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.

Eliciting the Impact of Digital Consulting for Young People Living With Long-Term Conditions (LYNC Study): Cognitive Interviews to Assess the Face and Content Validity of Two Patient-Reported Outcome Measures.

BACKGROUND: Digital consulting, using email, text, and Skype, is increasingly offered to young people accessing specialist care for long-term conditions. No patient-reported outcome measures (PROMs) have been evaluated for assessing outcomes of digital consulting. Systematic and scoping reviews, alongside patient involvement, revealed 2 candidate PROMs for this purpose: the patient activation measure (PAM) and the physician's humanistic behaviors questionnaire (PHBQ). PAM measures knowledge, beliefs, and skills that enable people to manage their long-term conditions. PHBQ assesses the presence of behaviors that are important to patients in their physician-patient interactions. OBJECTIVE: This study aimed to assess the face and content validity of PAM and PHBQ to explore whether they elicit important outcomes of digital consulting and whether the PROMs can isolate the digital consultation component of care. METHODS: Participants were drawn from 5 clinics providing specialist National Health Service care to 16- to 24-year-olds with long-term health conditions participating in the wider LYNC (Long-Term Conditions, Young People, Networked Communications) study. Overall, 14 people undertook a cognitive interview in this substudy. Of these, 7 participants were young people with either inflammatory bowel disease, cystic fibrosis, or cancer. The remaining 7 participants were clinicians who were convenience sampled. These included a clinical psychologist, 2 nurses, 3 consultant physicians, and a community youth worker practicing in cancer, diabetes, cystic fibrosis, and liver disease. Cognitive interviews were transcribed and analyzed, and a spreadsheet recorded the participants' PROM item appraisals. Illustrative quotes were extracted verbatim from the interviews for all participants. RESULTS: Young people found 11 of the PAM 13 items and 7 of the additional 8 PAM 22 items to be relevant to digital consulting. They were only able to provide spontaneous examples of digital consulting for 50% (11/22) of the items. Of the 7 clinicians, 4 appraised all PAM 13 items and 20 of the PAM 22 items to be relevant to evaluating digital consulting and articulated operationalization of the items with reference to their own digital consulting practice with greater ease than the young people. Appraising the PHBQ, in 14 of the 25 items, two-thirds of the young people's appraisals offered digital consulting examples with ease, suggesting that young people can detect and discern humanistic clinician behaviors via digital as well as face-to-face communication channels. Moreover, 17 of the 25 items were appraised as relevant by the young people. This finding was mirrored in the clinician appraisals. Both young people and the clinicians found the research task complex. Young participants required considerably more researcher prompting to elicit examples related to digital consulting rather than their face-to-face care. CONCLUSIONS: PAM and PHBQ have satisfactory face and content validity for evaluating digital consulting to warrant proceeding to psychometric evaluation. Completion instructions require revision to differentiate between digital and face-to-face consultations.