JMIR Publications

ABSTRACT

Background:

Hospital readmission rates have been proposed as an indicator of quality of care within inpatient psychiatric services. Numerous factors may predict readmissions into acute psychiatric care. Minimizing the risk factors linked to psychiatric readmissions can help develop preventive intervention strategies that enhance patient safety, improve quality of care and well-being, and help control healthcare costs.

Objective:

The objective of this paper is to assess the rate and correlates of readmission six months post-discharge from inpatient psychiatric units.

Methods:

This study employed a prospective observational cohort design. The study covered all acute mental health units in Edmonton, Calgary, and Grande Prairie.Admissions to inpatient care six months prior to and six months post the index admission were assessed using medical records from adult inpatient psychiatric units to identify factors associated with patients' readmission within 6 months of discharge. A stepped-wedge recruitment approach was employed. REDCap was used as the data collection tool and the data were exported to SPSS for Mac, version 25 for analysis. Descriptive statistics as well as univariate analysis using a chi-square test was conducted to assess the association between demographic and clinical factors and 6-month post-discharge readmission. Multiple binary logistic regression models were fitted to examine associations between predictors and readmission within six months post-discharge.

Results:

Of the 1,070 participants, 823 (76.9%) were not admitted within 6 months prior to the index admission. Most participants were Caucasian, 661 (61.8%). The six-month post-discharge readmission rate was 247 (23.1%) among participants. Participants who were admitted within six months prior to the index admission were almost two times more likely to be readmitted (OR = 1.76; 95% C.I. = 1.27–2.44; p= <.001) than participants with no prior admission to the index admission. Additionally, unemployed participants were almost twice as likely (OR = 1.69; 95% C.I. = 1.15–2.47; p = .007) to be readmitted compared with employed participants.

Conclusions:

These findings suggest that policies and intervention programs should focus on improving employment opportunities and strengthening post-discharge support systems, which could be instrumental in reducing readmission rates. Clinical Trial: clinicaltrials.gov, NCT05133726. Registered on November 24, 2021.