1. The role of a best practice alert in the electronic medical record in reducing repetitive lab tests
- Author
-
Bejjanki H, Mramba LK, Beal SG, Radhakrishnan N, Bishnoi R, Shah C, Agrawal N, Harris N, Leverence R, and Rand K
- Subjects
Laboratory ,testing ,healthcare ,costs ,Medicine (General) ,R5-920 ,Therapeutics. Pharmacology ,RM1-950 - Abstract
Harini Bejjanki,1 Lazarus K Mramba,2 Stacy G Beal,3 Nila Radhakrishnan,1 Rohit Bishnoi,1 Chintan Shah,1 Nikhil Agrawal,4 Neil Harris,3 Robert Leverence,1 Kenneth Rand3 1Division of Hospital Medicine, Department of Medicine, University of Florida, Gainesville, FL, USA; 2Statistics, Department of Internal Medicine, University of Florida, Gainesville, FL, USA; 3Department of Pathology, Immunology, & Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL, USA; 4Department of Nephrology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA Background: The recommendations of the American Board of Internal Medicine Foundation’s “Choosing Wisely®” initiative recognize the importance of improving the appropriateness of testing behavior and reducing the number of duplicate laboratory tests.Objective: To assess the effectiveness of an electronic medical record Best Practice Alert (BPA or “pop up”) intervention aimed at reducing duplicate laboratory tests and hospital costs.Design: Comparison of the number of duplicated laboratory tests performed on inpatients before and after the intervention.Setting: University of Florida Health Shands Hospital, Gainesville, FL, USA, during 2014–2017.Intervention: The electronic medical record intervention was a BPA pop-up alert that informed the ordering physician if a recent identical order already existed along with the “ordering time”, “collecting time”, “resulting time”, and the result itself.Main outcome measures: Percentage change in the number of inpatient duplicate orders of selected clinical biochemistry tests and cost savings from reduction of the duplicates. Student’s t-test and beta-binomial models were used to analyze the data.Results: Results from the beta-binomial model indicated that the intervention reduced the overall duplicates by 18% (OR=0.82, standard error=0.016, P-value
- Published
- 2018