Development of a predictive model to identify inpatients at risk of re-admission within 30 days of discharge (PARR-30).

ABSTRACT: To develop an algorithm for identifying inpatients at high risk of re-admission to a National Health Service (NHS) hospital in England within 30 days of discharge using information that can either be obtained from hospital information systems or from the patient and their notes. Multivariate statistical analysis of routinely collected hospital episode statistics (HES) data using logistic regression to build the predictive model. The model's performance was calculated using bootstrapping. HES data covering all NHS hospital admissions in England. The NHS patients were admitted to hospital between April 2008 and March 2009 (10% sample of all admissions, n=576 868). Area under the receiver operating characteristic curve for the algorithm, together with its positive predictive value and sensiti

SUBMITTER: Billings J 

PROVIDER: S-EPMC3425907 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature