Prediction of early readmission in medical inpatients using the Probability of Repeated Admission instrument.
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 > or = .53 was 1.67. Using a Pra cut point of > or = .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.


CONCLUSIONS
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.
Novotny
Nancy L
NL
Methodist College of Nursing, Peoria, Illinois 61603, USA. nlnovotny@mcon.edu
Anderson
Mary Ann
MA
D000293:Adolescent; D000328:Adult; D000368:Aged; D005260:Female; D006304:Health Status; D006801:Humans; D007297:Inpatients / Q000706:statistics & numerical data*; D016015:Logistic Models; D008297:Male; D008403:Mass Screening / Q000379:methods* / Q000592:standards; D008875:Middle Aged; D015146:Midwestern United States / Q000453:epidemiology; D015999:Multivariate Analysis; D015403:Nursing Evaluation Research; D016017:Odds Ratio; D010351:Patient Discharge; D010359:Patient Readmission / Q000706:statistics & numerical data*; D011237:Predictive Value of Tests; D011336:Probability; D011446:Prospective Studies; D018570:Risk Assessment / Q000379:methods* / Q000592:standards; D055815:Young Adult