411]; Table 3A.3.0.4 PDF [412] CSV [413]; and Table 3A.3.0.5 PDF [414] CSV [415])

In 2013, AORC-associated ambulatory care visits resembled all 2013 ambulatory care visits by sex, race/ethnicity, and geographic region; they differed in age, being lower in the 18 to 44-year age group (21% vs. 32%) and higher in the 45 to 64-year age group (44% vs. 36%) and the 65 and older age group (34% vs. 32%).  (Reference Table 3A.3.2.0.1 PDF [451] CSV [452]; Reference Table 3A.3.2.0.2 PDF [453] CSV [454]; Table 3A.3.2.0.3 PDF [455] CSV [456]; Table 3A.3.2.0.4 PDF [457] CSV [458]) (Note: Detailed data by type of ambulatory setting shown in Tables 3A.3.2.1.x, 3A.3.2.2.x(.1 to .4), and 3A.3.2.3.x, and can be accessed from the “Tables” tab in the upper right corner.)

Among the 10 AORC subgroups, 2 in 5 of the 99.3 million total ambulatory visits (41%) were associated with joint pain/effusion/other unspecified joint disorders or “other specified rheumatic conditions”; osteosteoarthritisrthritis and soft tissue disorders were the most common specific condition (~20% each). (Reference Table 3A.3.2.0.1 PDF [451] CSV [452])

AORC-associated ambulatory care visits for specific types of AORC differed by demographic variables.  Women comprised 62% of all AORC-associated ambulatory care visits; their proportion was much higher for fibromyalgia (79%) and diffuse connective tissue disease (90%), but much lower for gout and other crystal arthropathies (27%). Men comprised 39% of all AORC-associated ambulatory care visits; their proportion was much higher for gout (72%). (Reference Table 3A3.2.0.1 PDF [451] CSV [452])

The 18 to 44-year old group comprised 21% of all AORC-associated ambulatory care visits; their proportion was a bit higher for diffuse connective tissue disease (31%), fibromyalgia (27%), and carpal tunnel syndrome (26%). Those aged 45 to 64 years comprised 44% of all AORC –associated ambulatory care visits; this proportion was similar for most specific types of AORC. Those aged 65 and older comprised 34% of all AORC-associated ambulatory care visits; their proportion was much higher for osteoarthritis (51%) and gout (50%), and much lower for fibromyalgia (20%). (Reference Table 3A.3.2.0.2 PDF [453] CSV [454])

Non-Hispanic whites (65% of the US population) comprised 73% of all AORC-associated ambulatory care visits, but only 59% of those for gout. Comparisons for other race/ethnic groups, as well as geographic regions were difficult to determine due to small sample sizes and unreliable data. (Reference Table 3A.3.2.0.3 PDF [410] CSV [411]; Table 3A.3.0.4 PDF [412] CSV [413])

 

Physician Office Visits

Some 81 million AORC-related ambulatory care visits were physician office visits (PHYS); these accounted for 82% of all ambulatory care visits.  An AORC-related condition was listed as the presenting (first) diagnosis for 5.4% of all PHYS visits. (Reference Table 3A.3.0.1 PDF [404] CSV [405])

Overall, 2013 AORC-related PHYS visits resembled those for all 2013 PHYS visits by sex, race/ethnicity, and geographic region; they differed in age, being lower in the 18 to 44-year age group (20% vs. 29%), higher in the 45 to 64-year age group (46% vs. 37%), and similar in the 65 and older age group (34%).

Among the 10 AORC subgroups, nearly 2 in 5 of the 81 million AORC-related PHYS visits (37%) were associated with joint pain/effusion/other unspecified joint disorders; osteoarthritis and soft tissue disorders were about 21% each. (Reference Table 3A.3.2.1.1 PDF [467] CSV [468])

AORC-related PHYS visits for specific types of AORC differed by demographic variables.  Women comprised 61% of all AORC-associated PHYS visits; their proportion was much higher for rheumatoid arthritis (77%) and diffuse connective tissue disease (90%).  Men comprised 39% of all AORC-associated PHYS visits; their proportion was much higher for gout (71%). (Reference Table 3A.3.2.1.1 PDF [467] CSV [468])

Persons aged 18 to 44 comprised 20% of all AORC-associated PHYS visits; their proportion was higher for diffuse connective tissue disease (29%) and soft tissue disorders (26%), while lower for osteoarthritis (7%) and rheumatoid arthritis (13%). Those aged 45 to 64 comprised 46% of all AORC–associated PHYS visits; their proportion pf PHYS visits was higher for fibromyalgia (55%) and carpal tunnel syndrome (50%).  Those aged 65 and older comprised 34% of all AORC-associated PHYS visits; their proportion was much higher for osteoarthritis (51%) (Reference Table 3A.3.2.1.2 PDF [469] CSV [470]).

Non-Hispanic whites comprised 74% of all AORC-associated PHYS visits; their proportion was higher for rheumatoid arthritis (80%), spondylarthropathies (79%), and lower for gout (65%) and carpal tunnel syndrome (68%). Comparisons for other race/ethnic groups were difficult to determine. (Reference Table 3A.3.2.1.3 PDF [471] CSV [472])  

There was little difference by geographic region. (Reference Table 3A.3.2.1.4 PDF [473] CSV [474]).

 

Outpatient Clinic Visits

Some 6.5 million AORC-related ambulatory care visits were to outpatient (OP) clinics; these accounted for 7% of all ambulatory care visits. An AORC-related condition was listed as the presenting (first) diagnosis for 4.4% of all OP visits. (Reference Table 3A.3.0.1 PDF CSV)2013 AORC-related OP visits resembled those for all 2013 OP visits by sex, race/ethnicity, and geographic region; they differed in age, being lower in the 18 to 44-year age group (25% vs. 38%), and higher in the 45 to 64-year age group (49% vs. 39%) and the 65 and older age group (27% vs. 23%) (Reference Table 3A.3.2.2.1 PDF [475] CSV [476]).

Among the 10 AORC subgroups, more than 2 in 3 of the 6.5 million AORC-related OP visits (69%) were associated with joint pain/effusion/other unspecified joint disorders and osteoarthritis; soft tissue disorders and rheumatoid arthritis accounted for about 12% each. (Reference Table 3A.3.2.2.2 PDF [477] CSV [478])

AORC-related OP visits for specific types of AORC differed by demographic variables. Women comprised 69% of all AORC-associated OP visits; their proportion was much higher for rheumatoid arthritis (83%) and diffuse connective tissue disease (88%). Men comprised 31% of all AORC-associated OP visits; their proportion was much higher for gout (81%) and osteoarthritis (67%) (Reference Table 3A.3.2.2.1 PDF [475] CSV [476]).

Persons aged 18 to 44 comprised 25% of all AORC-associated OP visits; their proportion was higher for diffuse connective tissue disease (38%) and carpal tunnel syndrome (38%). Those aged 45 to 64 comprised 49% of all AORC-associated OP visits; their proportion was higher for rheumatoid arthritis (63%). Those aged 65 and older comprised 27% of all AORC-associated OP visits; their proportion was much higher for osteoarthritis (40%) (Reference Table 3A.3.2.2.2 PDF [477] CSV [478]).

Non-Hispanic whites comprised 58% of all AORC-associated OP visits; their proportion was higher for spondylarthropathies (71%) and fibromyalgia (70%). Comparisons for other race/ethnic groups were difficult to determine. (Reference Table 3A.3.2.2.3 PDF [479] CSV [480])

There was little difference by geographic region. (Reference Table 3A.3.2.2.4 PDF [481] CSV [482])

 

Emergency Department Visits 

Emergency department (ED) visits for AORC-related diagnoses, totaling 11.7 million, accounted for 12% of all ambulatory care visits in 2013 and 11% of all emergency department visits. An AORC-related condition was listed as the presenting (first) diagnosis for 2.8% of all ED care visits. (Reference Table 3A.3.0.1 PDF [404] CSV [405])

2013 AORC-related ED visits resembled those for all 2013 ED visits by sex and geographic area; they differed in age, being lower in the 18 to 44-year age group (29% vs. 49%) and higher in the 45 to 64-year age group (34% vs. 29%) and the 65 and older age group (37% vs. 23%). (Reference Table 3A.3.2.3.2 PDF [483] CSV [484])

Among the 10 AORC subgroups, 3 in 5 of the 11.7 million AORC-related ED visits were associated with joint pain/effusion/other unspecified joint disorders and osteoarthritis; soft tissue disorders and fibromyalgia accounted for 13% and 12%, respectively. (Reference Table 3A.3.0.1 PDF [404] CSV [405])

AORC-related ED visits for specific types of AORC differed by demographic variables. Women comprised 61% of all AORC-associated ED visits; their proportion was much higher for rheumatoid arthritis (77%), fibromyalgia (79%) and diffuse connective tissue disease (90%). Men comprised 39% of all AORC-associated ED visits; their proportion was much higher for gout (69%). (Reference Table 3A.3.2.3.1 PDF [485] CSV [486])

Persons aged 18 to 44 comprised 29% of all AORC-associated ED visits; their proportion was higher for diffuse connective tissue disease (40%), fibromyalgia (43%), and carpal tunnel syndrome (51%). Those aged 45 to 64 comprised 34% of all AORC-associated ED visits; this proportion was similar for most specific types of AORC. Those aged  65 and older comprised 37% of all AORC-associated ED visits; their proportion was much higher for osteoarthritis (66%), rheumatoid arthritis (49%), gout (56%), spondylarthropathies (50%), and other specified rheumatic conditions (49%). (Reference Table 3A.3.2.3.2 PDF [483] CSV [484])

Race/ethnicity was not a defined variable in the NEDS database. There was little difference by geographic region. (Reference Table 3A.3.2.3.4 PDF [487] CSV [488])

Disease burden can be measured in many ways. This is particularly important for AORC, which has a modest effect on conveniently measured outcomes like mortality, but a much larger impact on less conveniently measured outcomes important to functionality for most people. Such outcomes include effects on work, health-related quality of life, independence, and ability to keep doing valued life activities. Three of these burdens, along with adverse life style factors that are associated with arthritis, are addressed in the estimates below.

Bed Days and Lost Work Days

Bed Days

Bed days are defined as spending one-half or more days in bed due to injury or illness, excluding hospitalization. Data are averaged over three years for the NHIS to achieve larger, more powerful sample sizes. For the years 2013-2015, the proportion who had bed days among adults with arthritis was higher than that for adults with any medical condition (45% vs. 41%). The 24.6 million adults with doctor-diagnosed arthritis and any bed days, 10% of the adult population, had an annual average of nearly 25 days spent in bed in the previous 12 months. This is far higher than the annual average of 14.5 bed days for the 41% of adults with bed days for any medical condition. Multiplying the 24.6 million adults by the mean bed days for arthritis resulted in 607 million bed days overall, or 55% of the 1.1 trillion bed days among adults reporting any medical condition. (Reference Table 3A.4.1.1 PDF [489] CSV [490])

Among adults with arthritis, females had a higher proportion than males of bed days (48% vs 41%) and a slightly higher mean number of days (25.6 vs. 23.1 days).  Females with arthritis accounted for 65% of total bed days in 2013-2015.  (Reference Table 3A.4.1.1 PDF [489] CSV [490])

Bed days are reported by a higher proportion of younger than by older adults with arthritis. Adults with arthritis had a higher proportion with bed days than adults reporting any medical condition in each age group: persons aged 18 to 44 years (59% vs. 46%), aged 45 to 64 years (50% vs. 41%), and aged 65 and older (35% vs. 31%).  This was also true for the average number of bed days: 18 to 44 years (20.1 vs 9.3 days), 45 to 64 years (26.4 vs. 17.3 days), and 65 and older years (24.7 vs. 22.0 days). (Reference Table 3A.4.1.2 PDF [491] CSV [492])

Among racial/ethnic groups, those with arthritis had similar proportions reporting bed days (range 43%-47%) and a similar average number of bed days (range 21.4-25.6). (Reference Table 3A.4.1.3 PDF [493] CSV [494])

In the different geographic regions, those with arthritis had similar proportions with bed days (range 43%-47%) and a similar average number of bed days (range 22.4-27.2). (Reference Table 3A.4.1.4 PDF [495] CSV [496])

 

Lost Work Days

Persons in the workforce are defined as adults having worked at a job in the past 12 months. In the 2013-2015 NHIS sample, 81% of those age 18 to 44 held a job (56% of workforce), 74% of persons aged 45 to 64 years held a job (38% of workforce), and 20% of persons aged 65 and older were still working, comprising just under 6% of the workforce. Among the persons aged 65 and older, 83% were age 74 and younger. By sex, 73% of males reported being in the workforce, while 62% of females worked in the past 12 months. Males represented 52% of the workforce.

Lost work days for persons in the workforce are defined as absence from work due to illness or injury in the past 12 months, excluding maternity or family leave. For the years 2013-2015, the proportion of persons who had lost work days among adults with arthritis was lower than that for adults with any medical condition (23% vs. 30%).  Among adults with doctor-diagnosed arthritis, 12.6 million in the workforce reported an average of 14.3 work days lost in the past 12 months, nearly 5 days more than the 9.4 work days reported by adults with any medical condition. This resulted in 180.9 million total lost work days among adults with arthritis who are in the workforce, or 34% of the 533.2 million work days lost among adults reporting any medical condition.

Among adults with arthritis, females and males in the workforce had similar proportions with lost work days (23%-24%) and similar mean number of lost work days (14.2-14.4).  Females accounted for 57% of total arthritis-attributed lost work days per year in 2013-2013 due to the higher number of females with arthritis. (Reference Table 3A.4.1.1 PDF [489] CSV [490])
 
Compared with older adults, younger adults with arthritis or any medical condition had a higher proportion of lost workdays.  Adults with arthritis had a higher proportion of lost work days than adults reporting any medical condition for persons aged 18 to 44 years (47% vs. 42%), but proportions were similar for the older age groups. Although, overall, the proportion of persons with DDA reporting lost work days was slightly less than was reported for any medical condition, the average number of lost work days was higher among adults with arthritis than adults with any medical condition: 18 to 44 years (13.4 vs 8.2 days), 45 to 64 years (14.6 vs. 10.8 days), and 65 and older (15.3 vs. 12.6 days).  Adults aged 45 to 64 accounted for 62% of total arthritis-related lost work days even though they only comprised 38% of the workforce and 47% of those with any medical cause. (Reference Table 3A.4.1.2 PDF [491] CSV [492])

Activity Limitations

Activity limitations are included in the National Health Interview Survey in both the family database and the adult database, with slightly different response codes. Respondents are asked first if they need help performing a variety of activities of daily living (ADL), such as personal care, bathing, eating, getting in/out of chair, and walking. They are also asked if they are “limited in the kind or amount of work” they can perform. If a limitation of any type has a “yes” response, respondents are shown a list of 34 possible medical conditions and asked to identify those that cause the limitation. Multiple causes may be identified. This section uses the adult database and focuses on cases where arthritis is identified as a cause of limitations. The variable AAAL, defined in the introduction to this arthritis section, is based on a single question in the NHIS1 and produces somewhat different numbers than this more inclusive definition of activity limitations.

Limitations in any activities of daily living (ADLs) include seven components.  Musculoskeletal-related ADLs include only the three limitations related to movement and action commonly associated with musculoskeletal diseases and are 1) “needing help with routine needs,” 2) ”needing help with personal care,” and 3) “having difficulty walking without equipment.” Other ADLs are related to memory, vision, hearing, and other limitations.

Of the 35.6 million adults with limitations in any ADL, 23% (8.0 million) named arthritis as a cause; the proportion jumped to 29% for those with a limitation in musculoskeletal-related ADLs. One-third (33%, 4.5 million of 13.9 million) of adults with difficulty walking identified arthritis as a cause. More than 1 in 4 attributed their need for help with routine needs (2.8 million) or personal care (1.5 million) to arthritis. (Reference Table 3A.4.2.1 PDF [501] CSV [502])
 
These numbers demonstrate the large impact of arthritis on adults with limitations in any ADL or in musculoskeletal related ADLs. The effect was much stronger among females than males (Reference Table 3A.4.2.1 PDF [501] CSV [502]) and among older adults. (Reference Table 3A.4.2.2 PDF [503] CSV [504])

Little difference was found between adults by race/ethnicity except for slightly higher proportion of non-Hispanic blacks attributing limitations to arthritis. (Reference Table 3A.4.2.3 PDF [505] CSV [506]). Geographic region in the US does not seem to be a factor. (Reference Table 3A.4.2.4 PDF [507] CSV [508])

Work limitations are defined here as those unable to work now due to health or limited in kind or amount of work (i.e., “unable to work” or “limited in work”). Of the 28.1 million adults with work limitations per year in 2013-2015, arthritis attributable work limitations (AAWL) affected on average 23% (6.4 million).  Among those with any medical condition limiting work, 23% attributed their inability to work now to arthritis, while 22% limited in kind or amount of work did so. Higher percentages of females and older workers identified arthritis as a cause for work limitations. There was little difference seen by race/ethnicity or geographical region. (Reference Table 3A.4.2.1 PDF [501] CSV [502]; Table 3A.4.2.2 PDF [503] CSV [504]; Table 3A.4.2.3 PDF [505] CSV [506]; and Table 3A.4.2.4 PDF [507] CSV [508]).

 

Quality of Life and Lifestyle Factors

Among persons with DDA, compared with those without DDA, Health-Related Quality of Life (HRQoL) is worse on several scales. When assessed by self-reported health status, 27% of those with DDA reported fair/poor health compared to 12% of those without DDA. The DDA group also reported a higher mean number of days in the past month with poor physical health (6.6 vs 2.5 days), poor mental health (5.4 vs 2.8 days), or days with limitations in usual activities (4.3 vs 1.4 days).2 Using the same “unhealthy days” measures, an analysis of 2014 Humana Medicare Advantage members found that those with arthritis had more total unhealthy days, by 2.2 days per year, than those without arthritis, and that comorbid arthritis associated with hypertension, diabetes, chronic obstructive pulmonary disease, and congestive heart failure resulted in significant increases in both physically and mentally unhealthy days.3
 
The prevalence of DDA and of AAAL is much higher among those with the adverse lifestyle factors of obesity, insufficient or no physical activity, and fair/poor self-rated health.4 (Reference Table 3A.4.3 PDF [513] CSV [514])

 

• 1. National Health Interview Survey 2013-2015. Question: “Are you limited in any way in any of your usual activities because of arthritis or joint symptoms?” https://www.cdc.gov/nchs/nhis/nhis_questionnaires.htm [515].
• 2. Furner SE, Hootman JM, Helmick CG, Bolen J, Zack MM. Health-related quality of life of US adults with arthritis: analysis of data from the Behavioral Risk Factor Surveillance System, 2003, 2005 and 2007. Arthritis Care Res 2011;63(6):788-799.
• 3. Havens MA, Slabaugh SL, Helmick CG, et al. Comorbid arthritis is associated with lower health-related quality of life in older adults with other chronic conditions, United States, 2013-2014. Prev Chronic Dis 2017;14:160495. DOI: https://doi.org/10.5888/pcd14.160495.  [516] https://www.cdc.gov/pcd/issues/2017/16_0495.htm  [517] Accessed September 8, 2017.
• 4. Barbour KE, Helmick CG, Boring M, Brady TJ. Vital signs: prevalence of doctor-diagnosed arthritis and arthritis-attributable activity limitation — United States, 2013–2015. MMWR 2017;66:246–253. DOI: http://dx.doi.org/10.15585/mmwr.mm6609e1 [518].

The Economic Cost [519] section of this report uses the Medical Expenditures Panel Survey (MEPS), a standard source for cost of illness estimates, to estimate the total direct and indirect costs of musculoskeletal conditions and selected categories of musculoskeletal conditions, as well as the incremental direct and indirect costs specifically attributable to the selected category. Total costs are all costs for a patient regardless of the condition responsible; incremental costs are those costs attributed to a specified condition. A quick review of all economic terms used can be found by clicking HERE [520]. 

There are several important points to remember here. First, for arthritis and other rheumatic conditions, MEPS requires the use of selected 3-digit ICD-9-CM codes, using the 3- and 4-digit NADW AORC ICD-9-CM codes [521] to create a similar category called “arthritis and joint pain.” This approach has been used for a number of years and provides a comparative estimate of the costs of AORC. Additionally, costs estimates are per person and reported as mean per person costs. To arrive at the estimated aggregate cost, the mean per person cost is multiplied by the number of people affected, resulting in a total cost for conditions in the United States.

MEPS provides estimates of actual medical “expenditures,” meaning money changing hands, rather than medical “charges,” which are based on what is originally billed but rarely paid in full. Thus, the term direct costs, as used here, reflects actual medical expenditures. Indirect costs are those associated with lost wages. Aggregate costs for both direct and indirect costs are the sum of per-person costs across all individuals with the condition.

All-cause costs include medical expenditures or lost wages for persons with musculoskeletal disease, regardless of whether those costs are due to the musculoskeletal disease or another medical condition. Incremental costs are those estimated as attributable to musculoskeletal disease.

