{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T17:05:02Z","timestamp":1784135102660,"version":"3.55.0"},"reference-count":25,"publisher":"The Journal of Health Economics and Outcomes Research","issue":"2","license":[{"start":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T00:00:00Z","timestamp":1784073600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["jheor.org"],"crossmark-restriction":true},"short-container-title":[],"abstract":"<jats:p>\n                    <jats:bold>Background:<\/jats:bold>\n                    Ehlers-Danlos Syndrome (EDS) is a rare connective tissue disorder associated with substantial clinical complexity and healthcare utilization. Despite increasing recognition of EDS, little is known about its economic burden in the United States.\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>Objective:<\/jats:bold>\n                    To assess the all-cause healthcare costs for individuals with newly diagnosed EDS during the pre-diagnosis year and the first 2 years post-diagnosis.\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>Methods:<\/jats:bold>\n                    A retrospective cohort study was conducted using the Merative\u2122 MarketScan\u00ae Commercial Claims and Encounters Database (2016-2022). Newly diagnosed patients were identified using ICD-10-CM codes, with the first observed diagnosis defined as the index date. Continuous enrollment for 12 months pre-index and 24 months post-index was required. Costs represented gross payments to providers, adjusted to 2022 US dollars. Outcomes included inpatient, outpatient, and pharmacy expenditures, with outpatient services further stratified. Two-part models were estimated: a logistic regression for the probability of incurring costs and a GLM gamma model with log link for cost intensity among users.\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>Results:<\/jats:bold>\n                    The study included 4765 patients (mean age, 28.8 years; 78% female). Total annual costs rose from $19\u2009733 pre-index to $28\u2009922 in the first year post-diagnosis, then declined to $21\u2009804 in the second year, though remaining above baseline. Outpatient and pharmacy services were the largest contributors, while inpatient admissions, though less frequent, were resource intensive when they occurred. Two-part models showed that the likelihood of incurring any cost was significantly higher in Year 1 (\u03b2\u2009=\u20094.15, P\u2009&lt;\u2009.001) but not in Year 2 (\u03b2\u2009=\u2009\u20130.03, P\u2009=\u2009.845). Among cost users, expenditures remained elevated in both Year 1 (\u03b2\u2009=\u20090.41, P\u2009&lt;\u2009.001) and Year 2 (\u03b2\u2009=\u20090.13, P\u2009&lt;\u2009.001). Female sex and higher Charlson Comorbidity Index scores were associated with significantly greater costs. Costs peaked immediately after diagnosis, driven by outpatient and pharmacy use, and remained elevated in Year 2. Patient characteristics, particularly comorbidities, strongly influenced expenditures.\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>Conclusions:<\/jats:bold>\n                    Healthcare costs for patients with EDS peaked during the first year following diagnosis and remained elevated in the second year relative to pre-diagnosis levels. These findings highlight the substantial and persistent economic impact of EDS on the healthcare system.\n                  <\/jats:p>","DOI":"10.36469\/001c.145941","type":"journal-article","created":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T15:55:26Z","timestamp":1784130926000},"update-policy":"https:\/\/doi.org\/10.36469\/00001","source":"Crossref","is-referenced-by-count":0,"title":["Understanding Ehlers-Danlos Syndrome: A Claims-Based Analysis of Healthcare Cost Patterns"],"prefix":"10.36469","volume":"13","author":[{"given":"Samson A.","family":"Oyediran","sequence":"first","affiliation":[{"name":"The University of Texas Health Science Center at Houston, Texas"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Youngran","family":"Kim","sequence":"additional","affiliation":[{"name":"University of Texas Health Science Center at Houston","department":["UTHealth School of Public Health Center for Health Care Data"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhanna","family":"Novikov","sequence":"additional","affiliation":[{"name":"University of Texas Health Science Center at Houston","department":["UTHealth School of Public Health Center for Health Care Data"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Trudy M.","family":"Krause","sequence":"additional","affiliation":[{"name":"University of Texas Health Science Center at Houston","department":["UTHealth School of Public Health Center for Health Care Data"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"22273","published-online":{"date-parts":[[2026,7,15]]},"reference":[{"issue":"2","key":"ref1","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1001\/jamapediatrics.2014.2320","article-title":"Analyzing the effect of state legislation on health care utilization for children with concussion","volume":"169","author":"T. 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