Identifying households with children who have complex needs: a segmentation model for integrated care systems

Identifying households with children who have complex needs: a segmentation model for integrated care systems | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Identifying households with children who have complex needs: a segmentation model for integrated care systems Roberta Piroddi, Andrea Astbury, Wesam Baker, Kostantinos Daras, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5573233/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Adversity in childhood is increasing in the United Kingdom. Complex health and social problems affecting children cluster in families where adults also have high need, but services are rarely aligned to support the whole family. Household level segmentation can help identify households most needing integrated support. Thus, the aim was to develop a segmentation model to identify those households with children who have high levels of complex cross-sectoral needs, to use as a case-finding tool for health and social care services, and to describe characteristics of identified households, to inform service integration. Method: Working with stakeholders - in an English region of 2.7m population- we agreed a definition of families having complex needs which would benefit from service integration – including households with high intensity use, who had both physical and mental health problems amongst both adults and children and wider social risks. We then used individual and household linked data across multiple health and social care services to identify these households, providing an algorithm to be used in a case finding interface. Finally, to understand the needs of this segment, and to identify unmet need, to tailor support, we used descriptive statistics and Poisson regression to profile the segment and compare them with the rest of the population. Results: 21,527 households (8% of the population of the region) were identified with complex needs, including 89,631 people (41,382 children), accounting for 34% of health and social care costs for families with children, £362 million in total, of which 42% was on children in care of local authorities. The households had contact with 3-4 different services, had high prevalence of mental health problems, most frequently co-morbid with respiratory problems, with high mental health emergency service use particularly amongst teenage girls many of whom had no prior elective treatment for conditions. Conclusion: Our model provides a potentially useful tool for identifying households that could benefit from better integration of services and targeted family support that can help break intergenerational transfer of adversity. Health Policy Health service innovation population health management health needs segmentation integrated health and social care systems Full Text Additional Declarations The authors declare potential competing interests as follows: RP, BB, and KD report no conflict of interest in this project. AA is employed by NHS C&M Integrated Care Board, who is the commissioner of health services in C&M. WB, JR and IB are employed by NHS Mersey Care Foundation Trust, which is one of the providers of community and mental health services in C&M. They were involved in providing information about general service provision in C&M, facilitating access to data, as well as providing contextual information for the interpretation of the results, and reviewing drafts of the manuscript. They had no role in the analysis or presentation of the results. The views expressed in this article are those of the authors and do not represent the views of Mersey Care NHS Foundation Trust. There are no other relationships or activities that could appear to have influenced the submitted work. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5573233","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":385764533,"identity":"727f51fe-7cc7-4846-90e0-b77365738f9e","order_by":0,"name":"Roberta Piroddi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIie2RsYrCQBCGZxlImhxpNxjuGXIsKKLgs1j5BoelMrBp8gCKL+EDWKxMb21hoQjWsQt4hVmChXBrLC32a2an+Nj5ZwA8no9EzAACjOLQPixhU7JWJaGHgq2KJUDI+NG0Kb0V6bL8HaSKUcvr5vAdI4iyAlYuJT1sabnYTaIuC50sLheVEGBSAHddipRjwi/NViEVGR6v6wk7ADxsVRTVyl+j4O0tJUMxP0OjBPYX92DploTNIlnMT4WxWYTuF9nEGV928jPUGxvFeX40lak3FhLvq+ngZ+Z0nlsDzXFfHfIfxePxeDzP3AFMBlEuZcYzAwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-1139-2949","institution":"University of Liverpool","correspondingAuthor":true,"prefix":"","firstName":"Roberta","middleName":"","lastName":"Piroddi","suffix":""},{"id":385764534,"identity":"dd68c162-8a37-444e-9f52-2c50e50a60c2","order_by":1,"name":"Andrea Astbury","email":"","orcid":"","institution":"NHS Cheshire and Merseyside","correspondingAuthor":false,"prefix":"","firstName":"Andrea","middleName":"","lastName":"Astbury","suffix":""},{"id":385764535,"identity":"c8a0d9ba-df1f-4db3-be35-f4632ad0bdb1","order_by":2,"name":"Wesam Baker","email":"","orcid":"","institution":"Mersey Care NHS Foundation Trust","correspondingAuthor":false,"prefix":"","firstName":"Wesam","middleName":"","lastName":"Baker","suffix":""},{"id":385764536,"identity":"de88fd81-d36b-4e65-a9c6-7df9222f0133","order_by":3,"name":"Kostantinos