Obesity and its health sequelae are increasingly serious concerns in the Veterans Affairs Healthcare System, where it is estimated that 1 in 3 patients is obese and more than 2 in 3 are overweight. While disparities by race are well-documented for many aspects of healthcare, there are strong reasons to believe that similar mechanisms - relating to patient and physician factors - may also lead to differential care by weight status. In contrast to prior work, we examined quality measures that are: 1) objectively measured via chart abstraction (rather than self-reported), 2) relevant to both men and women, and 3) drawn from a nationally-based sample.
We examined weight status disparities in quality of care by using a rich array of clinical data obtained from detailed chart abstraction by professional reviewers. First, we examined the influence of patient weight status on quality of care using a broad array of process-based measures. We hypothesized that those who are obese receive lower quality of care relative to normal weight patients. Process measures included diabetes care, cancer screening, and other measures of care quality. Second, we examined how patient race/ethnicity moderates the relationship between weight status and quality of care. Third, we examined how patient medical complexity influences the relationship between weight status and quality of care. Obese patients may have more complicated overall care. Though we use process-based measures of quality that are not contingent on patient comorbidities, such complexity may distract providers from complying with recommended care, particularly preventive care. Fourth, we examined the role of provider-patient communication quality and patient satisfaction in the relationship between weight status and quality of clinical care.
We cross-linked VHA data from three different national sources: (1) the Performance Measurement System and External Peer Review Program (EPRP); (2) the Survey of Healthcare Experiences of Patients (SHEP); and (3) VHA administrative claims data. The EPRP data provide information on quality of care delivered within the VHA as well as measured weight status. These data are based on chart abstraction and are routinely collected by the VHA to measure and monitor quality of care nationwide. We use process-based quality measures that focus on clinicians' actions and specified populations of patients for whom specific actions were indicated over a certain time interval by established guidelines. The SHEP data are a survey of veterans' health care experiences that contain sociodemographic variables not available in EPRP data (e.g., income, education, and self-reported race/ethnicity), and data on communication quality and patient satisfaction. VHA administrative data were used to construct measures of clinical complexity and visit frequency. Clinical complexity was measured by using the Diagnostic Cost Groups-Hierarchical Condition categories (DCG-HCC) system to summarize patients' medical problems. We used VHA data from fiscal years 2003 and 2004, which are years when individuals in the EPRP sample were also administered the SHEP. The overall sample eligible for at least one quality measure was 33,550.
We examined the association between quality of care and weight status using logistic regression models with receipt of the measured care process as the dependent variable and weight status categories (underweight, overweight, normal, and obese) as primary independent variables of interest. Each process measure was examined with a separate model, and all models adjusted for sociodemographics, clinical complexity, and visit frequency. In addition, patient race/ethnicity, clinical complexity, provider-patient communication quality, and patient satisfaction were examined for mediating and/or moderating effects on the relationship between quality of care and weight status. Analyses included a random effect to account for clustering within 21 geographically-based VHA service networks.
We found no evidence across eight different performance measures for outpatient preventive services that obese or overweight patients are getting lower quality of care. To the contrary, obese and overweight patients are slightly more likely to get recommended care on several measures. Performance measures included: diabetes care (eye exam, lipid screening, and HbA1c testing), pneumococcal vaccination, influenza vaccination, colorectal cancer screening, mammography, and Pap smear. Obese patients had significantly higher odds of success relative to normal weight patients on lipid screening, HbA1c testing, and both vaccinations. Neither race nor sex modified these associations in any meaningful fashion. Additionally, patient clinical complexity, patient-provider communication quality, and patient satisfaction were not found to have a substantive or meaningful role in mediating the relationship between quality of care and weight status.
Prior studies show that clinicians openly admit to negative attitudes toward obese patients, and that many express dissatisfaction in caring for obese patients. Moreover, these findings generally concur with patient perceptions. Prior studies show that obese patients often feel that clinicians are biased or disrespectful because of their weight. These observations have raised the concern that obese patients may receive lower quality of care. We found no evidence that obese patients were less likely to receive recommended care relative to normal-weight patients across multiple, commonly-used measures of outpatient care quality, and success rates were often marginally higher for obese patients. While it may be true that providers often harbor negative attitudes towards obesity, our study indicates that these biases are not borne out in lower quality of care. Furthermore, the finding of higher success rates among obese patients suggests that physicians may actually be more aggressive in caring for obese patients in risk factor modification, perhaps because they are viewed as being at higher risk for adverse outcomes. This offers preliminary insight and one potential explanation for why the gap between obesity and normal-weight persons has been observed to narrow over recent decades at the population-level for mortality and cardiovascular risk factors (e.g., cholesterol).
Although our findings did not support our a priori hypothesis and expectation that obese patients would receive lower quality of care relative to normal weight patients, it is important to note that the mean age in our sample was 68.4 with a range of 60-77. Hence, these findings may not be generalizable to quality of care in younger populations where the stigma and stereotypes associated with obesity may be more salient. For older patients, however, our conclusions are strengthened by the fact that we found highly similar results (and consistent conclusions) for the same measures of care among a nationally representative sample of Medicare patients.
- Chang VW, Asch DA, Werner RM. Quality of care among obese patients. JAMA : the journal of the American Medical Association. 2010 Apr 7; 303(13):1274-81.
- Chang VW, Asch DA, Werner RM. Study Shows Obese and Overweight Patients Receive Equal or Better Care than Patients of Normal Weight. 2010 Apr 1.
- Chang VW. Risk of Death and Quality of Medical Care Associated with Obesity. Paper presented at: Columbia University Center for the Study of Wealth and Inequality Seminar Series; 2010 Apr 1; New York, NY.
- Chang VW. Quality of care among obese patients in the US. Paper presented at: RWJ Foundation Physician Faculty Scholars Program National Meeting; 2009 Dec 11; San Diego, CA.
- Chang VW. Obesity and Quality of Care: Implications for Disability and Mortality. Paper presented at: National Institute of Environmental Health Sciences Disability Advocacy Committee Meeting; 2009 Sep 1; Research Triangle Park, NC.