Automated severity classification of AIDS hospitalizations.

F W Stitt, Y Lu, G M Dickinson, N G Klimas
Author Information
  1. F W Stitt: Department of Epidemiology and Public Health, University of Miami, School of Medicine, Florida 33101.

Abstract

To validate an automated AIDS severity-of-illness prognostic algorithm, 2,113 discharge summaries of HIV-infected patients were merged with the Problem-Oriented Medical Synopsis (POMS) and an HIV risk registry. The combination of a medically derived classification and staging algorithm with multivariate statistical techniques was used for automated severity-of-illness disease staging and prognostic assignment. The model correctly predicted the outcomes of 82% of all cases (death, survivorship) at discharge, and 66% of deaths.

MeSH Term

Algorithms
Decision Making, Computer-Assisted
Florida
HIV Infections
Hospitalization
Humans
Length of Stay
Medical Records, Problem-Oriented
Multivariate Analysis
Patient Discharge
Prognosis
Registries
Reproducibility of Results
Risk Factors
Severity of Illness Index
Survival Analysis

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