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DOI: 10.4338/ACI-2015-11-RA-0161
Using Electronic Case Summaries to Elicit Multi-Disciplinary Expert Knowledge about Referrals to Post-Acute Care
The authors wish to thank the National Institute of Nursing Research of the National Institutes of Health under Award Number R01-NR007674 and the experts who participated in this study for supporting the research reported in this publication. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. We also thank the nursing and information technology staff at the six hospitals who assisted us in collecting the electronic data for the study and MI Digital Agency for their technical expertise in building the website and data management.Publication History
received:
23 November 2015
accepted:
28 February 2016
Publication Date:
16 December 2017 (online)
![](https://www.thieme-connect.de/media/10.1055-s-00035026/201602/lookinside/thumbnails/10-4338-aci-2015-11-ra-0161-1.jpg)
Summary
Background
Eliciting knowledge from geographically dispersed experts given their time and scheduling constraints, while maintaining anonymity among them, presents multiple challenges.
Objectives
Describe an innovative, Internet based method to acquire knowledge from experts regarding patients who need post-acute referrals. Compare, 1) the percentage of patients referred by experts to percentage of patients actually referred by hospital clinicians, 2) experts’ referral decisions by disciplines and geographic regions, and 3) most common factors deemed important by discipline.
Methods
De-identified case studies, developed from electronic health records (EHR), contained a comprehensive description of 1,496 acute care inpatients. In teams of three, physicians, nurses, social workers, and physical therapists reviewed case studies and assessed the need for post-acute care referrals; Delphi rounds followed when team members did not agree. Generalized estimating equations (GEEs) compared experts’ decisions by discipline, region of the country and to the decisions made by study hospital clinicians, adjusting for the repeated observations from each expert and case. Frequencies determined the most common case characteristics chosen as important by the experts.
Results
The experts recommended referral for 80% of the cases; the actual discharge disposition of the patients showed referrals for 67%. Experts from the Northeast and Midwest referred 5% more cases than experts from the West. Physicians and nurses referred patients at similar rates while both referred more often than social workers. Differences by discipline were seen in the factors identified as important to the decision.
Conclusion
The method for eliciting expert knowledge enabled national dispersed expert clinicians to anonymously review case summaries and make decisions about post-acute care referrals. Having time and a comprehensive case summary may have assisted experts to identify more patients in need of post-acute care than the hospital clinicians. The methodology produced the data needed to develop an expert decision support system for discharge planning.
Citation: Bowles KH, Ratcliffe S, Potashnik S, Topaz M, Holmes J, Shih N-W, Naylor MD. Using electronic case summaries to elicit multi-disciplinary expert knowledge about referrals to post-acute care.
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