Direct Costs

Annual all-cause direct costs, in 2014 dollars, for arthritis and joint pain increased from a per person mean of $6,642 in the years 1996-1998 to $9,554 in 2012-2014. Incremental direct costs for arthritis and joint pain increased from a per person mean of $679 in the years 1996-1998 to a mean of $1,352 in 2012-2014, in 2014 dollars. The change in total mean costs was 44%, while incremental mean costs doubled. Incremental arthritis and joint pain costs showed a decline in 2012-2014 annual average costs compared to the previous five periods. (Reference Table 8.4.3 PDF [522] CSV [523]; Table 8.5.3 PDF [524] CSV [525])

Mean per person direct costs include ambulatory care, inpatient care, prescriptions, and other healthcare costs. In 2012-2014, ambulatory care accounted for about a third of per person direct costs, with inpatient care and prescriptions each accounting for approximately one-quarter (28% and 25%, respectively) of total cost. Over the past 18 years, prescription costs have seen the greatest change, rising nearly 140% per person in that time. Both inpatient and other healthcare costs remained steady at 9% and 11% increase, respectively. Ambulatory care increased by 59% over the same time period. (Reference Table 8.4.3 PDF [522] CSV [523])

Annual all-cause aggregate medical costs for persons with a diagnosis of arthritis and joint pain in the US increased from $192.4 billion in 1996-1998 to $626.8 billion, in 2014 dollars, for the years 2012-2014. Aggregate annual direct costs specifically attributed to arthritis and joint pain (incremental costs) in the US increased from $19.7 billion in 1996-1998 to $88.7 billion for the years 2012-2014, in 2014 dollars. While the increase over the 18-year period for total aggregate costs was more than 225%, the increase for incremental aggregate costs was greater than 350%, despite the recent decline in aggregate incremental costs. (Reference Table 8.6.3 PDF [530] CSV [531])

Annual per-person all-cause direct costs for arthritis and joint pain are highest for people age 65 and older, females, non-Hispanic whites, and residents of the Northeast region. Lower education and marital staus (divorced-widowed-separated) are also factors in higher cost. Public only insurance (Medicaid/Medicare) show the highest per person costs, in part because they serve a large share of the elderly population. (Reference Table 8.15.3 PDF [534] CSV [535])

Mean and aggregate total and incremental direct and indirect costs for osteoarthritis [536], rheumatoid arthritis [537], gout [538], and connective tissue disease [539], using the annual average for years 2008-2014 MEPS data, are calculated and shown in their respective sections.

Indirect Costs

“Indirect costs” as used in this report reflect estimates of earnings losses for persons with a work history who are unable to work due to a medical condition. They do not reflect supplemental measures, such as reduced productivity, worker replacement, or early retirement due to medical conditions.

Indirect costs are not estimated for the broad category of arthritis and joint pain.

 

Because many types of arthritis have a higher prevalence among older adults, we expect that the current aging of the population will increase the prevalence and impact of AORC unless new interventions are implemented within the near future. The projections of arthritis prevalence and AAAL take into account age and sex, but do not take into account potentially important factors such as the obesity epidemic and the increasing frequency of joint injuries.1 The age-adjusted percentage of AAAL among adults with arthritis increased 19% between 2002-2004 and 2013-2015.2 Previous costs of arthritis have been driven by age-related increases in prevalence,3 so future costs of arthritis are likely to be driven higher by the same age-related increase in prevalence, but also from the increasing frequency of surgical interventions.

• 1. Hootman JM, Helmick CG. Updated projections of US prevalence of arthritis and associated activity limitations. Arthritis Rheum 2016;68(7):1582-1587.
• 2. Barbour KE, Helmick CG, Boring M, Brady TJ.  Prevalence of doctor-diagnosed arthritis and arthritis-attributable activity limitation—United States, 2013-2015. MMWR 2017;66(9):246-253.
• 3. Cisternas MG, Murphy L, Yelin E, Foreman AJ, Pasta DJ, Helmick CG. Trends in medical care expenditures of adults with arthritis and other rheumatic conditions: 1997 to 2005. J Rheum 2009;36:2531-8.

Several data limitations exist for monitoring AORC burden in the future. First, on October 1, 2015, ICD-10-CM was required for use in clinical records; it was previously in use for death records. The current National Arthritis Data Workgroup definition of AORC uses ICD-9-CM codes. Due to significant changes in conceptualizing the new codes, a direct translation cannot be made. This means a new definition of AORC or some similar concept will be needed for analyses using ICD-based data in the future. CDC is working with ICD-10-CM translation experts and selected stakeholders to propose a draft standard ICD-10-CM based definition, which will be shared with the larger arthritis community to reach agreement on a new definition.

Second, there is a need for data on more specific conditions, for example rheumatoid arthritis, systemic lupus erythematosus, and psoriatic arthritis, to help drive clinical (eg, treatment, quality of care) and public health (eg, self-management education, safe physical activity) efforts that allow for better incidence estimates in order to better understand risk. Electronic health records may prove helpful in creating valid measures. There is also a lack of data on patient reported outcome measures (PROMs) on pain and function in electronic health records and administrative databases. These outcome measures are important to assessing the impact/burden of rheumatic and musculoskeletal diseases. 

Arthritis and other rheumatic conditions are not addressed with the same priority as many other chronic conditions, perhaps because such priorities are driven more by easily available measures of mortality rather than by more challenging measures such as quality of life, disability, and impact on work. However, there is a growing policy interest in the role of multiple chronic conditions in health and health costs,1 and AORC plays a major role from this perspective for at least three reasons. First, those with priority chronic conditions are highly affected by AORC, with about half of adults with heart disease or diabetes and about a third of adults with obesity affected by DDA.2^,3^,4 Second, arthritis is very common condition among individuals with two or more chronic conditions, regardless of the conditions considered.5 Third, those with arthritis as one of their multiple chronic conditions fare much worse on important life domains such as social participation restriction, serious psychological distress, and work limitations.6

• 1. U.S. Department of Health and Human Services. HHS initiative on multiple chronic conditions. http://www.hhs.gov/ash/initiatives/mcc/ [540]. Accessed October 24, 2018.
• 2. Bolen J, Murphy L, Greenlund K, et. al. Arthritis as a potential barrier to physical activity among adults with heart disease — United States, 2005 and 2007. MMWR 2009;58(7):165-169.
• 3. Bolen J, Hootman J, Helmick CG, et. al. Arthritis as a potential barrier to physical activity among adults with diabetes — United States, 2005 and 2007. MMWR 2008;57(18):486-489.
• 4. Barbour KE, Hootman JM, Murphy LB, Helmick CG. Arthritis as a potential barrier to physical activity among obese adults–United States, 2007 and 2009. MMWR 2011;60(19):614–618.
• 5. Ward BW, Schiller JS. Prevalence of multiple chronic conditions among US adults: estimates from the National Health Interview Survey, 2010. Prev Chronic Dis 2013;10:120203. DOI: http://dx.doi.org/10.5888/pcd10.120203 [541].
• 6. Qin J, Theis KA, Barbour KE, et.al. Impact of arthritis and multiple chronic conditions on selected life domains — United States, 2013. MMWR 2015;64(21):578-582.

There are widespread and consistent professional recommendations for most types of AORC that involve increasing self-management of the disease through education, physical activity, and achieving a healthy weight, but little progress is being made.1 Such behavioral interventions offer evidence-based improvements to patients without the side effects seen with medications and other interventions. While most clinical settings are not set up to help patients achieve these recommendations effectively, increasing clinical/community linkages may offer a better approach. To see if provider referrals to community resources is a better solution, approaches such as the 1.2.3 Approach to Provider Outreach [542] and Spread the Word: Marketing Self-Management Education Through Ambassador Outreach [543] are being pilot tested in communities.
 
The Healthy People [544] project started with the 1979 Surgeon General’s report, Healthy People: The Surgeon General’s Report on Health Promotion and Disease Prevention. The current version of Healthy People 2020 [545] has set nine arthritis objectives for the nation to achieve by 2020, but only limited progress has occurred with the current level of investments in interventions. Currently, four new developmental objectives are included in the Arthritis, Osteoporosis, and Chronic Back Conditions [546] topic area as part of a larger effort to insure that chronic pain, regardless of the original cause, is included in Healthy People 2020.

There is a need for more conveniently measured outcomes that are important to most people. Such outcomes include effects on work, activities, health-related quality of life, independence, and ability to keep doing valued life activities.

Research funding to develop and evaluate more effective clinical and public health interventions is relatively modest, given that arthritis is the most common cause of disability and is a large and growing problem, affecting 54.4 million adults now,2 and a projected 78 million by 2040.3 This is especially frustrating because even the evidence-based interventions we have now are not reaching the people who would benefit from them. Implementation research to translate effective interventions to clinical practice and/or community settings is needed.

Although most adults with doctor-diagnosed arthritis are younger than age 65 and in their working years, the effect of their arthritis on employment and work, and the effect of reasonable workplace accommodations, have not been explored in depth. There is a need for the development and demonstration of web-based or app-based interventions for education, physical activity and achieving a healthy weight. This is an urgent issue right now and will continue to be an urgent issue as an aging workforce keeps working beyond age 65, as is anticipated.

 

 

 

• 1. Office of Disease Prevention and Health Promotion. HealthyPeople.gov.  http://www.healthypeople.gov/2020/data-search/Search-the-DData?&f[0]=field_topic_area%3A3507  [547]  Accessed October 24, 2018.
• 2. Barbour KE, Helmick CG, Boring M, Brady TJ. Vital signs: prevalence of doctor-diagnosed arthritis and arthritis-attributable activity limitation — United States, 2013–2015. MMWR 2017;66:246–253. DOI: http://dx.doi.org/10.15585/mmwr.mm6609e1 [518]. Accessed July 31, 2017.
• 3. Hootman JM, Helmick CG, Barbour KE, et al. Updated projected prevalence of self-reported doctor-diagnosed arthritis and arthritis-attributable activity limitation among US adults, 2015-2040. Arthritis Rheumatol 2016:68(7):1582-1587.

As noted above, the use of ICD-9-CM codes for clinical and public health purposes ended with the healthcare system shift to the ICD-10-CM codes on October 1, 2015. This means the national surveys analyzed here that use ICD codes will shift to ICD-10CM as well. Standard definitions of generic and specific types of AORC need to be developed for clinical and public health researchers using the new ICD-10-CM codes; otherwise, investments in research will not be comparable and will be unable to build on each other.

