Performance status of health care facilities changes with risk adjustment of HbA(1c)

Quanwu Zhang, Monika Safford, John Ottenweller, Gerald Hawley, Denis Repke, James F. Burgess, Sunil Dhar, Hsiaofen Cheng, Herbert Natto, Leonard M. Pogach

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

OBJECTIVE - To develop a risk adjustment method for HbA(1c) based solely on administrative data and to determine the extent to which risk-adjusted HbA(1c) changes the identification of high- or low-performing medical facilities. RESEARCH DESIGN AND METHODS - Through use of pharmacy records, 204,472 diabetic patients were identified for federal fiscal year 1996 (FY96). Complete information (HbA(1c) levels, demographic data, inpatient records, outpatient pharmacy utilization records) was available on 38,173 predominantly male patients from 48 Veterans Health Administration (VHA) medical facilities. Hierarchical mixed-effects models were used to estimate risk-adjusted unique facility-level HbA(1c). RESULTS - Predicted HbA(1c) demonstrated expected patterns for major factors known to influence glycemic control. Poorer glycemic control was seen in minorities and patients with greater disease severity, longer duration of disease (using treatment type or presence of amputation as surrogates), and more extensive comorbidity (measured by an adapted Charlson index). Better glycemic control was seen in Caucasians, older diabetic patients, and patients with higher outpatient utilization. The number of performance outliers was reduced as a result of risk adjustment. For mean HbA(1c) levels, 7 facilities that were initially identified as statistically significant outliers were no longer outliers after risk adjustment. For high-risk HbA(1c) (>9.5%) rates, 12 facilities that were initially identified as statistically significant outliers were no longer outliers after risk adjustment. CONCLUSIONS - Risk adjustment using only administrative data resulted in substantial changes in identification of high or low performers compared with non-risk-adjusted HbA(1c). Although our findings are exploratory, risk adjustment using administrative data may be a necessary and achievable step in quality assessment of diabetes care measured by rates of high-risk HbA(1c) (>9.5%).

Original languageEnglish (US)
Pages (from-to)919-927
Number of pages9
JournalDiabetes Care
Volume23
Issue number7
DOIs
StatePublished - 2000

All Science Journal Classification (ASJC) codes

  • Internal Medicine
  • Endocrinology, Diabetes and Metabolism
  • Advanced and Specialized Nursing

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