Development and validation of a transitions-of-care pharmacist tool to predict potentially avoidable 30-day readmissions. (1st February 2018)

• Record Type: Journal Article
• Authors: McAuliffe, Laura (Hunt); Zullo, Andrew R.; Dapaah-Afriyie, Ruth; Berard-Collins, Christine
• Is Part Of: American journal of health-system pharmacy. Volume 75:Number 3(2019)
• Page Start: 111
• Page End: 119
• Publication Date: 2018-02-01
• Subjects: pharmacist -- pharmacy -- readmission -- rehospitalization -- tool -- transitions of care; Hospital pharmacies -- United States -- Periodicals; 615.1
• DOI: 10.2146/ajhp170184
• Languages: English
• ISSNs: 1079-2082

Abstract

Abstract : Purpose: A practical tool for predicting the risk of 30-day readmissions using data readily available to pharmacists before hospital discharge is described. Methods: A retrospective cohort study to identify predictors of potentially avoidable 30-day readmissions was conducted using transitions-of-care pharmacy notes and electronic medical record data from a large health system. Through univariate and multivariable logistic regression analyses of factors associated with unplanned readmissions in the study cohort ( n = 690) over a 22-month period, a risk prediction tool was developed. The tool's discriminative ability was assessed using the C statistic; its calibration was assessed using the Hosmer–Lemeshow goodness-of-fit test. Results: Three factors predictive of readmission risk were identified; these variables—med ication count, co mobidity count, and health ins urance status at discharge—form the 3-predictor MEDCOINS score. Among patients identified as being at high risk for readmission using the MEDCOINS tool, the estimated readmission risk was 22.5%, as compared with an observed readmission rate of 21.9%. The discriminatory performance of MEDCOINS scoring was fair (C statistic = 0.65 [95% confidence interval, 0.60–0.70]), with good calibration (Hosmer–Lemeshow p = 0.99). Conclusion: Among a cohort of patients who were seen by a transitions-of-care pharmacist during an inpatient hospitalization, comorbidity burden, number of medications, and health insurance coverage were most predictive of 30-day readmission. The MEDCOINS tool was found to have fair discriminative ability and good calibration.