{"id":1450,"date":"2014-10-31T00:00:00","date_gmt":"2014-10-31T04:00:00","guid":{"rendered":"https:\/\/icesontario.wpengine.com\/journal-articles\/high-cost-health-care-users-in-ontario-canada-demographic-socio-economic-and-health-status-characteristics\/"},"modified":"2023-06-14T19:19:43","modified_gmt":"2023-06-14T23:19:43","slug":"high-cost-health-care-users-in-ontario-canada-demographic-socio-economic-and-health-status-characteristics","status":"publish","type":"journal_article","link":"https:\/\/www.ices.on.ca\/fr\/publications\/journal-articles\/high-cost-health-care-users-in-ontario-canada-demographic-socio-economic-and-health-status-characteristics\/","title":{"rendered":"High-cost healthcare users in Ontario, Canada: demographic, socio-economic, and health status characteristics"},"content":{"rendered":"<p><strong>Background<\/strong> &#x2014; Healthcare spending is overwhelmingly concentrated within a very small proportion of the population, referred to as the high-cost users (HCU). To date, research on HCU has been limited in scope, focusing mostly on those characteristics available through administrative databases, which have been largely clinical in nature, or have relied on ecological measures of socio-demographics. This study links population health surveys to administrative data, allowing for the investigation of a broad range of individual-level characteristics and provides a more thorough characterization of community-dwelling HCU across demographic, social, behavioral and clinical characteristics.<\/p>\n<p><strong>Methods<\/strong> &#x2014; The authors linked three cycles of the Canadian Community Health Survey (CCHS) to medical claim data for the years 2003&#x2013;2008 for Ontario, Canada. Participants were ranked according to gradients of cost (Top 1%, Top 2-5%, Top 6-50% and Bottom 50%) and multinomial logistic regression was used to investigate a wide range of factors, including health behaviors and socio-demographics, likely associated with HCU status.<\/p>\n<p><strong>Results<\/strong> &#x2014; Using a total sample of 91,223 adults (18 and older),&#xa0;the authors&#xa0;found that HCU status was strongly associated with being older, having multiple chronic conditions, and reporting poorer self-perceived health. Specifically, in the fully-adjusted model, poor self-rated health (vs. good) was associated with a 26-fold increase in odds of becoming a Top 1% HCU (vs. Bottom 50% user) [95% CI: (18.9, 36.9)]. Further, HCU tended to be of lower socio-economic status, former daily smokers, physically inactive, current non-drinkers, and obese.<\/p>\n<p><strong>Conclusion<\/strong> &#x2014; The results of this study have provided valuable insights into the broader characteristics of community-dwelling HCU, including unique demographic and behavioral characteristics. Additionally, strong associations with self-reported clinical variables, such as self-rated general and mental health, highlight the importance of the patient perspective for HCU. These findings have the potential to inform policies for healthcare and public health, particularly in light of increasing decision-maker attention in the sustainability of the healthcare system, improving patient outcomes and, more generally, in order to achieve the common goal of improving population health outcomes.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Background &#x2014; Healthcare spending is overwhelmingly concentrated within a very small proportion of the population, referred to as the high-cost users (HCU). To date, research on HCU has been limited in scope, focusing mostly on those characteristics available through administrative databases, which have been largely clinical in nature, or have relied on ecological measures of [&hellip;]<\/p>\n","protected":false},"template":"","migration-helper-automated":[],"migration-manual":[],"topic":[20,61,62],"migration-helper-qa-sample-set":[],"class_list":["post-1450","journal_article","type-journal_article","status-publish","hentry","topic-health-and-health-care-inequality","topic-health-economics","topic-health-services-research"],"acf":{"citation":"Rosella LC, Fitzpatrick T, Wodchis WP, Calzavara A, Manson H, Goel V. <em>BMC Health Serv Res.