Evaluation of a Diabetes Screening Clinical Decision Support Tool.

Introduction: The authors evaluated whether an electronic health record clinical decision support system improves diabetes screening across a health system.

Methods: Study population included adults without diabetes attending a visit at 27 primary care clinics. Outcomes included the monthly screening laboratory order rate and completion rate among eligible patient visits. The authors performed logistic regression using a generalized estimating equations model and interrupted time series analysis to evaluate the change in the outcome from baseline to implementation and postimplementation periods.

Results: From the baseline to postimplementation period, screening laboratory order rates increased from 53% to 66%, and completion rates increased from 46% to 54%, respectively. The odds of laboratory order and completion increased significantly from the baseline to postimplementation period (test order: OR=3.7; 95% CI=3.4, 4.1, <0.001; test completion: OR=2.1; 95% CI=2.0, 2.3, <0.001). In the interrupted time series analysis, laboratory order and completion rates increased significantly from the baseline period (<0.001 for both).

Conclusions: The authors developed and implemented a clinical decision support system alert that automatically identifies eligible patients and facilitates single-click ordering of a diabetes screening test. An easily implementable and scalable clinical decision support system alert can improve diabetes screening.