Nursing Variables Predicting Readmissions in Patients With a High Risk

Author:

Lee Ji YeaORCID,Park Jisu,Choi Hannah,Oh Eui GeumORCID

Abstract

Unplanned readmission endangers patient safety and increases unnecessary healthcare expenditure. Identifying nursing variables that predict patient readmissions can aid nurses in providing timely nursing interventions that help patients avoid readmission after discharge. We aimed to provide an overview of the nursing variables predicting readmission of patients with a high risk. The authors searched five databases—PubMed, CINAHL, EMBASE, Cochrane Library, and Scopus—for publications from inception to April 2023. Search terms included “readmission” and “nursing records.” Eight studies were included for review. Nursing variables were classified into three categories—specifically, nursing assessment, nursing diagnosis, and nursing intervention. The nursing assessment category comprised 75% of the nursing variables; the proportions of the nursing diagnosis (25%) and nursing intervention categories (12.5%) were relatively low. Although most variables of the nursing assessment category focused on the patients' physical aspect, emotional and social aspects were also considered. This study demonstrated how nursing care contributes to patients' adverse outcomes. The findings can assist nurses in identifying the essential nursing assessment, diagnosis, and interventions, which should be provided from the time of patients' admission. This can mitigate preventable readmissions of patients with a high risk and facilitate their safe transition from an acute care setting to the community.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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