Daras","email":"","orcid":"","institution":"University of Liverpool","correspondingAuthor":false,"prefix":"","firstName":"Kostantinos","middleName":"","lastName":"Daras","suffix":""},{"id":385764537,"identity":"bef30472-eaf1-4236-bab8-faaab8de3715","order_by":4,"name":"Joe Rafferty","email":"","orcid":"","institution":"Mersey Care NHS Foundation Trust","correspondingAuthor":false,"prefix":"","firstName":"Joe","middleName":"","lastName":"Rafferty","suffix":""},{"id":385764538,"identity":"620be6a9-71e1-46f0-b31d-8e7b82d1e76b","order_by":5,"name":"Iain Buchan","email":"","orcid":"","institution":"University of Liverpool","correspondingAuthor":false,"prefix":"","firstName":"Iain","middleName":"","lastName":"Buchan","suffix":""},{"id":385764539,"identity":"8af3cb5d-408f-4129-9f89-7bb5e695dc05","order_by":6,"name":"Benjamin Barr","email":"","orcid":"","institution":"University of Liverpool","correspondingAuthor":false,"prefix":"","firstName":"Benjamin","middleName":"","lastName":"Barr","suffix":""}],"badges":[],"createdAt":"2024-12-03 14:52:02","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":true,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-5573233/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5573233/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":70618831,"identity":"23fe1fad-be6c-4818-82fb-edaaea435bd2","added_by":"auto","created_at":"2024-12-05 02:43:57","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":647084,"visible":true,"origin":"","legend":"","description":"","filename":"complexhouseholdssegmentationfullmanuscriptrevisedafterreviewclear.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5573233/v1_covered_acd3373a-1624-4523-a8ae-588e782c188d.pdf"}],"financialInterests":"The authors declare potential competing interests as follows: RP, BB, and KD report no conflict of interest in this project. 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Complex health and social problems affecting children cluster in families where adults also have high need, but services are rarely aligned to support the whole family. Household level segmentation can help identify households most needing integrated support.\u003cstrong\u003e \u003c/strong\u003eThus, the aim was\u003cstrong\u003e \u003c/strong\u003eto develop a segmentation model to identify those households with children who have high levels of complex cross-sectoral needs, to use as a case-finding tool for health and social care services, and to describe characteristics of identified households, to inform service integration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod: \u003c/strong\u003eWorking with stakeholders - in an English region of 2.7m population-\u003cstrong\u003e \u003c/strong\u003ewe agreed a definition of families having complex needs which would benefit from service integration – including households with high intensity use, who had both physical and mental health problems amongst both adults and children and wider social risks. We then used individual and household linked data across multiple health and social care services to identify these households, providing an algorithm to be used in a case finding interface. Finally, to understand the needs of this segment, and to identify unmet need, to tailor support, we used descriptive statistics and Poisson regression to profile the segment and compare them with the rest of the population.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003e21,527 households (8% of the population of the region) were identified with complex needs, including 89,631 people (41,382 children), accounting for 34% of health and social care costs for families with children, £362 million in total, of which 42% was on children in care of local authorities. The households had contact with 3-4 different services, had high prevalence of mental health problems, most frequently co-morbid with respiratory problems, with high mental health emergency service use particularly amongst teenage girls many of whom had no prior elective treatment for conditions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eOur model\u003cstrong\u003e \u003c/strong\u003eprovides a potentially useful tool for identifying households that could benefit from better integration of services and targeted family support that can help break intergenerational transfer of adversity.\u003c/p\u003e","manuscriptTitle":"Identifying households with children who have complex needs: a segmentation model for integrated care systems","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-05 02:35:41","doi":"10.21203/rs.3.rs-5573233/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9bf8ed3a-c276-4496-a8dd-ceb5eb86fa62","owner":[],"postedDate":"December 5th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":41097604,"name":"Health Policy"}],"tags":[],"updatedAt":"2024-12-05T02:35:41+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-05 02:35:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5573233","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5573233","identity":"rs-5573233","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}