{"id":4413,"date":"2015-07-22T00:00:00","date_gmt":"2015-07-22T04:00:00","guid":{"rendered":"https:\/\/icesontario.wpengine.com\/journal-articles\/impact-of-diabetes-on-healthcare-costs-in-a-population-based-cohort-a-cost-analysis\/"},"modified":"2023-06-14T19:59:41","modified_gmt":"2023-06-14T23:59:41","slug":"impact-of-diabetes-on-healthcare-costs-in-a-population-based-cohort-a-cost-analysis","status":"publish","type":"journal_article","link":"https:\/\/www.ices.on.ca\/fr\/publications\/journal-articles\/impact-of-diabetes-on-healthcare-costs-in-a-population-based-cohort-a-cost-analysis\/","title":{"rendered":"Impact of diabetes on healthcare costs in a population-based cohort: a cost analysis"},"content":{"rendered":"<p><strong>Aims<\/strong> &#x2014; To estimate the healthcare costs attributable to diabetes in Ontario, Canada using a propensity-matched control design and health administrative data from the perspective of a single-payer healthcare system.<\/p>\n<p><strong>Methods<\/strong> &#x2014; Incident diabetes cases among adults in Ontario were identified from the Ontario Diabetes Database between 2004 and 2012 and matched 1:3 to control subjects without diabetes identified in health administrative databases on the basis of sociodemographics and propensity score. Using a comprehensive source of administrative databases, direct per-person costs (Canadian dollars 2012) were calculated. A cost analysis was performed to calculate the attributable costs of diabetes; i.e. the difference of costs between patients with diabetes and control subjects without diabetes.<\/p>\n<p><strong>Results<\/strong> &#x2014; The study sample included 699 042 incident diabetes cases. The costs attributable to diabetes were greatest in the year after diagnosis [C&#x24;3,785 (95% CI 3708, 3862) per person for women and C&#x24;3,826 (95% CI 3751, 3901) for men], increasing substantially for older age groups and patients who died during follow-up. After accounting for baseline comorbidities, attributable costs were primarily incurred through inpatient acute hospitalizations, physician visits and prescription medications and assistive devices.<\/p>\n<p><strong>Conclusions<\/strong> &#x2014; The excess healthcare costs attributable to diabetes are substantial and pose a significant clinical and public health challenge. This burden is an important consideration for decision-makers, particularly given increasing concern over the sustainability of the healthcare system, aging population structure and increasing prevalence of diabetic risk factors, such as obesity.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Aims &#x2014; To estimate the healthcare costs attributable to diabetes in Ontario, Canada using a propensity-matched control design and health administrative data from the perspective of a single-payer healthcare system. Methods &#x2014; Incident diabetes cases among adults in Ontario were identified from the Ontario Diabetes Database between 2004 and 2012 and matched 1:3 to control [&hellip;]<\/p>\n","protected":false},"template":"","migration-helper-automated":[],"migration-manual":[],"topic":[50,61],"migration-helper-qa-sample-set":[],"class_list":["post-4413","journal_article","type-journal_article","status-publish","hentry","topic-endocrinology","topic-health-economics"],"acf":{"citation":"Rosella LC, Lebenbaum M, Fitzpatrick T, O&apos;Reilly D, Wang J, Booth GL, Stukel TA, Wodchis WP. <em>Diabet Med<\/em>. 2016; 33(3):395-403. Epub 2015 Jul 22.","source_url":"https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC5014203\/","ices_scientist":[1339,1175,1372,1135,13131],"site":[6735,6733],"research_program":[6740,6746],"news_release":[7844],"journal_article":[],"atlas":[],"research_report":[],"infographic":[],"video":[],"downloads":null,"links":null,"sitecore_item_id":"F6497240-C100-4700-A85A-BC4F42ED1617","sitecore_item_name":"Impact-of-diabetes-on-healthcare-costs-in-a-population-based-cohort-a-cost-analysis","sitecore_field_values":"{\n  \"__Valid from\": \"20170726T155443\",\n  \"Title\": \"Impact of diabetes on healthcare costs in a population-based cohort: a cost analysis\",\n  \"Short title\": \"Impact of diabetes on healthcare\",\n  \"Summary\": \"The study objective was to estimate the healthcare costs attributable to diabetes in Ontario, using a propensity-matched control design and health administrative data.