A business intelligence framework for tactical demand planning in home health care: evidence from a Colombian case study

A business intelligence framework for tactical demand planning in home health care: evidence from a Colombian case study | 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 A business intelligence framework for tactical demand planning in home health care: evidence from a Colombian case study Jennifer Benavides Castillo, Elena Valentina Gutiérrez-Gutiérrez, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9118103/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Background Home health care (HHC) services face increasing pressure to balance growing demand, limited workforce capacity, and complex contractual arrangements with health insurers. Although large volumes of operational data are routinely generated, many HHC providers lack structured analytical frameworks to support tactical demand planning. This challenge is particularly relevant in Latin American health systems, where information is often fragmented across multiple administrative sources and the analytical maturity of HHC institutions remains limited. This paper proposes a business intelligence (BI) framework to support tactical demand planning in HHC institutions. Methods The research follows the CRISP-DM methodology and is conducted as a descriptive case study in a Colombian HHC institution serving more than 1800 monthly patients and performing approximately 60000 visits annually. Semi-structured interviews with managerial and operational staff were conducted to identify key planning decisions and information requirements. The analysis used the institution’s historical database covering the period 2014–2024, comprising 372337 records on patients, health insurers, services, and geolocation. Descriptive statistical analyses examined demographic characteristics, epidemiological profiles, service demand patterns, visit volumes, and geographic distribution to inform the development of a BI model for demand planning. Results Demand for HHC services increased substantially over the study period. Chronic patients showed the largest growth, rising from 235 admissions in 2015 to 2280 in 2022, while palliative patients increased from 4 cases in 2015 to 210 in 2023. The epidemiological profile showed a high prevalence of endocrine, metabolic, circulatory, and genitourinary conditions among older age groups. Service demand was dominated by therapist services (annual average 186864 visits), followed by auxiliary nursing (80279) and nursing services (21203). Therapist visits increased from 127404 in 2015 to 333038 in 2023, accompanied by rising rejection rates, indicating pressure on service capacity. Demand was geographically concentrated in the metropolitan cluster of the covering area, with increasing chronic and palliative demand in more distant municipalities. Conclusions Structured analysis of historical service records can improve demand visibility and support more consistent planning decisions in HHC institutions, even in fragmented data environments. The proposed framework contributes to strengthening data-informed demand planning in fragmented health systems common across Latin America. Home health care demand planning business intelligence decision support systems descriptive analytics Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 05 May, 2026 Reviewers invited by journal 22 Apr, 2026 Editor assigned by journal 20 Apr, 2026 Editor invited by journal 27 Mar, 2026 Submission checks completed at journal 27 Mar, 2026 First submitted to journal 27 Mar, 2026 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-9118103","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":633488971,"identity":"67cdcc2f-06d4-49ee-9a1d-cebc427b175d","order_by":0,"name":"Jennifer Benavides Castillo","email":"","orcid":"","institution":"University of Valle","correspondingAuthor":false,"prefix":"","firstName":"Jennifer","middleName":"Benavides","lastName":"Castillo","suffix":""},{"id":633488972,"identity":"67391b50-6d15-455b-bb46-a74d2bd98d21","order_by":1,"name":"Elena Valentina Gutiérrez-Gutiérrez","email":"data:image/png;base64,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","orcid":"","institution":"University of Valle","correspondingAuthor":true,"prefix":"","firstName":"Elena","middleName":"Valentina","lastName":"Gutiérrez-Gutiérrez","suffix":""},{"id":633488973,"identity":"fa436a83-01ee-4cfe-95c9-a2fe7c03a135","order_by":2,"name":"Robert Hugo Caicedo Muñoz","email":"","orcid":"","institution":"Secretaría de Salud Pública","correspondingAuthor":false,"prefix":"","firstName":"Robert","middleName":"Hugo Caicedo","lastName":"Muñoz","suffix":""}],"badges":[],"createdAt":"2026-03-13 21:09:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9118103/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9118103/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108492459,"identity":"32a7d4fd-55db-4eb0-b44f-b569d5a4d042","added_by":"auto","created_at":"2026-05-05 09:57:49","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1262076,"visible":true,"origin":"","legend":"","description":"","filename":"00.Benavides.et.al2026.aBIFrameworkTacDemPlaHHCRevisedMarch272026.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9118103/v1_covered_c33b528e-eecc-462c-959d-ef3f3cf26e97.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A business intelligence framework for tactical demand planning in home health care: evidence from a Colombian case study","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Home health care, demand planning, business intelligence, decision support systems, descriptive analytics","lastPublishedDoi":"10.21203/rs.3.rs-9118103/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9118103/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eHome health care (HHC) services face increasing pressure to balance growing demand, limited workforce capacity, and complex contractual arrangements with health insurers. Although large volumes of operational data are routinely generated, many HHC providers lack structured analytical frameworks to support tactical demand planning. This challenge is particularly relevant in Latin American health systems, where information is often fragmented across multiple administrative sources and the analytical maturity of HHC institutions remains limited. This paper proposes a business intelligence (BI) framework to support tactical demand planning in HHC institutions.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe research follows the CRISP-DM methodology and is conducted as a descriptive case study in a Colombian HHC institution serving more than 1800 monthly patients and performing approximately 60000 visits annually. Semi-structured interviews with managerial and operational staff were conducted to identify key planning decisions and information requirements. The analysis used the institution\u0026rsquo;s historical database covering the period 2014\u0026ndash;2024, comprising 372337 records on patients, health insurers, services, and geolocation. Descriptive statistical analyses examined demographic characteristics, epidemiological profiles, service demand patterns, visit volumes, and geographic distribution to inform the development of a BI model for demand planning.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eDemand for HHC services increased substantially over the study period. Chronic patients showed the largest growth, rising from 235 admissions in 2015 to 2280 in 2022, while palliative patients increased from 4 cases in 2015 to 210 in 2023. The epidemiological profile showed a high prevalence of endocrine, metabolic, circulatory, and genitourinary conditions among older age groups. Service demand was dominated by therapist services (annual average 186864 visits), followed by auxiliary nursing (80279) and nursing services (21203). Therapist visits increased from 127404 in 2015 to 333038 in 2023, accompanied by rising rejection rates, indicating pressure on service capacity. Demand was geographically concentrated in the metropolitan cluster of the covering area, with increasing chronic and palliative demand in more distant municipalities.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eStructured analysis of historical service records can improve demand visibility and support more consistent planning decisions in HHC institutions, even in fragmented data environments. The proposed framework contributes to strengthening data-informed demand planning in fragmented health systems common across Latin America.\u003c/p\u003e","manuscriptTitle":"A business intelligence framework for tactical demand planning in home health care: evidence from a Colombian case study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-04 08:19:52","doi":"10.21203/rs.3.rs-9118103/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"242757790297354128332819993743179786902","date":"2026-05-05T06:20:23+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-22T18:24:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-20T09:12:35+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-27T21:32:44+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-27T12:25:13+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Health Services Research","date":"2026-03-27T12:20:14+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"de079c50-c6bb-4ec9-97f6-d712b523f1b4","owner":[],"postedDate":"May 4th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"242757790297354128332819993743179786902","date":"2026-05-05T06:20:23+00:00","index":74,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T08:19:52+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-04 08:19:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9118103","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9118103","identity":"rs-9118103","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}