To evaluate the amount of variation in diabetes practice patterns at the primary care provider (PCP), provider group, and facility level, and to examine the reliability of diabetes care profiles constructed using electronic databases.
Clinical and administrative data obtained from the electronic information systems at all facilities in a Department of Veterans Affairs' (VA) integrated service network for a study period of October 1997 through September 1998.
This is a cohort study. The key variables of interest are different types of diabetes quality indicators, including measures of technical process, intermediate outcomes, and resource use.
Data Sources/Study Setting
A coordinated registry of patients with diabetes was constructed by integrating laboratory, pharmacy, utilization, and primary care provider data extracted from the local clinical information system used at all VA medical centers. The study sample consisted of 12,110 patients with diabetes, 258 PCPs, 42 provider groups, and 13 facilities.
There were large differences in the amount of practice variation across levels of care and for different types of diabetes care indicators. The greatest amount of variance tended to be attributable to the facility level. For process measures, such as whether a hemoglobin A1c was measured, the facility and PCP effects were generally comparable. However, for three resource use measures the facility effect was at least six times the size of the PCP effect, and for intermediate outcome indicators, such as hyperlipidemia, facility effects ranged from two to sixty times the size of the PCP level effect. A somewhat larger PCP effect was found (5 percent of the variation) when we examined a “linked” process–outcome measure (linking hyperlipidemia and treatment with statins). When the PCP effect is small (i.e., 2 percent), a panel of two hundred diabetes patients is needed to construct profiles with 80 percent reliability.
Little of the variation in many currently measured diabetes care practices is attributable to PCPs and, unless panel sizes are large, PCP profiling will be inaccurate. If profiling is to improve quality, it may be best to focus on examining facility‐level performance variations and on developing indicators that promote specific, high‐priority clinical actions.
Data Collection/Extraction Methods