DII 99-205
Developing and Implementing a Quality Measure for Glycemic Control
Dan R. Berlowitz, MD MPH VA Bedford HealthCare System, Bedford, MA Bedford, MA Funding Period: July 1999 - December 2003 Portfolio Assignment: Research Methods Development |
BACKGROUND/RATIONALE:
Many patients with diabetes are under sub-optimal glycemic control. Central to the clinician’s task in improving glycemic control is the management of hypoglycemic medication therapy, including the use of drugs such as insulin and sulfonylureas. Clinical trials have demonstrated that more intensive hypoglycemic medication therapy results in improved glycemic control. Yet quality measures for this critical process of care have not been developed and we know little about how physicians actually manage hypoglycemic medications. OBJECTIVE(S): We propose to develop a quality measure that describes the intensity of physicians’ hypoglycemic medication therapy. We will then provide feedback to VA physicians regarding their practices and access to experts in diabetes care to determine whether this intervention leads to improvements in glycemic control. METHODS: The study was divided into two phases. During the first phase we used existing data to model the decision to increase hypoglycemic medications. At each medical visit, we determined whether an increase in medication therapy occurred. We then used recursive partitioning to develop a model that identified patient characteristics at the visit, such as recent laboratory results and diagnoses, associated with the decision to increase therapy. This model assigns a predicted probability of an increase in therapy to each visit. We used these predictions to define an intensity of hypoglycemic medication therapy for each physician that compared the actual to predicted number of increases over all patient-visits. The second phase was a randomized trial in which clinicians at experimental sites receive feedback on performance and access to expert opinion while usual care is provided at control sites. Feedback on performance was provided twice over 6 months. The change in intensity of treatment scores and glycosylated hemoglobin levels pre- and post-intervention at these sites were compared to performance of primary care physicians at control sites not receiving the intervention. FINDINGS/RESULTS: Newer medical regimes for the treatment of diabetes are being adopted. A model identifying predictors of an increase in hypoglycemic medications has been developed. Among the important predictors are most recent glycosylated hemoglobin level, most recent blood glucose, time since last visit, whether on insulin, and recency of last glycosylated hemoglobin level. Visit-predicted probabilities of an increase varied from 1.5 to 32.0%. Patient treatment intensity scores varied considerably and those patients receiving more intensive therapy had a greater decrease in glycosylated hemoglobin levels over time. Clinician specific profiles containing information on glycemic control and intensity of therapy were disseminated at intervention sites. Considerable differences have been noted in clinician performance. At the provider level, intensity of therapy was weakly correlated with glycemic control and future intensity of therapy. While reports led to an increase in glycosylated hemoglobin testing, there were no increases in intensity of therapy or glycemic control. IMPACT: We have now demonstrated that intensity of therapy can be measured and that this process measure can be linked to the outcome of glycemic control. Clinicians vary in the intensity of their therapy. Further understanding is required as to how clinicians’ practices in the management of medications may be improved. External Links for this ProjectDimensions for VA![]() Learn more about Dimensions for VA. VA staff not currently on the VA network can access Dimensions by registering for an account using their VA email address. Search Dimensions for this project PUBLICATIONS:Journal Articles
DRA:
Health Systems Science
DRE: Technology Development and Assessment Keywords: Behavior (provider), Diabetes, Quality assessment MeSH Terms: Diabetes Mellitus, Outcome and Process Assessment (Health Care), Quality of Health Care |