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Who needs AESOP? Predicting long-term readmission rates from routine Early Intervention team discharge information
Matthew J Taylor1, Tania Blanco Pena1,2, Rocio Perez-Iglesias1,3
1Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
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 4 or more. Model predictions for 10-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 long-term outcomes matching those observed in formal research. This low-cost approach could allow EI services to develop locale-specific prognostic information.
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