Validation of the Registered Nurse Assessment of Readiness for Hospital Discharge Scale.

Nurs Res

Kathleen L. Bobay, PhD, RN, NEA-BC, is Professor, Marcella Niehoff School of Nursing, Loyola University Chicago, Maywood, Illinois. Marianne E. Weiss, DNSc, RN, is Wheaton Franciscan Healthcare St. Joseph/Sister Rosalie Klein Professor of Women's Health Professor, Marquette University School of Nursing, Milwaukee, Wisconsin Debra Oswald, PhD, is Professor, Department of Psychology, Marquette University, Milwaukee, Wisconsin. Olga Yakusheva, PhD, is Associate Professor, University of Michigan School of Nursing, Ann Arbor.

Published: February 2019

Background: Statistical models for predicting readmissions have been published for high-risk patient populations but typically focus on patient characteristics; nurse judgment is rarely considered in a formalized way to supplement prediction models.

Objectives: The purpose of this study was to determine psychometric properties of long and short forms of the Registered Nurse Readiness for Hospital Discharge Scale (RN-RHDS), including reliability, factor structure, and predictive validity.

Methods: Data were aggregated from two studies conducted at four hospitals in the Midwestern United States. The RN-RHDS was completed within 4 hours before hospital discharge by the discharging nurse. Data on readmissions and emergency department visits within 30 days were extracted from electronic medical records.

Results: The RN-RHDS, both long and short forms, demonstrate acceptable reliability (Cronbach's alphas of .90 and .73, respectively). Confirmatory factor analysis demonstrated less than adequate fit with the same four-factor structure observed in the patient version. Exploratory factor analysis identified three factors, explaining 60.2% of the variance. When nurses rate patients as less ready to go home (<7 out of 10), patients are 6.4-9.3 times more likely to return to the hospital within 30 days, in adjusted models.

Discussion: The RN-RHDS, long and short forms, can be used to identify medical-surgical patients at risk for potential unplanned return to hospital within 30 days, allowing nurses to use their clinical judgment to implement interventions prior to discharge. Use of the RN-RHDS could enhance current readmission risk prediction models.

Download full-text PDF

Source
http://dx.doi.org/10.1097/NNR.0000000000000293DOI Listing

Publication Analysis

Top Keywords

hospital discharge
12
registered nurse
8
readiness hospital
8
discharge scale
8
long short
8
short forms
8
factor analysis
8
validation registered
4
nurse
4
nurse assessment
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!