\",\n  \"Citation\": \"<p>Rosella LC, Lebenbaum M, Fitzpatrick T, O'Reilly D, Wang J, Booth GL, Stukel TA, Wodchis WP. <em>Diabet Med<\/em>. 2016; 33(3):395-403. Epub 2015 Jul 22.<\/p>\",\n  \"Abstract\": \"<p><strong>Aims<\/strong> &mdash; To estimate the healthcare costs attributable to diabetes in Ontario, Canada using a propensity-matched control design and health administrative data from the perspective of a single-payer healthcare system.<\/p>n<p><strong>Methods<\/strong> &mdash; Incident diabetes cases among adults in Ontario were identified from the Ontario Diabetes Database between 2004 and 2012 and matched 1:3 to control subjects without diabetes identified in health administrative databases on the basis of sociodemographics and propensity score. Using a comprehensive source of administrative databases, direct per-person costs (Canadian dollars 2012) were calculated. A cost analysis was performed to calculate the attributable costs of diabetes; i.e. the difference of costs between patients with diabetes and control subjects without diabetes.<\/p>n<p><strong>Results<\/strong> &mdash; The study sample included 699 042 incident diabetes cases. The costs attributable to diabetes were greatest in the year after diagnosis [C$3,785 (95% CI 3708, 3862) per person for women and C$3,826 (95% CI 3751, 3901) for men], increasing substantially for older age groups and patients who died during follow-up. After accounting for baseline comorbidities, attributable costs were primarily incurred through inpatient acute hospitalizations, physician visits and prescription medications and assistive devices.<\/p>n<p><strong>Conclusions<\/strong> &mdash; The excess healthcare costs attributable to diabetes are substantial and pose a significant clinical and public health challenge. This burden is an important consideration for decision-makers, particularly given increasing concern over the sustainability of the healthcare system, aging population structure and increasing prevalence of diabetic risk factors, such as obesity.<\/p>n<p><a href=\"https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC5014203\/\" title=\"opens external link\">View full text<\/a><\/p>\",\n  \"Keywords\": \"{26EB1DB1-6793-4CB3-9CFB-DFF37E09FB5A}|{5B386094-8417-4B93-9D08-2F46BC0458AB}\",\n  \"Related Products\": \"<h2>NEWS RELEASE<\/h2>rn<h3><a href=\"~\/link.aspx?_id=493719518F0447F6B983AD5695045E48&amp;_z=z\">Large Canadian study finds healthcare cost of people living with diabetes more than double that of people without the disease <\/a><\/h3>rn<h2>ICES IN THE NEWS<\/h2>rn<h3><a href=\"http:\/\/www.ctvnews.ca\/health\/health-costs-for-diabetes-expected-to-rise-as-population-ages-researcher-1.2520583\" title=\"External link to CTV News website opens in new window\" target=\"_blank\">Health costs for diabetes expected to rise as population ages: researcher<\/a><\/h3>\",\n  \"Research Programs\": \"{5B1AF319-EC9B-4BF0-A9CD-D066ABE49D71}|{46DF28D2-EDE8-4DF2-8CC0-87CEF464E435}|{CFE36C89-C969-4C23-B5E4-1BA9E5BDC273}\",\n  \"ICES Locations\": \"{FBE2D1B1-C0BA-423F-8D16-39466B6C1424}|{4FCAABBA-14A5-42E6-8F33-BC6C2F1D9908}\",\n  \"ICES Scientists\": \"{430B2731-D3D6-4D57-9AF4-AA7626CF61B0}|{98B8617F-C6B9-4032-9C0D-7053D3651ABA}|{A0978F87-1C10-4E62-A833-89616146CA59}|{26C6C411-14DA-4E2F-9D10-9564115ADE0A}|{9896A0CF-1FD3-454E-B574-37CFAA5B2613}\",\n  \"Posted Date\": \"20150722T000000\",\n  \"Show on Publications Landing Page\": \"1\"\n}","previous_url":"https:\/\/www.ices.on.ca\/Publications\/Journal-Articles\/2015\/January\/Impact-of-diabetes-on-healthcare-costs-in-a-population-based-cohort-a-cost-analysis"},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>ICES | Impact of diabetes on healthcare costs in a population-based cohort: a cost analysis<\/title>\n<meta name=\"description\" content=\"Aims &#x2014; 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