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Design Features of Successful Outpatient Chronic Disease Care Clinical Decision Support Systems
Background/Aims: To identify key design features of point-of-care diabetes clinical decision support (CDS) that have high use rates and high provider satisfaction rates, and that have improved control of major cardiovascular risk factors. Methods: Based on a series of National Institutes of Health-f...
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Published in: | Journal of Patient-Centered Research and Reviews 2016-08, Vol.3 (3), p.190 |
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Main Authors: | , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Online Access: | Get full text |
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Summary: | Background/Aims: To identify key design features of point-of-care diabetes clinical decision support (CDS) that have high use rates and high provider satisfaction rates, and that have improved control of major cardiovascular risk factors.
Methods: Based on a series of National Institutes of Health-funded projects to develop point-of-care electronic health record-linked, web-based CDS systems, we have identified design features that contribute to observed high use rates (6080%) at targeted visits, high primary care provider satisfaction rates (9495%) and positive effects on glucose and blood pressure control in adults with diabetes.
Results: The ideal outpatient chronic disease care CDS system would include the following features: a) co-designed by primary care physicians (PCPs) and researchers, b) supported by clinic and medical group leaders, c) designed to improve publicly reported quality measures, d) introspective identification of targeted encounters, e) total target encounters limited to about 20% of all adult visits, f) rooming nurse launches CDS early in encounter workflow, g) PCP sees CDS early in workflow and uses for visit planning, h) patient reviews CDS before PCP enters room, i) simple visual display of potential benefits for patients, j) prioritization of treatment options based on potential benefit to patient, k) automated feedback to PCP and clinics on CDS use rates at targeted encounters, l) compensation to clinics to cover training costs, m) location of algorithms in web service to facilitate updates and scalability, and n) built-in SmartSet to facilitate clinical actions.
Conclusion: These design features may inform future iterations of chronic disease CDS systems. |
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ISSN: | 2330-0698 2330-0698 |
DOI: | 10.17294/2330-0698.1324 |