Clinical decision support directed to primary care patients and providers reduces cardiovascular risk: a randomized trial.

Objective: To test the hypothesis that use of a clinical decision support (CDS) system in a primary care setting can reduce cardiovascular (CV) risk in patients. Materials and Methods: Twenty primary care clinics were randomly assigned to usual care (UC) or CDS. For CDS clinic patients identified algorithmically with high CV risk, rooming staff were prompted by the electronic health record (EHR) to print CDS that identified evidence-based treatment options for lipid, blood pressure, weight, tobacco, or aspirin management and prioritized them based on potential benefit to the patient. The intention-to-treat analysis included 7914 adults who met high CV risk criteria at an index clinic visit and had at least one post-index visit, accounted for clustering, and assessed impact on predicted annual rate of change in 10-year CV risk over a 14-month period. Results: The CDS was printed at 75% of targeted visits, and providers reported 85% to 98% satisfaction with various aspects of the intervention. Predicted annual rate of change in absolute 10-year CV risk was significantly better in CDS clinics than in UC clinics (-0.59% vs. +1.66%, -2.24%; P < .001), with difference in 10-year CV risk at 12 months post-index favoring the CDS group (UC 24.4%, CDS 22.5%, P < .03). Discussion: Deploying to both patients and providers within primary care visit workflow and limiting CDS display and print burden to two mouse clicks by rooming staff contributed to high CDS use rates and high provider satisfaction. Conclusion: This EHR-integrated, web-based outpatient CDS system significantly improved 10-year CV risk trajectory in targeted adults.

Educating resident physicians using virtual case-based simulation improves diabetes management: a randomized controlled trial.

PURPOSE: To test a virtual case-based Simulated Diabetes Education intervention (SimDE) developed to teach primary care residents how to manage diabetes. METHOD: Nineteen primary care residency programs, with 341 volunteer residents in all postgraduate years (PGY), were randomly assigned to a SimDE intervention group or control group (CG). The Web-based interactive educational intervention used computerized virtual patients who responded to provider actions through programmed simulation models. Eighteen distinct learning cases (L-cases) were assigned to SimDE residents over six months from 2010 to 2011. Impact was assessed using performance on four virtual assessment cases (A-cases), an objective knowledge test, and pre-post changes in self-assessed diabetes knowledge and confidence. Group comparisons were analyzed using generalized linear mixed models, controlling for clustering of residents within residency programs and differences in baseline knowledge. RESULTS: The percentages of residents appropriately achieving A-case composite clinical goals for glucose, blood pressure, and lipids were as follows: A-case 1: SimDE = 21.2%, CG = 1.8%, P = .002; A-case 2: SimDE = 15.7%, CG = 4.7%, P = .02; A-case 3: SimDE = 48.0%, CG = 10.4%, P < .001; and A-case 4: SimDE = 42.1%, CG = 18.7%, P = .004. The mean knowledge score and pre-post changes in self-assessed knowledge and confidence were significantly better for SimDE group than CG participants. CONCLUSIONS: A virtual case-based simulated diabetes education intervention improved diabetes management skills, knowledge, and confidence for primary care residents.

Using simulation technology to teach diabetes care management skills to resident physicians.

BACKGROUND: Simulation is widely used to teach medical procedures. Our goal was to develop and implement an innovative virtual model to teach resident physicians the cognitive skills of type 1 and type 2 diabetes management. METHODS: A diabetes educational activity was developed consisting of (a) a curriculum using 18 explicit virtual cases, (b) a web-based interactive interface, (c) a simulation model to calculate physiologic outcomes of resident actions, and (d) a library of programmed feedback to critique and guide resident actions between virtual encounters. Primary care residents in 10 U.S. residency programs received the educational activity. Satisfaction and changes in knowledge and confidence in managing diabetes were analyzed with mixed quantitative and qualitative methods. RESULTS: Pre- and post-education surveys were completed by 92/142 (65%) of residents. Likert scale (five-point) responses were favorably higher than neutral for general satisfaction (94%), recommending to colleagues (91%), training adequacy (91%), and navigation ease (92%). Finding time to complete cases was difficult for 50% of residents. Mean ratings of knowledge (on a five-point scale) posteducational activity improved by +0.5 (p < .01) for use of all available drug classes, +0.9 (p < .01) for how to start and adjust insulin, +0.8 (p < .01) for interpreting blood glucose values, +0.8 (p < .01) for individualizing treatment goals, and +0.7 (p < .01) for confidence in managing diabetes patients. CONCLUSIONS: A virtual diabetes educational activity to teach cognitive skills to manage diabetes to primary care residents was successfully developed, implemented, and well liked. It significantly improved self-assessed knowledge and confidence in diabetes management.

