Measuring the quality of XXXX care using administrative data: is there bias?

@entity1 @entity165 @entity6 @entity989
OBJECTIVES: Health care organizations often measure processes of care using only administrative data. We assessed whether measuring processes of @entity6 care using administrative data without medical record data is likely to underdetect compliance with accepted standards for certain groups of @entity1 . DATA SOURCES/STUDY SETTING: Assessment of quality indicators during 1998 using administrative and medical records data for a cohort of 1,335 @entity6 @entity1 enrolled in three Minnesota health plans. STUDY DESIGN: Cross-sectional retrospective study assessing hemoglobin A1c testing, LDL @entity165 testing, and @entity989 screening from the two data sources. Analyses examined whether @entity1 or clinic characteristics were associated with underdetection of quality indicators when administrative data were not supplemented with medical record data. DATA COLLECTION/EXTRACTION METHODS: The health plans provided administrative data, and trained abstractors collected medical records data. PRINCIPAL FINDINGS: Quality indicators that would be identified if administrative data were supplemented with medical records data are often not identified using administrative data alone. In adjusted analyses, older @entity1 were more likely to have hemoglobin A1c testing underdetected in administrative data (compared to @entity1 <45 years, OR 2.95, 95 percent CI 1.09 to 7.96 for @entity1 65 to 74 years, and OR 4.20, 95 percent CI 1.81 to 9.77 for @entity1 75 years and older). Black @entity1 were more likely than white @entity1 to have @entity989 screening underdetected using administrative data (2.57, 95 percent CI 1.16 to 5.70). @entity1 in different health plans also differed in the likelihood of having quality indicators underdetected. CONCLUSIONS: @entity6 quality indicators may be underdetected more frequently for elderly and black @entity1 and the physicians, clinics, and plans who care for such @entity1 when quality measurement is based on administrative data alone. This suggests that providers who care for such @entity1 may be disproportionately affected by public release of such data or by its use in determining the magnitude of financial incentives.
