FEATURESFactors Affecting Patient Prioritization Decisions at Admission to Home Healthcare A Predictive Study to Develop a Risk Screening ToolTopaz, Maxim PhD, RN; Naylor, Mary D. PhD, RN; Holmes, John H. PhD; Bowles, Kathryn H. PhD, RNAuthor Information Author Affiliations: School of Nursing and Data Science Institute, Columbia University (Dr Topaz); and Visiting Nurse Service of New York (Drs Topaz and Bowles); and School of Nursing (Drs Naylor and Bowles), and Department of Biostatistics and Epidemiology, Institute for Biomedical Informatics, Perelman School of Medicine (Dr Holmes), University of Pennsylvania, Philadelphia. This study received support from the US National Institute of Nursing Research (R01-NR007674). This work is based on a dissertation by Maxim Topaz. Reference: Topaz M. Developing a tool to support decisions on patient prioritization at admission to home healthcare. Dissertation repository, University of Pennsylvania Library; 2014. https://doi.org/AAI3635561. The authors have disclosed that they have no significant relationships with, or financial interest in, any commercial companies pertaining to this article. Corresponding author: Maxim Topaz, PhD, RN, Associate Professor, School of Nursing, Columbia University, New York, NY, USA, 560 W 168th St, New York, NY 10032 (firstname.lastname@example.org). Online date: December 5, 2019 CIN: Computers, Informatics, Nursing: February 2020 - Volume 38 - Issue 2 - p 88-98 doi: 10.1097/CIN.0000000000000576 Buy Metrics Abstract There is a lack of evidence on how to identify high-risk patients admitted to home healthcare. This study aimed (1) to identify which disease characteristics, medications, patient needs, social support characteristics, and other factors are associated with patient priority for the first home health nursing visit; and (2) to construct and validate a predictive model of patient priority for the first home health nursing visit. This was a predictive study of home health visit priority decisions made by 20 nurses for 519 older adults. The study found that nurses were more likely to prioritize patients who had wounds (odds ratio = 1.88), comorbid condition of depression (odds ratio = 1.73), limitation in current toileting status (odds ratio = 2.02), higher number of medications (increase in odds ratio for each medication = 1.04), and comorbid conditions (increase in odds ratio for each condition = 1.04). This study developed one of the first clinical decision support tools for home healthcare called “PREVENT”. (PRiority home health Visit Tool). Further work is needed to increase the specificity and generalizability of the tool and to test its effects on patient outcomes. Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.