Codes used in this analysis of AORC are based on the "National Arthritis Data Workgroup ICD-9-CM diagnostic codes for arthritis and other rheumatic conditions." Centers for Disease Control and Prevention, Arthritis Program, National Arthritis Data Workgroup.1

Osteoarthritis and allied disorders
    715-Osteoarthritis and allied disorders
Rheumatoid arthritis
    714-Rheumatoid arthritis and other inflammatory polyarthropathies
Gout and other crystal arthropathies
    274-Gout
    712-Crystal arthropathies
Joint pain, effusion and other unspecified joint disorders
    716.1, .3-.6-.9-Other unspecified arthropathies
     719.0, .4-.9-Other and unspecified joint disorders
Spondylarthropathies
    720-AS/inflammatory spondylopathies
    721-Spondylosis and allied disorders
    99.3-Reiter’s Disease
    696.0-Psoriatic arthopathy
Fibromyalgia
    729.1-Myalgia and myositis unspecified
Diffuse connective tissue disease
    710-Diffuse connective tissue disease [excl 710.0-.2]
    710.2-Sicca syndrome (also called Sjögren's syndrome)
    710.1-Systemic sclerosis (SSC, scleroderma)
    710.0-Systemic lupus erythematosus (SLE)
Carpal tunnel syndrome
    354.0-Carpal tunnel syndrome
Soft tissue disorders (excluding back)
    726-Peripheral enthesopathies and allied disorders
    727-Other disorders of synovium/tendon/bursa
    728.0-.3, .6–.9-Disorders of muscle/ligament/fascia
    729.0-Rheumatism, unspecified and fibrositis
    729.4-Fascitis, unspecified
Other specified rheumatic conditions
    95.6-Syphilis of muscle
    95.7-Syphilis of synovium/tendon/bursa
    98.5-Gonococcal infection of joint
    136.1-Behcet’s syndrome
    277.2-Other disorders purine/pyrimidine metabolism
    287.0-Allergic purpura
    344.6-Cauda equina syndrome
    353.0-Brachial plexus/thoracic outlet lesions
    355.5-Tarsal tunnel syndrome
    357.1-Polyneuropathy in collagen vascular disease
    390-Rheumatic fever w/o heart disease
    391-Rheumatic fever w/heart disease
    437.4-Cerebral arteritis
    443.0-Raynaud’s syndrome
    446-Polyarteritis nodosa and allied conditions [excl 446.5]
    447.6-Arteritis, unspecified
    711-Arthritis associated with infections
    713-Arthropathy associated w/disorders classified elsewhere
    716.0, .2, .8-Specified arthropathies
    719.2, .3-Specified joint disorders
    725-Polymyalgia rheumatica

• 1. Centers for Disease Control and Prevention. Arthritiiis Case Definitions. http://www.cdc.gov/arthritis/data_statistics/arthritis_codes_2004.pdf [548] ). Accessed October 29, 2013.

Osteoarthritis (OA) is widely recognized as the most common form of arthritis, and a major cause of pain and disability among US adults. Estimates of prevalence vary depending on how OA is defined: radiographic, symptomatic radiographic, or symptomatic only (self-reported presence of pain, aching, or stiffness). Radiographic OA is reported at higher prevalence levels than symptomatic, but symptomatic OA is more often cited from the self-reported databases.

From 2008 to 2014, 32.5 million US adults, or one in seven persons (14%), reported osteoarthritis and allied disorders, including joint pain with other specified or unspecified arthropathy, (herein called “osteoarthritis”) annually. Per previous research on the definition of osteoarthritis in the Medical Expenditure Panel Survey (MEPS),1 OA was defined as the presence of ICD-9-CM code 715 or a self-reported diagnosis of arthritis excluding rheumatoid arthritis and presence of ICD-9-CM 716 or ICD-9-CM 719. (Reference Table 8.13 PDF [554] CSV [555])

Across socio-demographic and health status characteristics, the following five groups represented the largest number of adults with OA by demographic classification: non-Hispanic whites (25.3 million), middle age (45-64 years) (14.8 million) or older adults (≥ 65 years) (13.8 million), those with private insurance (18.8 million), and those who were married/had a partner (17.8 million). (Reference Table 8.22 PDF [556] CSV [557])

However, total numbers do not reflect the share of the population group with OA. For example, females represent about 51% of the adult population in any given year, but comprise 78% of adults with OA. An even more disproportionate share of 18% of the population age 65 and older have OA (43%). This compares to 46% with osteoarthritis in the 34% of the population age 45 to 64 years. Non-Hispanic whites still have the highest share by race/ethnicity, comprising 65% of the population but 78% of those with OA, while Hispanics have the lowest (15% of population to 7% of adults with OA). Geographic region is not a major factor for OA, although the Midwest has a higher proportion of cases than it represents in the US population.

Share of the total OA population, however, does not give the whole picture. Since OA is closely linked to age, race/ethnicity and geographical regions with younger population segments will exhibit a lower overall share of OA patients. Both non-Hispanic black and Hispanic populations have a higher share of adults age 45 and older reporting OA than is found among non-Hispanic white adults. Hence, while non-Hispanic white adults represent the largest group of adults with OA, other race/ethnic groups have higher rates of OA. This same pattern can be seen in geographic regions, where the West has a younger population but higher rate of OA in the 65 and older population than is found in other regions. (Reference Table T3A.1.1.a PDF [562] CSV [563])

Joint Involvement in Osteoarthritis

Most OA diagnoses in both a hospital and outpatient setting do not specify the bodily site for which a healthcare visit is made. However, among those that are diagnosed with a specific site, the knee is the most common, followed by the hip. The knee accounts for about one-third (31%) of OA visits in all settings and is the only site identified in the data that meets reliability standards in all outpatient settings. Osteoarthritis in the hip accounts for 14% of hospital discharges, and 6% of physician office visits. (Reference Table 3C.1.0 PDF [566] CSV [567])

 

Healthcare Utilization

Osteoarthritis was diagnosed in 23.7 million healthcare visits in 2013, or 2.4% of all healthcare visits for any cause (Reference Table 3A.3.0.1 PDF [404] CSV [405]). It accounted for 10% of all hospitalizations and 2% of ambulatory visits.

Hospitalization

Nearly 3 million hospital stays in 2013 had an OA diagnosis and it was the leading cause (46%) of hospitalization among all arthritis diagnoses. Osteoarthritis accounted for 45% of total hospital charges for arthritis diagnoses (cost charged but not necessarily paid), presumably in part because OA is the principal diagnosis associated with hip and knee joint replacements. Fewer than half (43%) of patients with an OA diagnosis were discharged to home or self-care, the lowest share of all arthritis diagnosed hospitalized patients. This is probably due to discharges to assisted living facilities or skilled nursing homes for rehabilitation following the hip or knee joint replacement. (Reference Table 3A.3.0.1 PDF [404] CSV [405]; Table 3A.3.1.1.1 PDF [428] CSV [429]; Table 3A.3.1.3.1 PDF [441] CSV [442]; and Table 3A.5.3 PDF [568]CSV [569])

Females hospitalized with OA outnumber males two to one, while two in three patients were age 65 and older and hospitalized at a rate of 4.5 in 100. Non-Hispanic whites had the highest rate of hospitalization for OA (1.4 in 100 persons), while Hispanics had the lowest rate (0.4/100). Residents of the Midwest region were also more likely to be hospitalized with a diagnosis of OA (1.5/100), while those living in the West were least likely (0.9/100). Regional differences are a product of age to some degree, with the mean age of the Northeast and Midwest about 4 years older than the West. (Reference Table 3A.3.1.0.1 PDF [416] CSV [417]; Table 3A.3.1.0.2 PDF [418] CSV [419]; Table 3A.3.1.0.3 PDF [420] CSV [421]; and Table 3A.3.1.0.4 PDF [422] CSV [423])

Ambulatory Care Visits

Osteoarthritis was diagnosed in 20.8 million outpatient visits in 2013 and accounted for one in five (21%) ambulatory care visits with any arthritis diagnosis. This was a rate of 1 in 12 (8.4%) outpatient visits for any diagnoses including an OA diagnosis. Visits per 100 were higher among females, adults 45 years and older, and non-Hispanic whites and blacks. Residents in the South had the lowest rate of outpatient visits for OA. (Reference Table 3A.3.2.0.1 PDF [451] CSV [452]; Table 3A.3.2.0.2 PDF [453] CSV [454]; Table 3A.3.2.0.3 PDF [455] CSV [456]; Table 3A.3.2.0.4 PDF [457] CSV [458])

Economic Burden

Combining direct and indirect costs for OA and allied disorders, average annual all-cause costs for the years 2008-2014 were $486.4 billion. Total incremental costs (direct and indirect costs directly associated with osteoarthritis) were $136.8 billion. (Reference Table 8.13 PDF [554] CSV [555])

Direct Medical Costs

Among all adults with osteoarthritis, annual all-cause per person direct costs were $11,502. Those reporting limitations had the highest all-cause per person direct costs: any limitation in work, housework, or school activities ($17,136) or any limitation in IADLs, ADLs, functioning, work, housework, school, vision or hearing ($14,146).

Annual total all-cause direct costs were $373.2 billion.  The five socio-demographic groups with the highest total all-cause direct costs were: non-Hispanic whites ($300.7 billion); those with any limitation in IADLs, ADLs, functioning, work, housework, school, vision or hearing ($298.5 billion); any limitation in work, housework, or school activities ($213.0 billion); any private insurance ($216.5 billion); or who were married/had a partner ($200.4 billion).

Osteoarthritis incremental direct medical costs totaled $65.5 billion annually; average per person OA incremental costs were $2,018. (Reference Table 8.13 PDF [554] CSV [555], and Table 8.22 PDF [556] CSV [557])

Indirect Costs

Some 16.7 million adults of working age (18-64 years) with a work history had OA. The ratio of persons in the labor force without osteoarthritis (90%) is higher than for those with OA (69%), resulting in earnings losses due to OA.

On average, for the years 2008-2014, those without OA earned $6,783 more than those with OA, which represented a total of $113.2 billion in all-cause earnings losses for all U.S. adults with OA. Earnings losses attributable to OA were $71.3 billion; per person osteoarthritis-attributable earnings losses were $4,274. (Reference Table 8.13 PDF [554] CSV [555])

Lifetime OA Treatment Costs

Lifetime cost attributed to knee OA in 2013 were $140,300. More than one-half (54%) of knee OA patients underwent total knee arthroplasty (TKA) an average of 13 years after diagnosis. The largest proportion of knee OA-related direct medical costs for those meeting TKA eligibility criteria was attributable to primary TKA.2

• 1. Cisternas MG, Murphy L, Sacks JJ, Solomon DH, et al. Alternative methods for defining osteoarthritis and the impact on estimating prevalence in a US population-based survey. Arthritis Care Res 2016;68(5):574-580.
• 2. Losina E, Paltiel AD, Weinstein AM, et al. Lifetime medical costs of knee osteoarthritis management in the United States: impact of extending indications for total knee arthroplasty. Arthritis Care Res (Hoboken) 2015;67(2):203-215.

