2020
DOI: 10.31234/osf.io/bvcgu
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Using epidemiological evidence to forecast population need for early treatment programmes in mental health: a generalisable Bayesian prediction methodology applied to and validated for first-episode psychosis in England

Abstract: Background: Mental health service policymakers require evidence-based information to optimise effective care provision based on local need, but tools are unavailable. We developed and validated a population-level prediction model to forecast need for early intervention in psychosis [EIP] services in England up to 2025.Methods: We fitted six candidate Bayesian Poisson regression models, combining epidemiological data on psychosis risk, to predict new annual caseload of referrals, assessed, treated, and probable… Show more

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