A Markov Model for Estimating Medication Adherence Effect on Pediatric Asthma Healthcare Use and Cost

A Markov Model for Estimating Medication Adherence Effect on Pediatric Asthma Healthcare Use and Cost | 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 Markov Model for Estimating Medication Adherence Effect on Pediatric Asthma Healthcare Use and Cost Daniel L. Brinton, Claire A. MacGeorge, Annie N. Simpson, Kit N. Simpson DrPH, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4876779/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 23 Mar, 2026 Read the published version in Cost Effectiveness and Resource Allocation → Version 1 posted 7 You are reading this latest preprint version Abstract Background/Objective: Asthma medication adherence, measured by the asthma medication ratio (AMR), has been shown to be a reliable predictor of exacerbations among children with asthma. We estimated the effects of optimal vs suboptimal AMR on exacerbations resulting in an emergency department (ED) visit or inpatient (IP) admission. Methods : We constructed an asthma Markov model using claims for a cohort of Medicaid beneficiaries aged 2‐17 years (n = 214,452) using 2013‐2014 MarketScan® data who had at least one claim for an inhaled corticosteroid. We calculated 3‐month AMRs as the basis of transition estimates in the model. The AMRs data were transformed to reflect a one‐month Markov cycle length. Our model included five states: controlled, sub optimally controlled, inactive, IP admission, and ED. The Markov model used an overall 2‐year time horizon for 10,000 beneficiaries. Patients entered the model in one of the five states as observed in the Medicaid data. Costs were based on 2017 Medicaid claims adjusted to reflect 2019 costs. Asthma medication cost-weight were mean payments observed for controller or rescue drugs, and costs weights for an ED visit or inpatient admission used median payments. Utilities for each state were based on existing literature. Results : Monthly costs for children with asthma were $214 for controlled, $32 for suboptimally controlled (attributable to fewer medication fills), $565 for months with ED visit, and $5,883 with admission. Over a 2‐year period, we estimated the 2‐year direct medical costs of asthma among Medicaid insured children to average $4,552 per child. Children are on average 1.6 months more in controlled state at a cost of $0.71 more per child per month accounting for medication cost less the cost of ED visits and hospitalizations. In addition to the saved side effects of oral steroids and time hospitalized, there is one increased quality month per 13 months. Conclusions : This Markov model populated with Medicaid population exacerbation, ED, hospital and medication use and payment data provides a solid framework to examine the cost effectiveness of existing and novel targeted interventions aimed at improving medication adherence and decreasing acute care visits for Medicaid children with asthma. hma Markov model cost-savings quality of life asthma medication ratio adherence Full Text Additional Declarations No competing interests reported. Supplementary Files SupplementalMarkovtransitions.xlsx Cite Share Download PDF Status: Published Journal Publication published 23 Mar, 2026 Read the published version in Cost Effectiveness and Resource Allocation → Version 1 posted Editorial decision: Revision requested 04 Apr, 2025 Reviews received at journal 26 Aug, 2024 Reviewers agreed at journal 14 Aug, 2024 Reviewers invited by journal 09 Aug, 2024 Editor assigned by journal 08 Aug, 2024 Submission checks completed at journal 08 Aug, 2024 First submitted to journal 07 Aug, 2024 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-4876779","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":345410155,"identity":"8de3819e-28e0-4ba3-a176-522abdf321c9","order_by":0,"name":"Daniel L. 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We estimated the effects of optimal vs suboptimal AMR on exacerbations resulting in an emergency department (ED) visit or inpatient (IP) admission. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e:\u0026nbsp;We constructed an asthma Markov model using claims for a cohort of Medicaid beneficiaries aged 2‐17 years (n = 214,452) using 2013‐2014\u0026nbsp;MarketScan®\u0026nbsp;data who had at least one claim for an inhaled corticosteroid. We calculated 3‐month AMRs as the basis of transition estimates in the model. The AMRs data were transformed to reflect a one‐month Markov cycle length. Our model included five states: controlled, sub optimally controlled, inactive, IP admission, and ED. The Markov model used an overall 2‐year time horizon for 10,000 beneficiaries.\u0026nbsp;Patients entered the model in one of the five states as observed in the Medicaid data. Costs were based on 2017 Medicaid claims adjusted to reflect 2019 costs. Asthma medication cost-weight were mean payments observed for controller or rescue drugs, and costs weights for an ED visit or inpatient admission used median payments. Utilities for each state were based on existing literature.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Monthly costs for children with asthma were $214 for controlled, $32 for suboptimally controlled (attributable to fewer medication fills), $565 for months with ED visit, and $5,883 with admission. Over a 2‐year period, we estimated the 2‐year direct medical costs of asthma among Medicaid insured children to average $4,552 per child. Children are on average 1.6 months more in controlled state at a cost of $0.71 more per child per month accounting for medication cost less the cost of ED visits and hospitalizations.\u0026nbsp; In addition to the saved side effects of oral steroids and time hospitalized, there is one increased quality month per 13 months.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: This Markov model populated with Medicaid population exacerbation, ED, hospital and medication use and payment data provides a solid framework to examine the cost effectiveness of existing and novel targeted interventions aimed at improving medication adherence and decreasing acute care visits for Medicaid children with asthma.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"A Markov Model for Estimating Medication Adherence Effect on Pediatric Asthma Healthcare Use and Cost","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-04 03:47:20","doi":"10.21203/rs.3.rs-4876779/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-04T17:22:43+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-26T21:41:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"171209970843310794700053032718129751020","date":"2024-08-14T18:49:32+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-09T04:02:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-08T14:57:12+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-08T14:55:58+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cost Effectiveness and Resource Allocation","date":"2024-08-07T19:46:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cost-effectiveness-and-resource-allocation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cera","sideBox":"Learn more about [Cost Effectiveness and Resource Allocation](http://resource-allocation.biomedcentral.com)","snPcode":"12962","submissionUrl":"https://submission.nature.com/new-submission/12962/3","title":"Cost Effectiveness and Resource Allocation","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bc451a15-5867-473c-baec-151a473e6888","owner":[],"postedDate":"September 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-30T16:23:50+00:00","versionOfRecord":{"articleIdentity":"rs-4876779","link":"https://doi.org/10.1186/s12962-026-00742-z","journal":{"identity":"cost-effectiveness-and-resource-allocation","isVorOnly":false,"title":"Cost Effectiveness and Resource Allocation"},"publishedOn":"2026-03-23 16:10:36","publishedOnDateReadable":"March 23rd, 2026"},"versionCreatedAt":"2024-09-04 03:47:20","video":"","vorDoi":"10.1186/s12962-026-00742-z","vorDoiUrl":"https://doi.org/10.1186/s12962-026-00742-z","workflowStages":[]},"version":"v1","identity":"rs-4876779","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4876779","identity":"rs-4876779","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}