Cost-effectiveness of an electronic medical record based clinical decision support system.

BACKGROUND AND OBJECTIVE: Medical groups have invested billions of dollars in electronic medical records (EMRs), but few studies have examined the cost-effectiveness of EMR-based clinical decision support (CDS). This study examined the cost-effectiveness of EMR-based CDS for adults with diabetes from the perspective of the health care system. DATA SOURCES/SETTING: Clinical outcome and cost data from a randomized clinical trial of EMR-based CDS were used as inputs into a diabetes simulation model. The simulation cohort included 1,092 patients with diabetes with A1c above goal at baseline. STUDY DESIGN: The United Kingdom Prospective Diabetes Study Outcomes Model, a validated simulation model of diabetes, was used to evaluate remaining life years, quality-adjusted life years (QALYs), and health care costs over patient lifetimes (40-year time horizon) from the health system perspective. PRINCIPAL FINDINGS: Patients in the intervention group had significantly lowered A1c (0.26 percent, p = .014) relative to patients in the control arm. Intervention costs were $120 (SE = 45) per patient in the first year and $76 (SE = 45) per patient in the following years. In the base case analysis, EMR-based CDS increased lifetime QALYs by 0.04 (SE = 0.01) and increased lifetime costs by $112 (SE = 660), resulting in an incremental cost-effectiveness ratio of $3,017 per QALY. The cost-effectiveness of EMR-based CDS persisted in one-way, two-way, and probabilistic sensitivity analyses. CONCLUSIONS: Widespread adoption of sophisticated EMR-based CDS has the potential to modestly improve the quality of care for patients with chronic conditions without substantially increasing costs to the health care system.

Impact of electronic health record clinical decision support on diabetes care: a randomized trial.

PURPOSE: We wanted to assess the impact of an electronic health record-based diabetes clinical decision support system on control of hemoglobin A(1c) (glycated hemoglobin), blood pressure, and low-density lipoprotein (LDL) cholesterol levels in adults with diabetes. METHODS: We conducted a clinic-randomized trial conducted from October 2006 to May 2007 in Minnesota. Included were 11 clinics with 41 consenting primary care physicians and the physicians' 2,556 patients with diabetes. Patients were randomized either to receive or not to receive an electronic health record (EHR)-based clinical decision support system designed to improve care for those patients whose hemoglobin A(1c), blood pressure, or LDL cholesterol levels were higher than goal at any office visit. Analysis used general and generalized linear mixed models with repeated time measurements to accommodate the nested data structure. RESULTS: The intervention group physicians used the EHR-based decision support system at 62.6% of all office visits made by adults with diabetes. The intervention group diabetes patients had significantly better hemoglobin A(1c) (intervention effect -0.26%; 95% confidence interval, -0.06% to -0.47%; P=.01), and better maintenance of systolic blood pressure control (80.2% vs 75.1%, P=.03) and borderline better maintenance of diastolic blood pressure control (85.6% vs 81.7%, P =.07), but not improved low-density lipoprotein cholesterol levels (P = .62) than patients of physicians randomized to the control arm of the study. Among intervention group physicians, 94% were satisfied or very satisfied with the intervention, and moderate use of the support system persisted for more than 1 year after feedback and incentives to encourage its use were discontinued. CONCLUSIONS: EHR-based diabetes clinical decision support significantly improved glucose control and some aspects of blood pressure control in adults with type 2 diabetes.