{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T10:27:42Z","timestamp":1785407262620,"version":"3.56.0"},"reference-count":13,"publisher":"Royal College of Psychiatrists","license":[{"start":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T00:00:00Z","timestamp":1768867200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["cambridge.org"],"crossmark-restriction":true},"short-container-title":["BJPsych Bull"],"abstract":"<jats:sec id=\"S2056469425102052_as1\">\n                    <jats:title>Aims and method<\/jats:title>\n                    <jats:p>This study aimed to develop and evaluate a predictive model using electronic health record (EHR) data from a large south London mental health service, in order to identify patients 3 months following first referral who are at risk of subsequent high-intensity service use over the subsequent 12 months. Early identification of such patients may support proactive and personalised care planning, reducing the need for high-cost episodes of care. Predictive models were developed using information from 18 869 patients newly referred between 2007 and 2011. High-intensity use was defined as the top 10% of estimated mental healthcare expenditure. The model was developed using demographic, clinical and service use variables, and was validated on data from the periods 2012\u20132017 and 2018\u20132023.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"S2056469425102052_as2\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A logistic regression model achieved an area under the receiver operating characteristic (AUROC) of 0.79 in development (sensitivity 0.82, specificity 0.54), with robust performance in validation sets (AUROC 0.81, 0.83, respectively). Key predictors included first 3 months service use, schizophrenia or eating disorder diagnoses and living alone. Natural language processing-derived features did not improve performance.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"S2056469425102052_as3\">\n                    <jats:title>Clinical implications<\/jats:title>\n                    <jats:p>Routine EHR data performed well in predicting the risk of high-cost care, potentially enabling targeted interventions and more efficient resource allocation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1192\/bjb.2025.10205","type":"journal-article","created":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T05:40:26Z","timestamp":1768887626000},"page":"1-7","update-policy":"https:\/\/doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":1,"title":["Development and validation of a predictive model for high-intensity mental health service use using electronic health record data"],"prefix":"10.1192","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-3065-1072","authenticated-orcid":false,"given":"Bharadwaj V.","family":"Chada","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/0220mzb33","id-type":"ROR","asserted-by":"publisher"}],"name":"King\u2019s College London"},{"name":"South London and Maudsley NHS Foundation Trust"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4435-6397","authenticated-orcid":false,"given":"Robert","family":"Stewart","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/0220mzb33","id-type":"ROR","asserted-by":"publisher"}],"name":"King\u2019s College London"},{"name":"South London and Maudsley NHS Foundation Trust"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"James","family":"Lai","sequence":"additional","affiliation":[{"name":"Imperial College Healthcare NHS Trust"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"170","published-online":{"date-parts":[[2026,1,20]]},"reference":[{"key":"S2056469425102052_ref10","unstructured":"10 Gilburt, H , Mallorie, S. Mental health 360: inequalities. The King\u2019s Fund, 2024 (https:\/\/www.kingsfund.org.uk\/insight-and-analysis\/long-reads\/mental-health-360-inequalities)."},{"key":"S2056469425102052_ref9","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.1004139"},{"key":"S2056469425102052_ref1","unstructured":"1 Baker, C , Kirk-Wade, E. Mental Health Statistics: Prevalence, Services and Funding in England. House of Commons Library, 2024 (http:\/\/researchbriefings.files.parliament.uk\/documents\/SN06988\/SN06988.pdf)."},{"key":"S2056469425102052_ref7","doi-asserted-by":"publisher","DOI":"10.1080\/13696998.2022.2157596"},{"key":"S2056469425102052_ref5","unstructured":"5 NIHR Maudsley Biomedical Research Centre. Natural Language Processing (NLP) Service. NIHR Maudsley Biomedical Research Centre, 2025 (https:\/\/www.maudsleybrc.nihr.ac.uk\/facilities\/clinical-record-interactive-search-cris\/cris-natural-language-processing\/)."},{"key":"S2056469425102052_ref12","first-page":"CD007906","article-title":"Intensive case management for severe mental illness","volume":"1","author":"Dieterich","year":"2017","journal-title":"Cochrane Database Syst Rev"},{"key":"S2056469425102052_ref4","unstructured":"4 NIHR Maudsley Biomedical Research Centre. Clinical Record Interactive Search (CRIS). NIHR Maudsley Biomedical Research Centre, 2025 (https:\/\/www.maudsleybrc.nihr.ac.uk\/facilities\/clinical-record-interactive-search-cris\/)."},{"key":"S2056469425102052_ref6","unstructured":"6 University of Kent. Unit Costs 2022\u20132027. University of Kent, 2025 (https:\/\/www.pssru.ac.uk\/unitcostsreport\/)."},{"key":"S2056469425102052_ref11","doi-asserted-by":"publisher","DOI":"10.1038\/s41380-022-01528-4"},{"key":"S2056469425102052_ref8","doi-asserted-by":"publisher","DOI":"10.1002\/eat.23486"},{"key":"S2056469425102052_ref2","doi-asserted-by":"publisher","DOI":"10.1192\/bjo.2019.96"},{"key":"S2056469425102052_ref13","first-page":"55","article-title":"Realigning theory with evidence to understand the role of care coordination in mental health services research","volume":"26","author":"Hynes","year":"2023","journal-title":"Int J Care Coord"},{"key":"S2056469425102052_ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.euroneuro.2024.08.005"}],"container-title":["BJPsych Bulletin"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S2056469425102052","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T05:40:28Z","timestamp":1768887628000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S2056469425102052\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,20]]},"references-count":13,"alternative-id":["S2056469425102052"],"URL":"https:\/\/doi.org\/10.1192\/bjb.2025.10205","relation":{},"ISSN":["2056-4694","2056-4708"],"issn-type":[{"value":"2056-4694","type":"print"},{"value":"2056-4708","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,20]]},"assertion":[{"value":"\u00a9 The Author(s), 2026. Published by Cambridge University Press on behalf of Royal College of Psychiatrists","name":"copyright","label":"Copyright","group":{"name":"copyright_and_licensing","label":"Copyright and Licensing"}},{"value":"This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https:\/\/creativecommons.org\/licenses\/by\/4.0\/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.","name":"license","label":"License","group":{"name":"copyright_and_licensing","label":"Copyright and Licensing"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}