Assessing clinical discharge data preferences among practicing surgeons

• Type of Material: Article
• Authors: Ira L. Leeds, Emory University; Vjollca Sadiraj, Georgia State University; James C. Cox, Georgia State University; Kurt E. Schnier, Georgia State University; John F Sweeney, Emory University
• Language: English
• Date: 2013-09-01
• Publisher: Elsevier
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2013 Elsevier Inc. All rights reserved.
• License: Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1016/j.jss.2013.03.064
• Title of Journal or Parent Work: Journal of Surgical Research
• ISSN: 0022-4804
• Volume: 184
• Issue: 1
• Start Page: 42
• End Page: +
• Grant/Funding Information: The research was supported in part by the National Institutes of Health/National Institute on Aging (1RC4AG039071).
• Keywords: Decision support; Life Sciences & Biomedicine; Surgery; Surgical outcomes; HOSPITAL READMISSION; Discharge; Science & Technology; Clinical decision-making; Ordered logit regression; Hospital readmission
• Research Categories: Health Sciences, Medicine and Surgery

Abstract

Background: It is believed that many postoperative patient readmissions can be curbed via optimization of a patient's discharge from hospital, but little is known about how surgeons make the decision to discharge a patient. This study explored the criteria that surgeons preferentially value in their discharge decision-making process. Materials and methods: All surgical faculty and residents at a U.S. academic medical center were surveyed about the relative importance of specific criteria regularly used to make a discharge decision. Demographic and professional information was collected about each surgeon as well. A KruskaleWallis and Fisher's exact test were used to describe one-way analysis of variance between groupings of surgeons. Ordered logit regressions were used to analyze variations across multiple subgroups. Factor analysis was used to further characterize statistically relevant groupings of criteria. Results: In total, 88 (49%) of the invited surgeons responded to the survey. Respondents reported statistically less reliance oncommon Laboratory tests and Patient demographicswhen making discharge decisions preferring Vital signs, Perioperative factors, and Functional criteria. Surgeon-specific factors that influenced discharge criteria preferences included years of clinical education and gender. Factor analysis further identified subtle variations in preferences for specific criteria groupings based on clinical education, gender, and race. Conclusions: Surgeons use a wide range of clinical data when making discharge decisions. Typical measures of patient condition also appear to be used heterogeneously with a preference for binary rather than continuous measures. Further understanding the nature of these preferences may suggest novel ways of presenting discharge-relevant information to clinical decision makers to optimize discharge outcomes.