Evaluation of a Diabetes Screening Clinical Decision Support Tool
Eva Tseng, MD, MPH,
Ariella Stein, MPH,
Nae-Yuh Wang, PhD,
Nestoras N. Mathioudakis, MD, MHS,
Hsin-Chieh Yeh, PhD,
Nisa M. Maruthur, MD, MHS
Affiliations
Eva Tseng, MD, MPH
Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland; Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland; Address correspondence to: Eva Tseng, MD, MPH, Division of General Internal Medicine, Johns Hopkins University School of Medicine, 2024 East Monument Street, Room 2-601, Baltimore MD 21205.
Ariella Stein, MPH
Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
Nae-Yuh Wang, PhD
Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland; Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland; Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland; Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland
Nestoras N. Mathioudakis, MD, MHS
Division of Endocrinology, Diabetes & Metabolism, Johns Hopkins University School of Medicine, Baltimore, Maryland; Division of Biomedical Informatics & Data Science, Johns Hopkins University School of Medicine, Baltimore, Maryland
Hsin-Chieh Yeh, PhD
Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland; Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland; Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland
Nisa M. Maruthur, MD, MHS
Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland; Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland; Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland
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, p<0.001; test completion: OR=2.1; 95% CI=2.0, 2.3, p<0.001). In the interrupted time series analysis, laboratory order and completion rates increased significantly from the baseline period (p<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.
