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.

Background: Mental health policy makers require evidence-based information to optimise effective care provision based on local need, but tools are unavailable. Aims: To develop and validate a population-level prediction model for need for early intervention in psychosis (EIP) care for first-episode psychosis (FEP) in England up to 2025, based on epidemiological evidence and demographic projections. Method: We used Bayesian Poisson regression to model small-area-level variation in FEP incidence for people aged 16-64 years. We compared six candidate models, validated against observed National Health Service FEP data in 2017. Our best-fitting model predicted annual incidence case-loads for EIP services in England up to 2025, for probable FEP, treatment in EIP services, initial assessment by EIP services and referral to EIP services for 'suspected psychosis'. Forecasts were stratified by gender, age and ethnicity, at national and Clinical Commissioning Group levels. Results: A model with age, gender, ethnicity, small-area-level deprivation, social fragmentation and regional cannabis use provided best fit to observed new FEP cases at national and Clinical Commissioning Group levels in 2017 (predicted 8112, 95% CI 7623-8597; observed 8038, difference of 74 [0.92%]). By 2025, the model forecasted 11 067 new treated cases per annum (95% CI 10383-11740). For every 10 new treated cases, 21 and 23 people would be assessed by and referred to EIP services for suspected psychosis, respectively. Conclusions: Our evidence-based methodology provides an accurate, validated tool to inform clinical provision of EIP services about future population need for care, based on local variation of major social determinants of psychosis.

Which pathways to psychiatric care lead to earlier treatment and a shorter duration of first-episode psychosis?

BACKGROUND: The pathways to care in a first onset psychosis are diverse and may influence the chances of early treatment and therefore the duration of untreated psychosis. We test which pathways to care are associated with a delay in receiving treatment and a longer duration of untreated psychosis (DUP). METHODS: In a population based survey, we interviewed 480 people with first episode psychosis aged 18 to 64 years over a 2-year period. Information from structured interview and case files provided DSM-IV diagnostic, clinical, and demographic information. Consecutive contacts in the care pathway were mapped using the World Health Organisation's Encounter Form. Using information from all sources, DUP was defined as time from symptom onset to first treatment with antipsychotic medication. RESULTS: The most common first contacts were primary care physicians (35.2%), emergency rooms in general hospital settings (21.3%), and criminal justice agencies (25.4%). In multivariate regression models, compared to DUP for those first in contact with primary care, DUP was shortest for first encounters with psychiatric emergency clinics (RR = 0.4, 95% CI: 0.23-0.71) and longest for first encounters with criminal justice agencies (RR = 1.61, 95% CI: 1-2.58). Older age was associated with a longer DUP (RR = 1.01 per year, 95% CI: 1-1.04). A shorter DUP was associated with a diagnosis of mania and affective psychoses-NOS compared with schizophrenia (RR = 0.22, 95% CI: 0.14-0.35; RR = 0.18, 95% CI: 0.06-0.54, respectively), for Black compared with White ethnicity (RR = 0.52, 95% CI: 0.34-0.82), and for each close person in the social network (RR = 0.9, 95% CI: 0.84-0.96). CONCLUSIONS: To further reduce DUP, better links are needed between primary care, emergency rooms, criminal justice and psychiatric services.