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A Framework for Usable and Effective Clinical Decision Support: Experience from the iCPR Randomized Clinical Trial

INTRODUCTION: The promise of Clinical Decision Support (CDS) has always been to transform patient care and improve patient outcomes through the delivery of timely and appropriate recommendations that are patient specific and, more often than not, are appropriately actionable. However, the users of C...

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Autores principales: Kannry, Joseph, McCullagh, Lauren, Kushniruk, Andre, Mann, Devin, Edonyabo, Daniel, McGinn, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AcademyHealth 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4537146/
https://www.ncbi.nlm.nih.gov/pubmed/26290888
http://dx.doi.org/10.13063/2327-9214.1150
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author Kannry, Joseph
McCullagh, Lauren
Kushniruk, Andre
Mann, Devin
Edonyabo, Daniel
McGinn, Thomas
author_facet Kannry, Joseph
McCullagh, Lauren
Kushniruk, Andre
Mann, Devin
Edonyabo, Daniel
McGinn, Thomas
author_sort Kannry, Joseph
collection PubMed
description INTRODUCTION: The promise of Clinical Decision Support (CDS) has always been to transform patient care and improve patient outcomes through the delivery of timely and appropriate recommendations that are patient specific and, more often than not, are appropriately actionable. However, the users of CDS—providers—are frequently bombarded with inappropriate and inapplicable CDS that often are not informational, not integrated into the workflow, not patient specific, and that may present out of date and irrelevant recommendations. METHODS: The integrated clinical prediction rule (iCPR) project was a randomized clinical trial (RCT) conducted to determine if a novel form of CDS, i.e., clinical prediction rules (CPRs), could be efficiently integrated into workflow and result in changes in outcomes (e.g., antibiotic ordering) when embedded within a commercial electronic health record (EHR). We use the lessons learned from the iCPR project to illustrate a framework for constructing usable, useful, and effective actionable CDS while employing off-the-shelf functionality in a production system. Innovations that make up the framework combine the following: (1) active and actionable decision support, (2) multiple rounds of usability testing with iterative development for user acceptance, (3) numerous context sensitive triggers, (4) dedicated training and support for users of the CDS tool for user adoption, and (5) support from clinical and administrative leadership. We define “context sensitive triggers” as being workflow events (i.e., context) that result in a CDS intervention. DISCUSSION: Success of the framework can be measured by CDS adoption (i.e., intervention is being used), acceptance (compliance with recommendations), and clinical outcomes (where appropriate). This framework may have broader implications for the deployment of Health Information Technology (HIT). RESULTS AND CONCLUSION: iCPR was well adopted(57.4% of users) and accepted (42.7% of users). Usability testing identified and fixed many issues before the iCPR RCT. The level of leadership support and clinical guidance for iCPR was key in establishing a culture of acceptance for both the tool and its recommendations contributing to adoption and acceptance. The dedicated training and support lead to the majority of the residents reporting a high level of comfort with both iCPR tools strep pharyngitis (64.4 percent) and pneumonia (62.7 percent) as well as a high likelihood of using the tools in the future. A surprising framework addition resulted from usability testing: context sensitive triggers.
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spelling pubmed-45371462015-08-19 A Framework for Usable and Effective Clinical Decision Support: Experience from the iCPR Randomized Clinical Trial Kannry, Joseph McCullagh, Lauren Kushniruk, Andre Mann, Devin Edonyabo, Daniel McGinn, Thomas EGEMS (Wash DC) Articles INTRODUCTION: The promise of Clinical Decision Support (CDS) has always been to transform patient care and improve patient outcomes through the delivery of timely and appropriate recommendations that are patient specific and, more often than not, are appropriately actionable. However, the users of CDS—providers—are frequently bombarded with inappropriate and inapplicable CDS that often are not informational, not integrated into the workflow, not patient specific, and that may present out of date and irrelevant recommendations. METHODS: The integrated clinical prediction rule (iCPR) project was a randomized clinical trial (RCT) conducted to determine if a novel form of CDS, i.e., clinical prediction rules (CPRs), could be efficiently integrated into workflow and result in changes in outcomes (e.g., antibiotic ordering) when embedded within a commercial electronic health record (EHR). We use the lessons learned from the iCPR project to illustrate a framework for constructing usable, useful, and effective actionable CDS while employing off-the-shelf functionality in a production system. Innovations that make up the framework combine the following: (1) active and actionable decision support, (2) multiple rounds of usability testing with iterative development for user acceptance, (3) numerous context sensitive triggers, (4) dedicated training and support for users of the CDS tool for user adoption, and (5) support from clinical and administrative leadership. We define “context sensitive triggers” as being workflow events (i.e., context) that result in a CDS intervention. DISCUSSION: Success of the framework can be measured by CDS adoption (i.e., intervention is being used), acceptance (compliance with recommendations), and clinical outcomes (where appropriate). This framework may have broader implications for the deployment of Health Information Technology (HIT). RESULTS AND CONCLUSION: iCPR was well adopted(57.4% of users) and accepted (42.7% of users). Usability testing identified and fixed many issues before the iCPR RCT. The level of leadership support and clinical guidance for iCPR was key in establishing a culture of acceptance for both the tool and its recommendations contributing to adoption and acceptance. The dedicated training and support lead to the majority of the residents reporting a high level of comfort with both iCPR tools strep pharyngitis (64.4 percent) and pneumonia (62.7 percent) as well as a high likelihood of using the tools in the future. A surprising framework addition resulted from usability testing: context sensitive triggers. AcademyHealth 2015-07-09 /pmc/articles/PMC4537146/ /pubmed/26290888 http://dx.doi.org/10.13063/2327-9214.1150 Text en All eGEMs publications are licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License http://creativecommons.org/licenses/by-nc-nd/3.0/
spellingShingle Articles
Kannry, Joseph
McCullagh, Lauren
Kushniruk, Andre
Mann, Devin
Edonyabo, Daniel
McGinn, Thomas
A Framework for Usable and Effective Clinical Decision Support: Experience from the iCPR Randomized Clinical Trial
title A Framework for Usable and Effective Clinical Decision Support: Experience from the iCPR Randomized Clinical Trial
title_full A Framework for Usable and Effective Clinical Decision Support: Experience from the iCPR Randomized Clinical Trial
title_fullStr A Framework for Usable and Effective Clinical Decision Support: Experience from the iCPR Randomized Clinical Trial
title_full_unstemmed A Framework for Usable and Effective Clinical Decision Support: Experience from the iCPR Randomized Clinical Trial
title_short A Framework for Usable and Effective Clinical Decision Support: Experience from the iCPR Randomized Clinical Trial
title_sort framework for usable and effective clinical decision support: experience from the icpr randomized clinical trial
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4537146/
https://www.ncbi.nlm.nih.gov/pubmed/26290888
http://dx.doi.org/10.13063/2327-9214.1150
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