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. 2015 Jul 9;3(2):1150.
doi: 10.13063/2327-9214.1150. eCollection 2015.

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

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

Joseph Kannry et al. EGEMS (Wash DC). .

Abstract

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CDS that often are not informational, not integrated into the workflow, not patient specific, and that may present out of date and irrelevant recommendations.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.

Keywords: Health Information Technology; Human Computer Interaction (HCI).

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References

    1. Greenes RA. Clinical decision support : the road to broad adoption. 2nd ed. Amsterdam Boston: Academic Press; 2014.
    1. Wager KA, Lee FW, Glaser JP. Health care information systems : a practical approach for health care management. Third editon. ed2013.
    1. Shortliffe EH, Cimino JJ. Biomedical informatics : computer applications in health care and biomedicine. 4th ed. New York, NY: Springer; 2014.
    1. Connelly DP, Rich EC, Curley SP, Kelly JT. Knowledge resource preferences of family physicians. J Fam Pract. 1990 Mar;30(3):353–9. [Comparative Study] - PubMed
    1. Hunt DL, Haynes RB, Hanna SE, Smith K. Effects of computer-based clinical decision support systems on physician performance and patient outcomes: a systematic review [see comments] Jama. 1998;280(15):1339–46. - PubMed

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