Inflammatory arthritis is a group of diseases characterized by inflammation of the synovial membrane in the joints and, often, other tissues throughout the body. Some forms of inflammatory arthritis are autoimmune diseases, conditions in which the body’s immune system attacks healthy tissue, also known as systemic autoimmune rheumatic diseases (SARD). Examples of SARDs that cause inflammatory arthritis include rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), Sjögren’s syndrome (SjS), systemic sclerosis (SSc), polymyositis (PM), and dermatomyositis (DM). Other types of inflammatory arthritis include axial spondyloarthritis (formerly called ankylosing spondylitis) and psoriatic arthritis, along with gout which is also considered a metabolic arthritis and discussed under it's own heading.

As a group, inflammatory arthritic diseases are characterized by joint pain, swelling, warmth, and tenderness in joints, and can cause deformity and loss of function of affected joints.  Since these diseases are systemic, they may be associated with involvement of other tissues or organs including the skin, eye and bowel. In addition, in these diseases, blood tests provide evidence of inflammation and some conditions are useful markers that assess disease likelihood. Inflammatory arthritis conditions are sometimes difficult to diagnose and distinguish; all patients suspected of having an inflammatory arthritis should be referred to a rheumatologist for evaluation and management. Arthritis occurring in children and adolescents is referred to as juvenile idiopathic arthritis (formerly juvenile rheumatoid arthritis) and is discussed in the Juvenile Arthritis [401] heading.

Only the most common inflammatory arthritides will be discussed below. A listing of the many types of inflammatory arthritis and related conditions can be seen by clicking HERE [576].

Gout is caused by a buildup in the body of uric acid, in the form of monosodium urate crystals that the body cannot rid itself of quickly. This condition is characterized by hyperuricemia, referring to an elevation in the serum level of uric acid. It is not fully understood why some people with hyperuricemia develop gout and others do not. Gout is characterized by recurrent attacks of painful, red, tender, warm, and swollen joints, which generally affects only one joint at a time, often the large toe. It is more common in men, but also affects women after menopause. Repeated flares of gout can lead to chronic gouty arthritis, with involvement of multiple joints and the development of subcutaneous nodules, called tophi.  While gout can be an intermittent condition, it can also lead to severe chronic arthritis and joint damage and deformity. Gout occurs frequently in patients with what is termed the metabolic syndrome and affects patients who also have diabetes, hypertension, and obesity.

Other crystal arthropathies can be caused by deposits of calcium pyrophosphate dihydrate (CPPD) crystals in the joints and have symptoms similar to gout. CPPD deposition disease is less common than gout, although radiographic chondrocalcinosis is common in older adults.

Prevalence of Gout

Prevalence estimates of gout vary for the US from 1% - 4%, depending on the data source and time frame. In 2005, an estimated 6.1 million adults reported having gout at some time, with 3.0 million affected each year.1 Estimates from the MEPS analyzed for the economic data section reported  3.1 million US adults had gout annually for the years 2008-2012, an annual prevalence rate of 1.3%.(Reference Table 8.13 PDF [554] CSV [555] and Table 8.24 PDF [629] CSV [630]) Additional studies report a higher prevalence of 3.9%, or 8.3 million adults in 2007-2008, using the NHANES as the basis of estimates.2^,3^,4 Another NHANES study from 2007-2010 reported a prevalence of 3.8%.5 Overall, it is believed the prevalence of gout is rising, with obesity and hypertension cited as contributors.2^,4 A study of hospitalization trends using the NIS from 1993-2011 supported this, showing hospitalizations with a diagnosis of rheumatoid arthritis declining over the study period while diagnosis of gout was reported as increasing.6

Prevalence of gout is higher in males than in females, 5.9% to 2.0%, respectively,4 or at a ratio of 3-4:1. The incidence of gout increases with age, and was shown in the MEPS to be higher in the following select socio-demographic groups: non-Hispanic whites (2.3 of 3.1 million); married/had a partner (1.9 million); any private insurance (2.0 million); those with any limitation in IADLs, ADLs, functioning, work, housework, school, vision, or hearing (1.7 million). (Reference Table 8.24 PDF [629] CSV [630]).

 

Healthcare Utilization

Hospitalization

More than 850,000 hospitalizations in 2013 had a diagnosis of gout, representing 2.9% of hospitals visits for any diagnoses, and accounting for 3.3% of all hospital charges billed. Gout is diagnosed along with joint pain and soft tissue disorders when multiple diagnoses are made (7% and 3.5% cross-diagnosis, respectively). At discharge, patients diagnosed with gout are more likely to be transferred to short-term or home health care than those with any diagnoses (45% vs 31%). (Reference Table 3A.3.1.0.1 PDF [416] CSV [417]; Table 3A.3.0.2 PDF [408] CSV [409]; Table 3A.3.1.1.1 PDF [428] CSV [429]; Table 3A.3.1.3.1 PDF [441] CSV [442])

 

Ambulatory Care Visits

Gout diagnoses were made in only 0.5% of ambulatory care visits for any diagnosis, accounting for 5.3 million ambulatory visits. Ambulatory visits were made more frequently by males (72%), those aged 65 years and older (50%), non-Hispanic whites (59%), and by those living in the Northeast (rate of 2.8/100 persons versus 2.1/100 for all regions). (Reference Table 3A.3.2.0.1 PDF [451] CSV [452]; Table 3A.3.2.0.2 PDF [453] CSV [454]; Table 3A.3.2.0.3 PDF [455] CSV [456]; and Table 3A.3.2.0.4 PDF [457] CSV [458])

 

Economic Burden

Estimates for gout, defined as ICD-9-CM 274, were generated from 2008-2012 MEPS data; analysis was limited to those years because the ICD-9-CM code for gout was suppressed in 2013 and 2014 MEPS data. Combining direct and indirect costs for gout, total average costs annually for the years 2008-2012 were $26 billion. Incremental costs could not be calculated due to a small sample size. (Reference Table 8.13 PDF [554] CSV [555])

 

Direct Costs

Among all adults with gout, all-cause per person direct costs were $11,936. Those with any limitation in work, housework, or school activities had the highest all-cause per person direct costs ($16,843) whereas those age 18-44 years had the lowest ($5,934). Total all-cause direct costs were $36.6 million.  Direct costs attributable to gout were not reported because the relative standard errors for the estimates was greater than 30%. (Reference Table 8.13 PDF [554] CSV [555] and Table 8.24 PDF [629] CSV [630])

 

Indirect Costs

The percentage working during the year among adults age 18-64 years was similar for those with (85%) and without gout (88%). Per person, those with gout earned $6,810 more than those without gout; thus, overall, those with gout had negative earnings losses (aggregate of -10.0 billion). Like direct costs, earnings losses attributable to gout were not reported because the estimates were unreliable, with a relative standard error greater than 30%. (Reference Table 8.13 PDF [554] CSV [555]).

 

• 1. Lawrence RC, Felson DT, Helmick CG, et al for the National Arthritis Data Workgroup. Estimates of the prevalence of arthritis and other rheumatic conditions in the United States:  Part II. Arthritis & Rheumatism 2008;58(1):26-35.
• 2. a. b. Gadol N. Global burden of gout: prevalence and risk factors. https://www.medpagetoday.com/resource-center/Gout/Global-Burden/a/54489 [637] . Accessed September 25, 2017.
• 3. Dalbeth N, Merriman TR, Stamp LK. Gout. Lancet 2016:355(10055);2039-2052.
• 4. a. b. c. Zhu Y, Pandya BJ, Choi HK. The National Health and Nutrition Examination Survey 2007-2008. Arth & Rheum 2011:63(10);3136-3141. Doi 10.1002/art.30520.
• 5. Lim SY, Lu N, Oza A, et al. Trends in gout and rheumatoid arthritis hospitalizations in the United States, 1993-2011. JAMA. 2016:315(21);2345-2346.
• 6. Roddy E, Choi H. Epidemiology of gout. Rheum Dis Clin North Am. 2014:40(2);155-175. Doi: 10.1016/j.rdc.2014.01.001.

Arthritis from joint infection, known by the umbrella term as septic arthritis, can occur from an infection anywhere in the body traveling through the bloodstream. It can also occur from a penetrating injury that delivers germs directly to a joint. An infected joint is usually very tender, swollen, and painful. When caught early and treated with antibiotics it can be cleared of the joint infection. Surgical drainage of the infected joint is often necessary which can be performed arthroscopically. In some cases, the arthritis becomes chronic. Knees are most commonly affected, but septic arthritis also can affect hips, shoulders, and other joints. Often, an infected joint has been affected by another form of arthritis. Gonococcal septic arthritis, transmitted from gonorrhea bacterium, a sexually transmitted disease, can occur in otherwise healthy individuals. Lyme disease is another form of arthritis associated with infection and occurs in certain areas of the country.

The incidence of septic arthritis in industrialized countries, including the US, is estimated at six (2-10) per 100,000 population per year. In persons with underlying joint disease or prosthetic joints, incidence increases to 6-30 per 100,000 per year. The most susceptible populations are young children and the elderly.1 Infection can occur in a prosthetic joint and be a source of chronic pain. Biologics, while shown to work well for RA and other inflammatory arthritis pain, have also been associated with statistically significant higher rates of serious infections as they are designed to weaken the immune system. Serious infections included opportunistic infections as well as bacterial infections in most studies.2 These side effects of increased risk for septic arthritis are recognized and published in numerous sources.

Septic arthritis is included in the “other specific rheumatic conditions” in the AORC discussion.

• 1. Lynn MM, Mathews CJ. Advances in the management of bacterial septic arthritis. International Journal of Clinical Rheumatology 2012;7(3):335-342.
• 2. Singh JA, Wells GA, Christensen R, et al. Adverse effects of biologics: a network meta-analysis and Cochrane overview. Cochrane Library. http://onlinelibrary.wiley.com/doi/10.1002/14651858.CD008794.pub2/abstra... [638] Accessed October 24, 2017.

