Who needs AESOP? Predicting long-term readmission rates from routine Early Intervention team discharge information

Area of Science:

• Psychiatry
• Mental Health Research

Background:

• Prognosis in early psychosis (EP) is highly variable.
• Limited long-term prognostic data is available from research studies.

Purpose of the Study:

• To assess the predictive power of routine discharge information for long-term readmission prognosis in early psychosis.
• To evaluate if standard discharge data can forecast long-term outcomes.

Main Methods:

• Reviewed records of 239 individuals exiting Early Intervention (EI) services.
• Counted relapses over an average of 2.5 years.
• Modeled and extrapolated relapse data to predict 10-year outcomes, comparing with published data.

Main Results:

• Significant variation in relapse numbers: 59% had no relapses before discharge, 5% had 4 or more.
• Model predictions for 10-year outcomes closely matched observed data.

Conclusions:

• A straightforward model effectively describes relapse distributions in individuals discharged from EI services.
• This low-cost method can generate locale-specific prognostic information for EI services, aligning with formal research findings.