Prediction of Early Readmission in Medical Inpatients Using the Probability of Repeated Admission Instrument

Abstract

Background: 

In the absence of an instrument to predict risk of early readmission, examination of the well-validated probability of repeated admission (Pra) for this new purpose is indicated.

Objective: 

The objective of this study was to examine the use of the Pra in accurately identifying and predicting adult medical inpatients at risk of early readmission.

Methods: 

Over 20 months, 1,077 consecutively admitted medical patients were enrolled in this prospective cohort study at a Midwestern tertiary care medical center. Pra score values were calculated within 2 days of discharge. Databases at the index medical center and other institutions were queried to identify readmission within 41 days.

Results: 

Prevalence of readmission was 14% (confidence interval = 12.4%-15.6%). Pra score values ranged from .16 to .75. Indices to identify and predict readmission for a range of cut points were reported to minimize loss of information. The likelihood ratio for patients with a Pra score value ≥.53 was 1.67. Using a Pra cut point of ≥.45, readmission of patients with a high Pra was 2.3 times more likely than that of patients with a low Pra (p < .001, confidence interval = 1.63-3.27). Comparisons between cohorts indicated that differences existed with four of the eight variables used to calculate the Pra score: diabetes (p = .01), self-rated health status (p = .007), and number of doctor visits (p < .001) and hospitalizations (p < .001) in the past year.

Discussion: 

Within this heterogeneous sample, prediction of readmission using the Pra was better than chance. These findings may facilitate development of a better predictive model by combining select Pra variables with other variables associated with early readmission.