Fibromyalgia does not fit within the main arthritis classifications but is considered a chronic pain condition. The primary symptoms are widespread pain throughout the body and fatigue. Recent revisions to diagnosis now focus on four criteria.1  
1)    Generalized pain, defined as pain in at least 4 of 5 regions is present.
2)    Symptoms have been present at a similar level for at least 3 months.
3)    Widespread pain index (WPI) ≥7 and symptom severity scale (SSS) score ≥5 OR WPI of 4-6 and SSS score ≥9.
4)    A diagnosis of fibromyalgia is valid irrespective of other diagnoses. A diagnosis of fibromyalgia does not exclude the presence of other clinically important illnesses.

The cause of fibromyalgia is not known, but current theories include a higher sensitivity to pain. Fibromyalgia can occur by itself, although it can also accompany another form of arthritis such as rheumatoid arthritis or spondyloarthritis.

 

Prevalence of Fibromyalgia

Estimates of fibromyalgia range from 4 million (2% of the adult population)2 to 10 million (5% of adult population).3 Fibromyalgia is most prevalent in females, with up to 90% of incident cases females. It is also more common among older members of the population.

 
Healthcare Utilization

Hospitalization

Just under one-half million (442,000) hospitalizations in 2013 had a diagnosis of fibromyalgia, representing 1.5% of hospital visits for any diagnoses, and accounting for 1.4% of all hospital charges billed. Females accounted for 89% of the hospitalizations, with those age 45 to 64 accounting for nearly half (48%) of the discharges. Fibromyalgia is diagnosed along with connective tissue disease (11.1%), joint pain (8.2%), and rheumatoid arthritis (7.1%) when multiple diagnoses are made. Hospital stays are similar to discharges for any diagnoses in length of stay and mean charges. Discharge to home is most common.  (Reference Table 3A.3.1.0.1 PDF [416] CSV [417]; Table 3A.3.1.0.2 PDF [418] CSV [419]; Table 3A.3.0.2 PDF [408] CSV [409]; Table 3A.3.1.1.1 PDF [428] CSV [429]; Table 3A.3.1.3.1 PDF [441] CSV [442])

 

Ambulatory Care Visits

Fibromyalgia diagnoses were made in 0.8% of all ambulatory care visits for any diagnosis, accounting for 7.7 million ambulatory visits. Ambulatory visits were made more frequently by females (79%), those aged 45-64 years (52%), non-Hispanic whites (74%), and by those living in the Northeast region (rate of 3.8/100 persons versus 3.1/100 for all regions). (Reference Table 3A.3.2.0.1 PDF [451] CSV [452]; Table 3A.3.2.0.2 PDF [453] CSV [454]; Table 3A.3.2.0.3 PDF [455] CSV [456]; and Table 3A.3.2.0.4 PDF [457] CSV [458])

Economic Burden

Economic costs were not calculated for fibromyalgia.

• 1. Wolfe F, Clauw DJ, Fitzcharles MA, et al. 2016 revisions to the 1010/2011 fibromyalgia diagnostic criteria. Seminars in Arthritis Rheum 2016;46(3):319-329.
• 2. Center for Disease Control. Fibromyalgia.  https://www.cdc.gov/arthritis/basics/fibromyalgia.htm [641] . Accessed September 25, 2017.
• 3. National Fibromyalgia Association. About fibromyalgia. http://www.fmaware.org/about-fibromyalgia/prevalence/ [642]. Accessed September 25, 2017.

Juvenile arthritis (JA) is an umbrella term used to describe a number of autoimmune and inflammatory conditions that can develop in children. It is the most common rheumatic disease of childhood, particularly in the Western world, with children of European descent reporting higher incidence rates.1^,2

The most common form of JA is Juvenile Idiopathic Arthritis (JIA) (formally called juvenile rheumatoid arthritis (JRA) or Juvenile Chronic Arthritis (JCA)). JIA is diagnosed in a child <16 years of age with at least six weeks of persistent arthritis. There are seven distinct subtypes, each having a different presentation and association to autoimmunity and genetics.3 Subtypes also differ in typical age of onset. Certain subtypes are associated with an increased risk of inflammatory eye disease (uveitis).

Understanding the differences in the various forms of JIA, their causes, and methods to better diagnose and treat these conditions in children is important to future treatment and prevention. Among all subtypes, 40% to 45% of children with JIA still have active disease after 10 years.4

Prevalence Of Juvenile Arthritis

Due to the various forms of JA, estimates of prevalence and incidence are difficult to ascertain. Overall estimates are that 294,000 children in the United States have arthritis or another rheumatic disease.5

In 2006, the CDC Arthritis Program finalized a case definition for ongoing surveillance of significant pediatric arthritis and other rheumatologic conditions (SPARC [643]) using the current ICD-9-CM diagnostically based data systems. In response to the variations in conditions that some felt should be included, but were not, CDC generated estimates for conditions that were not included in the case definition but were felt by some should have been.

Healthcare Utilization

Hospitalization for JA

Using the SPARC definitions, analysis of the recent national healthcare database focusing on children, the Healthcare Cost and Utility Project (HCUP) KID, showed 104,400 children age 17 and younger were discharged from a hospital with any diagnosis of SPARC in 2012. Of those, 15,600, or 15%, had an admitting diagnosis of SPARC. Slightly more females than males were hospitalized; children age 6 and younger were more likely to be hospitalized with an admitting diagnosis of SPARC than older children, accounting for 40% of admissions.

Only a small number of children (3.8%) discharged with any diagnosis of SPARC had a diagnosis of juvenile arthritis. Females accounted for 72% of discharges with a diagnosis of JIA, with 62% of the discharges for children age 13 to 17 years.

Average hospital stays of eight days were found for any diagnosis of SPARC. The very youngest children, babies under age one, had much longer stays and higher mean hospital charges. Children with a diagnosis of JIA had hospital stays of a mean of 4.6 days, with subsequently lower mean charges.

Total hospital charges associated with any diagnoses of SPARC in the population younger than age 20 were $8.3 billion in 2012. (Reference Table 3B.1 PDF [644] CSV [645])

JA Ambulatory Care Visits

Emergency rooms saw 515,600 patients ages 0 to 17 with any diagnoses of SPARC in 2013. Among these patients, 6,900 had a primary diagnosis of JIA. Visits did not show major differences by sex or age.

Due to smaller sample sizes in the currently available databases for physician office visits and outpatient clinics, outpatient visits for a diagnosis of SPARC in the juvenile population are difficult to quantify. In 2013, physician visits for treatment of JA numbered 1.2 million. As with ED visits, major differences by sex or age were not seen. Due to small sample sizes, the number of visits with a diagnosis of JIA was unreliable.

Outpatient clinics saw 305,100 patients in 2011, the most recent year for outpatient data available. Patterns for distribution reflected that of other treatment sites. Due to small sample sizes, the number of visits with a diagnosis of JIA was unreliable.

From these data, an estimated 2.03 million outpatient visits for any diagnoses of SPARC occurred in the 0 to 17 years age population in 2013. (Reference Table 3B.1 PDF [644] CSV [645])

 

ICD-9-CM Codes for SPARC    

In 2006, the CDC Arthritis Program finalized a case definition for ongoing surveillance of significant pediatric arthritis and other rheumatologic conditions (SPARC) using the current ICD-9-CM diagnostically-based data systems.

099.3 - Reactive arthritis
136.1 - Behcet's syndrome
274 - Gout
277.3 - Amyloidosis (includes Familial Mediterranean Fever)
287.0 - Allergic purpura / Henoch Schonlein purpura
390 - Rheumatic fever without heart involvement
391 - Rheumatic fever with heart involvement
437.4 - Cerebral arteritis
443.0 - Raynaud's syndrome
446 - Polyarteritis nodosa and allied conditions
447.6 - Arteritis, unspecified
695.2 - Erythema nodosum
696.0 - Psoriatic arthropathy
701.0 - Linear scleroderma / Circumscribed scleroderma / Morphea
710 - Diffuse diseases of connective tissue
711 - Arthropathy associated with infections
712 - Crystal arthropathies
713 - Arthropathy associated with other disorders classified elsewhere
714 - Rheumatoid arthritis and other inflammatory polyarthropathies
715 - Osteoarthritis and allied disorders
716 - Other and unspecified arthropathies
719.2 - Villonodular synovitis
719.3 - Palindromic rheumatism
720 - Ankylosing spondylitis and other inflammatory spondylopathies
727.0 - Tenosynovitis
729.0 - Rheumatism, unspecified and fibrositis
729.1 - Myalgia and myositis, unspecified

 

• 1. Saurenmann RK, Rose JB ,Tyrrell P, et. al. Epidemiology of juvenile idiopathic arthritis in a multiethnic cohort. Arthritis & Rheumatism. 2007;56(6):1974–1984.  DOI 10.1002/art.22709.
• 2. Espinosa M, Gottlieb BS. Juvenile Idiopathic Arthritis. Pediatrics in Review 2012;33:303-13.
• 3. Petty RE, Southwood TR, Manners P, et al. for the International League of Associations for Rheumatology. International League of Associations for Rheumatology classification of juvenile idiopathic arthritis: second revision, Edmonton, 2001. J Rheumatol. 2004 Feb;31(2):390-2.
• 4. Arthritis Foundation (http://www.arthritis.org/arthritis-facts/disease-center/juvenile-arthrit... [650]) November 11, 2014.
• 5. Centers for Disease Control and Prevention (CDC). What is juvenile arthritis?  (https://www.niams.nih.gov/Health_Info/Juv_Arthritis/juvenile_arthritis_f... [651] ) Accessed March 22, 2017.

Joint pain is a major symptom of arthritis and non-arthritis conditions and a primary reason for seeing a medical care provider. Self-report surveys ask about joint pain but do not distinguish the cause of joint pain, which may be from arthritis, injuries, or degeneration of bone surfaces.  

In 2013-2015, chronic joint pain was self-reported in the National Health Interview Survey (NHIS) by 78.9 million adults, among which 40.2 million also reported doctor-diagnosed arthritis (DDA) and 29.1 million reported activity limitations due to arthritis (AAAL). Because the latter two groups are not mutually exclusive, 30.4 million, or about 13% of the total population, have chronic joint pain but no DDA or AAAL. (Reference Table 3A.2.0 PDF [652] CSV [653])

The most common site of chronic joint pain reported by adults with DDA is the knee, reported by nearly 1 in 2 adults. Pain in the shoulder, finger, and/or hip is reported at each site by more than 1 in 4 adults with DDA. While 40% of people with DDA report joint pain in only one site, more than 20% report pain in four or more sites. (Reference Table 3A.2.1.1 PDF [654] CSV [655] and Table 3A.2.1.5 PDF [656] CSV [657])

Among adults with DDA, joint pain occurs in females more frequently than males, and in middle age more frequently than younger or older ages. Joint pain was similar by race/ethnicity and region. (Reference Table 3A.2.1.1 PDF [654] CSV [655]; Table 3A.2.1.2 PDF [658] CSV [659]; Table 3A2.1.3; PDF [660] CSV [661]; and Table 3A.2.1.4 PDF [662] CSV [663])

 

Joint Replacement

While in some sense, the need for a joint replacement represents failure of measures to prevent the occurrence or progression of joint problems, for those with the severe pain or poor function of end-stage joint problems, it can offer a life-altering “cure.” Joint replacements represent one of the fastest growing procedures in the US. Joint replacement procedures for hips and knees are most common, but replacements have been expanding to other joint sites in recent years.

