Roy E Furman1, Timothy S Harlan2, Lesley LeBlanc3, Elise C Furman1, Greg Liptak4, Vivian A Fonseca2. 1. American Diabetes Association, Bala Cynwyd, PA rfurman@diabetes.org. 2. Tulane University School of Medicine, New Orleans, LA. 3. Tulane University Medical Group, New Orleans, LA. 4. American Diabetes Association, Bala Cynwyd, PA.
Abstract
OBJECTIVE: To improve outcomes of patients with adult type 2 diabetes by decreasing HbA1c undertesting, reducing the proportion of patients with poor glycemic control, and lowering mean HbA1c levels using a quality improvement (QI) program. RESEARCH DESIGN AND METHODS: Six years of outpatient electronic health record (EHR) data were analyzed for care gaps before and 2 years after implementing a QI initiative in an urban academic medical center. QI strategies included 1) individual provider and departmental outcome reports, 2) patient outreach programs to address timely follow-up care, 3) a patient awareness campaign to improve understanding of achieving clinical goals, 4) improving EHR data capture to improve population monitoring, and 5) professional education. RESULTS: Analysis (January 2010 to May 2018) of 7,798 patients from Tulane Medical Center (mean age 61 years, 57% female, 62% black, 97% insured) with 136,004 visits showed target improvements. A Cox proportional hazards model controlling for age, sex, race, and HbA1c level showed a statistically significant reduction in HbA1c undertesting >6 months (hazard ratio 1.20 ± 0.07). Statistical process control charts showed 15.5% relative improvement in the patient proportion with HbA1c >9% (75 mmol/mol) from 13% to 11% (P < 10-6) following QI interventions and a 2.1% improvement of population mean HbA1c from 7.4% (57 mmol/mol) to 7.2% (55 mmol/mol) (P < 10-6). CONCLUSIONS: Multidisciplinary QI teams using EHR data to design interventions for providers and patients produced statistically significant improvements in both care process and clinical outcome goals.
OBJECTIVE: To improve outcomes of patients with adult type 2 diabetes by decreasing HbA1c undertesting, reducing the proportion of patients with poor glycemic control, and lowering mean HbA1c levels using a quality improvement (QI) program. RESEARCH DESIGN AND METHODS: Six years of outpatient electronic health record (EHR) data were analyzed for care gaps before and 2 years after implementing a QI initiative in an urban academic medical center. QI strategies included 1) individual provider and departmental outcome reports, 2) patient outreach programs to address timely follow-up care, 3) a patient awareness campaign to improve understanding of achieving clinical goals, 4) improving EHR data capture to improve population monitoring, and 5) professional education. RESULTS: Analysis (January 2010 to May 2018) of 7,798 patients from Tulane Medical Center (mean age 61 years, 57% female, 62% black, 97% insured) with 136,004 visits showed target improvements. A Cox proportional hazards model controlling for age, sex, race, and HbA1c level showed a statistically significant reduction in HbA1c undertesting >6 months (hazard ratio 1.20 ± 0.07). Statistical process control charts showed 15.5% relative improvement in the patient proportion with HbA1c >9% (75 mmol/mol) from 13% to 11% (P < 10-6) following QI interventions and a 2.1% improvement of population mean HbA1c from 7.4% (57 mmol/mol) to 7.2% (55 mmol/mol) (P < 10-6). CONCLUSIONS: Multidisciplinary QI teams using EHR data to design interventions for providers and patients produced statistically significant improvements in both care process and clinical outcome goals.