Continuity Clinic Model and Diabetic Outcomes in Internal Medicine Residencies: Findings of the Educational Innovations Project Ambulatory Collaborative

Maureen D. Francis, Katherine A. Julian, David A. Wininger, Sean Drake, Keri Lyn Bollman, Christopher Nabors, Anne Pereira, Michael Rosenblum, Amy B. Zelenski, David Sweet, Kris Thomas, Andrew Varney, Eric Warm, Mark L. Francis

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

RESULTS: No significant differences were found in glycemic control across clinic models (P = .06). The percentage of diabetic patients with LDL < 100 mg/dL was 60% in block, compared to 54.9% and 55% in traditional and combination models (P = .006). The percentage of diabetic patients with blood pressure < 130/80 mmHg was 48.4% in block, compared to 36.7% and 36.9% in other models (P < .001). The percentage of diabetic patients with HbA1C measured was 92.1% in block compared to 75.2% and 82.1% in other models (P < .001). Also, the percentage of diabetic patients with LDL measured was significantly different across all groups, with 91.2% in traditional, 70.4% in combination, and 83.3% in block model programs (P < .001).

CONCLUSIONS: While high scores on diabetic quality measures are achievable in any clinic model, the block model design was associated with better performance.

BACKGROUND: Efforts to improve diabetes care in residency programs are ongoing and in the midst of continuity clinic redesign at many institutions. While there appears to be a link between resident continuity and improvement in glycemic control for diabetic patients, it is uncertain whether clinic structure affects quality measures and patient outcomes.

METHODS: This multi-institutional, cross-sectional study included 12 internal medicine programs. Three outcomes (glycemic control, blood pressure control, and achievement of target low-density lipoprotein [LDL]) and 2 process measures (A1C and LDL measurement) were reported for diabetic patients. Traditional, block, and combination clinic models were compared using analysis of covariance (ANCOVA). Analysis was adjusted for continuity, utilization, workload, and panel size.

Original languageEnglish (US)
Pages (from-to)27-32
Number of pages6
JournalJournal of graduate medical education
Volume8
Issue number1
DOIs
StatePublished - Feb 1 2016

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