Estimates presented come from the Healthcare Cost and Utility Project (HCUP) Nationwide Inpatient Sample (NIS). In previous editions of BMUS, estimates from the National Hospital Discharge Survey (NHDS) were also presented and are found in two tables showing trends on mean age of joint replacement patients and average length of hospital stay. The NHDS is no longer produced and not otherwise used here.

In 2013, an estimated 1.3 million inpatient joint replacement procedures were performed. Joint replacement procedures comprised about 3.6% of all inpatient procedures. More joint replacements were performed on women than men (60% vs 40%), and 95% of the procedures were performed on knees or hips. (Reference Table 3A.5.1.1 PDF [666] CSV [667])

While joint replacement procedures are being performed on younger patients than in the past, it is still primarily a procedure for older patients. Persons age 65 years and older comprised 14% of the population in 2013 but accounted for 59% of the joint replacement procedures performed; most of the rest were performed among those aged 45 to 64 years. Nearly one in every 60 persons in the 65 years and older population had a joint replacement procedure performed in 2013, although a small number may have had more than one procedure. (Reference Table 3A.5.1.2 PDF [670] CSV [671])  Non-Hispanic whites are more than twice as likely to undergo a joint replacement as those of other racial/ethnic groups. A greater proportion of residents of the Midwest have joint replacements (0.5/100 persons) than residents in other regions of the US. (Reference Table 3A.5.1.3 PDF [672] CSV [673]; and Table 3A.5.1.4 PDF [674] CSV [675])

Knee Replacement Procedures  

In 2013, nearly 723,000 knee replacement procedures were performed in the U.S., comprising 56% of all joint replacement procedures. Over 90% were total knee replacements, but 8% were revision knee replacements, which occur when the original replacement fails or becomes infected. Three in five knee replacements (62%) occurred in females. More than one-half (57%) of knee replacement procedures were performed on those aged 65 years and older, but a substantial proportion (41%) were performed on persons aged 45 to 64 years. The majority (77%) of knee replacements were performed on non-Hispanic whites, with a proportion more than twice that of other racial/ethnic groups. The ratio of knee replacements to total population is higher in the Midwest region (27.2% of replacements vs. 21.4% of population) than other regions, with the Northeast having the lowest ratio of procedures (16.9% vs. 17.7%). (Reference Table 3A.5.1.1 PDF [666] CSV [667]; Table 3A.5.1.2 PDF [670] CSV [671]; Table 3A.5.1.3 PDF [672] CSV [673]; and Table 3A.5.1.4 PDF [674] CSV [675])

Trends in knee replacement procedures from 1992 to 2013 show steady increases in both total and revision knee replacements. Over the 22-year period, knee replacement procedures more than tripled, with the ratio of revisions to total remaining constant at 8% to 10%. (Reference Table 3A.5.2 PDF [676] CSV [677]).

The principal or first diagnosis associated with total knee replacement is osteoarthritis, accounting for 98% of all replacements in 2013. (Reference Table 3A.5.3 PDF [568] CSV [569]).

The 22-year mean age from 1992 to 2013 was nearly 68 years for total knee replacements, and about half a year younger for revision knee replacements. The mean age for both procedures shows a slow decline over time. (Reference Table 3A.5.4 PDF [680] CSV [681])

The average inpatient length of stay for total knee replacements has shown a remarkable decline of about 67% from a mean of nearly 8.9 days in 1992 to a mean of 3.4 days in 2013. (Reference Table 3A.5.5 PDF [682] CSV [683]).

Despite shorter hospital stays, the mean hospital charges from 1998 through 2013 showed a steady increase for all knee replacements, with revision knee replacement being more expensive than total knee replacement. Total hospitalization charges for both types of knee replacements have increased by five times over (in constant 2013 dollars) from $8.4 billion in 1998 to $41.7 billion in 2013. (Reference Table 3A.5.6 PDF [686] CSV [687])

Most adults (72%) with knee replacements are discharged to either short- or long-term care or home health care, likely due to the short hospital stay. Among persons aged 65 and older, a slightly higher proportion are discharged to either short- or long-term care or home health care (77%). (Reference Table 3A.5.7 PDF [690] CSV [691])  

Hip Replacement Procedures

An estimated 493,700 hip replacement procedures were performed in 2013, comprising 39% of all joint replacement procedures. A majority, about 58%, occurred in females. Total hip replacements occurred three times as frequently as partial hip replacements, and both are far more common than revision hip replacement. A very small number of procedures, about 3,700 in 2013, were hip resurfacing, an alternative to replacement, particularly for young, active males. Females have more hip replacement procedures than males, particularly partial replacements. Hip replacements were more common among adults aged 65 years and older (61%), with most of the rest occurring among adults aged 45 to 64 years. Hip replacements by race/ethnicity paralleled that for all joint replacements, as did hip replacements by geographic region. (Reference Table 3A.5.1.1 PDF [666] CSV [667]; Table 3A.5.1.2 PDF [670] CSV [671]; Table 3A.5.1.3 PDF [672] CSV [673]; and Table 3A.5.1.4 PDF [674] CSV [675])

Trends in hip replacement procedures from 1992 to 2013 show total hip replacements increasing in number by 150%, while the number of partial replacements remained relatively stable. The ratio of revision hip to total hip replacements was about 20% from 1992 to 2002, but has consistently been around 17% since then, and dropped to 15% in 2013. (Reference Table 3A.5.2 PDF [676] CSV [677])

The principal or first listed diagnosis associated with total hip replacements was osteoarthritis (87%).   The primary diagnosis for partial hip replacements was fractures (94%). (Reference Table 3A.5.3 PDF [568] CSV [569])

The 22-year mean age was about 66 years for total hip replacements and 77 years for partial hip replacements, reflecting the different underlying diagnoses. Mean ages for both procedures show a slight decline over the time period, reflecting the younger age at which joint replacements are now considered. However, in 2013, the mean age for partial hip replacements jumped to 80. (Reference Table 3A.5.4 PDF [680] CSV [681])  

The mean length of stay for total hip replacements (3.0 days in 2013) showed the same remarkable decline as that for knee replacements--about 67% from 1992 through 2013. The mean lenth- of-stays for partial and revision replacements are longer, with about a 50% decline over the 22-year period. (Reference Table 3A.5.5 PDF [682] CSV [683])

Despite shorter hospital stays, mean hospital charges from 1998 through 2013 steadily increased for all hip replacements even when compared in constant 2013 dollars. Revision hip replacements are the most expensive, while total hip replacements are the least expensive. Total hospital charges for all hip replacements have tripled (in constant 2013 dollars) from $9.25 billion in 1998 to $30.7 billion in 2013, led by charges for total hip replacements. (Reference Table 3A.5.6 PDF [686] CSV [687])

 

Other Joint Replacement Procedures

Shoulder replacement procedures accounted for an estimated 45,000 procedures in 2013, comprising about 4% of all joint replacement procedures. At the same time, an estimated 19,000 other joint replacement procedures were performed for other joints in the upper and lower extremities, and the spine. More than with hip and knee replacements, these other joint replacement procedures occurred somewhat equally between females and males, and were more evenly divided between those aged 44 to 64 and those aged 65 years and older, except for shoulder replacements. Race/ethnicity and geographic regions resembled the distribution of all joint replacements. (Reference Table 3A.5.1.1 PDF [666] CSV [667]; Table 3A.5.1.2 PDF [670] CSV [671]; Table 3A.5.1.3 PDF [672] CSV [673]; and Table 3A.5.1.4 PDF [674] CSV [675])

A recent study released by the CDC Arthritis Workgroup1 reported state-level arthritis prevalence estimates for the first time. Using the 2015 Behavioral Risk Factor Surveillance System (BRFSS) self-reported doctor-diagnosed data, age-adjusted for comparison across states, the median prevalence among adults across the 50 states and District of Columbia was 23.0%. State prevalence ranged from 17.2% in Hawaii to 33.6% in West Virginia. When viewed by states in the four regions used in this report, 75% of states in the South had an age-adjusted prevalence rate above that of the national rate of 23.0%. This compares to 40% in the Northeast, 42% in the Midwest, and 31% in the West. Furthermore, five states in the South (West Virginia, Alabama, Tennessee, Kentucky, and Arkansas) and two in the Midwest (Michigan and Missouri) had a majority of counties with an arthritis prevalence rate in the highest quartile (31.2%-42.7%). A summary of state age-adjusted doctor-diagnosed arthritis prevalence rates can be found by clicking HERE [700].

The study also looked at doctor-diagnosed arthritis prevalence among adults with three comorbid conditions. At 44.5%, prevalence of arthritis was highest among those with coronary heart disease. This was followed by adults with diabetes (37.3%) and obesity (30.9%).

Leisure-time physical inactivity was also analyzed, and the median age-standardized percentage of inactive adults with arthritis was 35.0%. States in the western region tended to have the lowest prevalence of leisure-time physical inactivity with arthritis, while states in Appalachia and along the Ohio and Mississippi Rivers had the highest percentage of leisure-time physical inactivity, following the overall state prevalence rates for arthritis.

Findings from this study showed that estimated prevalence of arthritis varies by geographic area, with correlation to comorbid conditions and negative health-related characteristics. While direct causation cannot be made and further study is needed to understand why these geographic differences occur, the authors have postulated that known risk factors for arthritis such as comorbid conditions, occupation, socioeconomic status, and negative health-related characteristics may contribute. Access to medical care and medications may also be factors.

The full study of arthritis prevalence by state can be found at https://www.cdc.gov/arthritis/data_statistics/state-data-current.htm [701].

The CDC has also produced estimates of arthritis prevalence by race/ethnicity2 based on the NHIS 2013-2015 data. The lowest prevalence rate was found among non-Hispanic Asians (11.8%), with non-Hispanic multi-racial adults having the highest rate (25.2%). Among adults with arthritis, non-Hispanic Asians also reported the lowest prevalence of arthritis-attributable activity limitations (37.6%), while American Indian/Alaska Natives reported the highest prevalence of limitations (51.5%).

