Who needs AESOP? Predicting long term readmission rates from routine EI team discharge information

Research output: Contribution to journalArticlepeer-review

65 Downloads (Pure)

Abstract

Aim: Prognosis following early psychosis is highly variable. Long-term prognostic information from research studies is available in only a few areas. We sought to understand how well routine discharge information allows prediction of long-term readmission prognosis.
Methods: We reviewed the records of 239 people leaving Early Intervention services, after an average of 2.5 years, and counted the number of relapses. The distribution was modelled and extrapolated to a predicted 10 year outcome. Model predictions were compared with published data.
Results: Numbers of relapses varied substantially, with 59% having no relapses before discharge, and 5% having four or more. Model predictions for ten year outcome were close to the observed data.
Conclusions: A simple model can describe the distribution of numbers of relapses among people discharged from EI services, and predict longer-term outcomes matching those observed in formal research. This low-cost approach could allow EI services to develop locale-specific prognostic information.
Original languageEnglish
Number of pages3
JournalEarly Intervention in Psychiatry
Early online date26 Jan 2017
DOIs
Publication statusE-pub ahead of print - 26 Jan 2017

Cite this