This study examined health care utilization patterns among knee OA patients in a national population sample. We found that knee OA patients had significantly more adjusted mean MD and non-MD visits than OA-free patients. This excess usage (6.0 visits to physicians and 3.8 visits to nonphysician providers) is attributable to knee OA, independent of the effects of comorbidity, obesity, functional status, and other patient characteristics.
After controlling for comorbidity, we did not find that knee OA contributed to excess utilization of ED resources, but we found that knee OA patients were about 30% more likely to have a hospital stay than OA-free subjects. Since this association was not found in sensitivity analyses, which excluded patients who had a lower extremity joint replacement during the study year, it appears that the increase in hospital stays in knee OA patients may be attributed to joint replacement surgeries. Yelin and Felts32
found that among patients with OA, the rate of hospitalization is 50% more for persons with at least one more comorbid condition and that more than 91% of the hospitalizations in those with OA occurred among those with at least one additional comorbidity. Thus, the higher rates of inpatient utilization previously reported for OA patients24
are probably due in part to comorbid conditions.
Whereas previous research has documented significant utilization among OA patients, this study is the first to our knowledge to examine utilization attributable to knee OA in a national population sample. Nationally representative data are critical for projecting accurate estimates of utilization for the US population and informing health care policy.
Most prior studies on utilization and/or cost in OA have studied European populations,18–21
a state-wide Medicare program,22
and VA populations.25
However, there are 2 studies of OA in national population samples that report findings on ambulatory utilization consistent with ours.33,34
Kramer et al found that OA patients had 10.9 physician visits on average in 1 year compared with 6.5 for the general population, or an excess of 4.4 MD visits for OA patients.33
This observation compares well with the 6.0 excess annual MD visits by knee OA patients observed in the present study.
In addition to general changes in health care from 1989 to 2003, distinctive findings in our study may reflect our focus on knee OA rather than OA of any joint, as in Kramer et al.33
Prior studies examining OA without reference to joint may have introduced heterogeneity in estimation of health care utilization. For example, utilization for hand and knee OA may differ because of differences in treatment protocols and disability consequences of upper extremity and lower extremity OA.
Whereas previous studies have documented significant outpatient utilization by OA patients, the question remains whether this increased utilization is due to OA specifically or to potentially confounding factors, such as comorbidity, functional limitation, and obesity.9,10
Dunlop et al address this question in the context of arthritis and rheumatic conditions generally.26
Their study observed increased outpatient utilization by arthritis patients as compared with nonarthritic controls after controlling for demographics and comorbid conditions.
The present study adds to the literature by addressing the question of health care utilization attributable to knee OA. Similar to the work of Dunlop et al performed in arthritis of diverse etiologies, we observed an independent effect of knee OA on ambulatory utilization. Our findings demonstrate that although persons with knee OA are more likely to have concomitant comorbidities and to be obese, the excess ambulatory health service utilization is not confounded by these factors. The increased utilization of MD and non-MD visits observed in the knee OA cohort persisted after controlling for comorbidity, obesity, functional limitation, and demographic characteristics and on stratification by sex, comorbidity, obesity, and education.
The present study has important differences from the work of Dunlop et al.26
Our study used Medicare billing data rather than patient self-report questionnaires and interviews. Medicare data files, with codes for diagnosis, procedure, and provider type, allow more certainty about diagnoses and utilization and eliminate the risk of reporting bias. Also, our focus on knee OA reduces the heterogeneity inherent in a general arthritis outcome. In contrast to Dunlop et al, we were able to quantify resource utilization, allowing us to assess the magnitude of the effect of knee OA on health care utilization. Whereas studies in primary care settings systematically exclude patients who visit orthopedists or other specialists directly,18,20
our study uses survey data that includes such patients, irrespective of provider type. Furthermore, the components of utilization we measured represent a comprehensive overview of medical resources.
The knee OA and OA-free cohorts reported in this manuscript consist of those seeking care, which leads to an undercounting of mild disease. This may account for the lower prevalence of knee OA found in this study compared with that reported in national surveys. We examined several strategies for increasing sensitivity, but all required compromise in specificity and, therefore, in positive predictive value of the algorithm for identifying knee OA cases. The trade-off between sensitivity and specificity of claims-based algorithms is well described.35
We chose to optimize specificity over sensitivity to maximize correct classification in both knee OA and OA-free cohorts. Because of substantial discordance between survey and claims data, we were unable to incorporate survey responses into the knee OA case definition; the reliance on claims likely led to a sample with more severe OA because a claim implies seeking medical attention for the problem.
Whereas the use of Medicare insurance claims brings certain strengths, these data source also has limitations. The analysis did not include aspects of utilization not reimbursed by Medicare, such as routine physical examinations, screening tests, and alternative therapies. Our utilization estimates may be low, as suggested by Harrold et al,36
who found that the use of data with OA diagnosis validated by medical chart review leads to substantially higher estimates of health utilization by OA patients. Furthermore, we examined all visits for knee OA patients and did not distinguish between OA-related and unrelated utilization. Consequently, some medical care may have been for comorbid conditions causally unrelated to OA. Although we recognize that knee OA can be a prominent disabling condition in younger ages, the nature of the data we used for the current analysis (Medicare claims) limits generalizability of our findings to populations with knee OA aged ≥65. Reason for the visit could offer important additional insights into health care utilization patterns among persons with knee OA, but this information was not available in Medicare claims. Our analysis focused on comparing health care utilization in a knee OA cohort with the OA-free population. Comparing different OA sites (eg, hands vs. hips vs. knees) was outside the scope of this article.
This first national, population-based study of health care utilization in knee OA documents considerable ambulatory usage attributable to knee OA, independent of the effects of comorbidity, functional limitation, obesity, and patient demographic characteristics. Furthermore, our results suggest that the additional inpatient health resource utilization previously reported as due to knee OA can be attributed to the number of comorbidities rather than knee OA per se, except in the case of hospital stays for joint replacement surgery. Nationally representative utilization data are critical for informing health care policy, particularly in the allocation of limited funds in the current environment of rising health care costs. Our finding of 9.8 excess ambulatory (MD and non-MD) visits per year attributable to knee OA suggests that OA treatment and prevention innovations represent opportunities to reduce a significant burden on the US health care system.