 

Access to Care

While medical professionals in many specialities and with a range of credentials treat patients with arthritis, those specializing in rheumatology are often at the frontline. A recently published workforce study by the American College of Rheumatology highlighted significant disparities in access to care within geographic regions of the US. Their findings showed access to care (defined as the ratio of adult rheumatology physicians to adult population) to be easiest in the Northeast (26,677 ratio) and most difficult in the Southern states (66,163 in the Southwest and 60,087 in the Southeast). This compares to a national average of rheumatologists per population of 41,658.3 Comparing this finding to the number of hospitalization and ambulatory healthcare visits, the highest number of visits, or need for care, was in the South. Furthermore, the study cited above reported the highest arthritis prevalence in the South.

In addition to regional differences, access to care based on population size is also the norm, as patients in areas with less than 50,000 population often must travel 200 or more miles to see a rheumatologist. The ratio of pediatric rheumatologists is much higher (229,442 children/physician), and it is estimated that only one-quarter of those aged 18 or younger with juvenile arthritis are currently able to see a rheumatologist.3

 

• 1. Barbour KE, Moss S, Croft JB, et al. Geographic variations in arthritis prevalence, health-related characteristics, and management — United States, 2015. MMWR Surveill Summ 2018;67(No. SS-4):1–28. DOI: http://dx.doi.org/10.15585/mmwr.ss6704a1 [704].
• 2. Barbour KE, Helmick CG, Boring M, Brady TJ. Vital signs: prevalence of doctor-diagnosed arthritis and arthritis-attributable activity limitation — United States, 2013–2015. Morb Mortal Wkly Rep. 2017;66:246–253. DOI: http://dx.doi.org/10.15585/mmwr.mm6609e1 [518].
• 3. a. b. American College of Rheumatology. 2015 Workforce study of rheumatology specialists in the United States. Atlanta, GA. 2015. https://www.rheumatology.org/portals/0/files/ACR-Workforce-Study-2015.pdf [705] Accessed March 26, 2018.

There are many challenges to the management of patients with arthritis that need to be addressed in the future, including, but not limited to, access to specialty care for timely and accurate diagnosis, appropriate use of non-pharmacologic modailities and pharmacotherapy, including targeted small molecule and newer biologic disease modifying anti-rheumatic drugs (DMARDs), adherence to pharmacotherapy, and addressing comorbid medical conditions in patients with various forms of arthritis.

 

Access to Specialty Care

The American College of Rheumatology (ACR) conducted a workforce study in 2015 and noted that the demand for care of patients with arthritis would continue to increase with the aging of the US population.1 Major areas that were identified include the role of primary care providers in the diagnosis and management of common forms of arthritis (eg, osteoarthritis, fibromyalgia, gout) and strategies to improve options for access to rheumatologist specialty care for patients with rheumatoid arthritis, psoriatic arthritis, spondyloarthritides, and systemic autoimmune rheumatic diseases. Training of more mid-level providers (ie, nurse practitioners and physician assistants) and more health professionals (eg, nurses, physical therapists, and occupational therapists) in the care of patients with rheumatic and musculoskeletal diseases would work to address some of this demand.

In addition to issues regarding workforce, there are potential barriers to care including insurance coverage, high co-pays, and limits on number for visits for rehabilitation services such as physical therapy and occupational therapy. Adding to the cost of non-pharmacologic and pharmacologic interventions, especially newer biologic DMARDS, and pharmacy benefit reimbursement plans, are barriers due to high co-pays and prior authorization required for newer pharmacologic interventions.

 

Appropriate Use of Treatment Modalities

Funding of clinical trials to provide best evidence of the efficacy of treatment modalities, including non-pharmacologic interventions is needed. It is extremely important that evidence-based treatments be translated into clinical practice through the use of evidence-based recommendations published by nationally recognized professional societies. Such recommendations exist for the management of most forms of arthritis including, but not limited to, gout, osteoarthritis, rheumatoid arthritis, axial spondyloarthritis (formerly known as ankylosing spondylitis), psoriatic arthritis, and fibromyalgia. These recommendations include the use of both non-pharmacologic and pharmacologic modalities; it is felt to be important to emphasize the role of the former approaches particularly for osteoarthritis and fibromyalgia.

 

Adherence to Treatment Modalities

Virtually all forms of arthritis and systemic autoimmune rheumatic diseases are chronic conditions and effective treatments require patient participation, whether that is taking medications regularly (eg, urate-lowering therapy for gout) or making lifestyle changes such as adhering to dietary changes, a lifelong pattern of physical activity, or using cognitive behavioral therapy or mind-body techniques.

 

Management of Comorbid Medical Conditions

Patients with various forms of arthritis have an increased risk for cardiovascular comorbidities including coronary artery disease. While control of systemic inflammation appears to be important in ameliorating this risk, it is important for practitioners to focus on reducing other factors that contribute to increased cardiovascular disease risk including overweight and obesity, lack of physical activity, smoking, hypertension, hyperlipidemia, and poorly controlled type 2 diabetes mellitus. Depression also has been recognized as contributing to persistent pain, reduced physical function, and impaired quality of life in patients with various forms of arthritis. There is an ongoing need for care coordination between the rheumatology specialist and the primary care provider, particularly in patients who require co-management.

Meeting current and future needs will require a wealth of data currently not available or accessible. In the broad scope of musculoskeletal diseases, data currently either not available or inaccessible to BMUS analysts include treatment cost/benefits, medical workforce, geographic data at detail levels (due to small sample sizes), and outcomes.

In addition, many of the requests for additional data and analysis are beyond the scope of the current BMUS project due to staff size, staff expertise, and funding. 

• 1. American College of Rheumatology. 2015 Workforce study of rheumatology specialists in the United States. Atlanta, GA. 2015. https://www.rheumatology.org/portals/0/files/ACR-Workforce-Study-2015.pdf [705] Accessed March 26, 2018.

Major unmet needs for patients with arthritis include new, effective interventions for the safe treatment of chronic pain, improving insurance coverage for effective evidence-based, non-pharmacologic interventions, as well as newer, targeted small molecules, biologic DMARDs, and the development and approval of Disease Modifying Osteoarthritis Drugs (DMOADs) to slow or prevent progression of osteoarthritis.

Additionally, there is an ongoing need for research funding to understand the pathophysiology of the various forms of arthritis with the goal of estabilishing effective strategies for primary prevention, determining the appropriate timing for surgical intervention and the role of pre- and post-operative exercise programs to maximize functional recovery after surgical interventions, and understanding the underlying reasons for the observed sex/gender and race/ethnicity disparities in most forms of arthritis and systemic autoimmune rheumatic diseases.

Meeting future patient care needs will require increasing the workforce size of medical professionals. The 2015 Workforce Study by the American College of Rheumatology reported an excess demand for adult rheumatology care givers over current workforce projections of nearly 3200 professionals by 2030 and an excess demand of nearly 200 professionals in pediatric rheumatology.1 Other specialists in the care of arthritis likely show similar workforce demands.

• 1. American College of Rheumatology. 2015 Workforce study of rheumatology specialists in the United States. Atlanta, GA. 2015. https://www.rheumatology.org/portals/0/files/ACR-Workforce-Study-2015.pdf [705] Accessed March 26, 2018.

The use of ICD-9-CM codes for clinical and public health purposes ended with the implementation of ICD-10-CM codes effective October 1, 2015. Standard definitions of generic and specific types of arthritis need to be developed for clinical and public health researchers using the new ICD-10-CM codes.

The crosswalk presented HERE [706] is for informational purposes only and should be carefully reviewed before used in future analysis.

 

When reporting the cause of their injury, respondents are asked about six specific causes and an “other” cause. Approximately one-half of respondents reply with the “other” response, which includes accidents around the home and while conducting activities of daily living. In compiling data on the cause of injury, only three categories are used. “Falls” is one of the six specific causes; “vehicle or sports-related” injuries include being in a motor vehicle collision or as a pedestrian hit by a vehicle, accidents while in a boat, train or airplane, and accidents while on a scooter, bike, skateboard, horse, etc. Burns are included in the “other” cause category.

The cause of all injuries reported by male and female individuals is 11% each for vehicle or sports-related injuries. However, women report more falls than men (43% versus 30%) and fewer other causes (46%, 60%). (Reference Table 5A.1.1 PDF [803] CSV [804])

By age, persons age 18 to 44 report higher incidence of vehicle and sport-related injuries (15.6%), while those age 65 and over report only 5% from this cause. However, the 65 and over population reports the highest incidence of falls (58.4%). (Reference Table 5A.1.2 PDF [807] CSV [808])

Using race/ethnicity as the comparison variable, there is less variation between groups with only vehicle or sport-related injuries varying. Black non-Hispanics report vehicle or sport-related injuries as a cause 15.2% of the time while non-Hispanic whites report only 9.7% of injuries caused by vehicle or sport-related causes. (Reference Table 5A.1.3 PDF [809] CSV [810])

Geographic regional areas report only minor differences by cause of injuries, with vehicle and sport-related accidents slightly higher in the South and West regions than in the Northwest and Midwest regions. (Reference Table 5A.1.4 PDF [811] CSV [812])

It has long been known that most injuries occur in or around the home, in part because of the time spent at home versus other locations. In 2013-2015, persons self-reporting injuries reported one-half of the injuries for which they sought medical treatment occurred in the home (32%) or outside the home or farm (17%). Female individuals are more likely to report an injury occurring inside the home than are male individuals (37% versus 22%). Other common places of injuries to occur are public buildings (13%) and public streets (12%). Male individuals report injuries occurring in public buildings more than do female ones (22%, 13% respectively). Age is also a factor in where injuries occur, with 75% of injuries reported by persons age 65 and over occurring in or around the home while those age 18 or younger have more injuries at school (28%) or in a public facility (22%). Race/ethnicity and geographic region are not factors in where injuries occur. (Reference Table 5A.2.1 PDF [823] CSV [824])

The type of activity engaged in does not differ significantly as a cause of musculoskeletal injuries. Sports, non-sport leisure activities, and working in and around the home or workplace are the cause of similar numbers of injuries for which medical care is sought. There are slight differences between male and female individuals, but age is a greater factor, with those age 65 and older reporting working at home (27%) or an “other” activity (42%) while young people under 18 are more likely to be injured during sport activities (41%). Race/ethnicity and geographic region are neither one a factor in the type of activity engaged in when injuries occur. (Reference Table 5A.2.1 PDF [823] CSV [824]; Table 5A.2.2 PDF [827] CSV [828]; Table 5A.2.3 PDF [829] CSV [830]; Table 5A.2.4 PDF [831] CSV [832])