A Report on Programming a Clinical Decision Support Algorithm to Capture Inappropriate Complete Blood Count and Basic Metabolic Panel Lab Orders Using Arden Syntax, a Formalism for Medical Logic Modules
2019-10
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A Report on Programming a Clinical Decision Support Algorithm to Capture Inappropriate Complete Blood Count and Basic Metabolic Panel Lab Orders Using Arden Syntax, a Formalism for Medical Logic Modules
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2019-10
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This project is the second phase of research on Minnesota Laboratory Appropriateness (MLAB) Criteria that focuses on developing medical logic for the clinical decision support system that can be adapted to a wide variety of electronic health record (EHR) systems. Of all the wasteful spending on healthcare in the United States one third of the wasteful spending and overtreatment includes laboratory test utilization. Research findings indicate that up to four billion labs of the seven to ten billion lab tests ordered annually are inappropriate.3,4 To address this area of overutilization, guidelines for laboratory tests to identify appropriate and inappropriate utilization for complete blood count (CBC) and Basic Metabolic Panel (BMP) lab orders in an inpatient setting were developed by Dr. Caleb Murphy and his research team in phase one of this study. The recommendations for MLAB criteria were based on Choosing Wisely initiative (26,27). Though there are many studies reported on lab overutilization, to our knowledge, no prior studies have developed or programmed a clinical decision support system (CDSS) embedded into the EHR to monitor and correct the rates of inappropriate CBC and BMP screening in an inpatient setting (1). To facilitate the detection of imprudent lab orders for the aforementioned tests, the Arden Syntax, a formalism for representation of procedural medical knowledge, is used to facilitate knowledge transfer (2). The unit of representation in the Arden Syntax is the Medical Logic Module (MLM), which contains enough data and logic to make a single medical decision.
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University of Minnesota M.S. thesis. October 2019. Major: Health Informatics. Advisor: Terrence Adam. 1 computer file (PDF); iii, 41 pages
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Gunashekar, Divya Rupini. (2019). A Report on Programming a Clinical Decision Support Algorithm to Capture Inappropriate Complete Blood Count and Basic Metabolic Panel Lab Orders Using Arden Syntax, a Formalism for Medical Logic Modules. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/211310.
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