<\/em> 2014; 14:532. Epub 2014 Oct 31.","source_url":"https:\/\/bmchealthservres.biomedcentral.com\/articles\/10.1186\/s12913-014-0532-2","ices_scientist":[1339,1135,1253,13131],"site":[6735],"research_program":[6740],"news_release":[],"journal_article":[],"atlas":[],"research_report":[],"infographic":[],"video":[],"downloads":null,"links":null,"sitecore_item_id":"B1A5B0E6-2250-40BE-8E2F-05700B38C83F","sitecore_item_name":"High-cost-health-care-users-in-Ontario-demographic-socio-economic-and-health-status-characteristics","sitecore_field_values":"{\n  \"Title\": \"High-cost healthcare users in Ontario, Canada: demographic, socio-economic, and health status characteristics\",\n  \"Short title\": \"High-cost healthcare users in Ontario,\",\n  \"Citation\": \"<p>Rosella LC, Fitzpatrick T, Wodchis WP, Calzavara A, Manson H, Goel V. <em>BMC Health Serv Res.<\/em> 2014; 14:532. Epub 2014 Oct 31.<\/p>\",\n  \"Abstract\": \"<p><strong>Background<\/strong> &mdash; Healthcare spending is overwhelmingly concentrated within a very small proportion of the population, referred to as the high-cost users (HCU). To date, research on HCU has been limited in scope, focusing mostly on those characteristics available through administrative databases, which have been largely clinical in nature, or have relied on ecological measures of socio-demographics. This study links population health surveys to administrative data, allowing for the investigation of a broad range of individual-level characteristics and provides a more thorough characterization of community-dwelling HCU across demographic, social, behavioral and clinical characteristics.<\/p>n<p><strong>Methods<\/strong> &mdash; The authors linked three cycles of the Canadian Community Health Survey (CCHS) to medical claim data for the years 2003&ndash;2008 for Ontario, Canada. Participants were ranked according to gradients of cost (Top 1%, Top 2-5%, Top 6-50% and Bottom 50%) and multinomial logistic regression was used to investigate a wide range of factors, including health behaviors and socio-demographics, likely associated with HCU status.<\/p>n<p><strong>Results<\/strong> &mdash; Using a total sample of 91,223 adults (18 and older),&nbsp;the authors&nbsp;found that HCU status was strongly associated with being older, having multiple chronic conditions, and reporting poorer self-perceived health. Specifically, in the fully-adjusted model, poor self-rated health (vs. good) was associated with a 26-fold increase in odds of becoming a Top 1% HCU (vs. Bottom 50% user) [95% CI: (18.9, 36.9)]. Further, HCU tended to be of lower socio-economic status, former daily smokers, physically inactive, current non-drinkers, and obese.<\/p>n<p><strong>Conclusion<\/strong> &mdash; The results of this study have provided valuable insights into the broader characteristics of community-dwelling HCU, including unique demographic and behavioral characteristics. Additionally, strong associations with self-reported clinical variables, such as self-rated general and mental health, highlight the importance of the patient perspective for HCU. These findings have the potential to inform policies for healthcare and public health, particularly in light of increasing decision-maker attention in the sustainability of the healthcare system, improving patient outcomes and, more generally, in order to achieve the common goal of improving population health outcomes.<\/p>n<p><a href=\"https:\/\/bmchealthservres.biomedcentral.com\/articles\/10.1186\/s12913-014-0532-2\" title=\"opens external link\">View full text<\/a><\/p>\",\n  \"Keywords\": \"{5B386094-8417-4B93-9D08-2F46BC0458AB}|{002C9B1A-B097-4316-A26A-BA3C0A3B8FA9}|{404E8236-468F-4DA1-8BA1-F405AC36275E}\",\n  \"Research Programs\": \"{46DF28D2-EDE8-4DF2-8CC0-87CEF464E435}|{5B1AF319-EC9B-4BF0-A9CD-D066ABE49D71}\",\n  \"ICES Locations\": \"{FBE2D1B1-C0BA-423F-8D16-39466B6C1424}\",\n  \"ICES Scientists\": \"{430B2731-D3D6-4D57-9AF4-AA7626CF61B0}|{26C6C411-14DA-4E2F-9D10-9564115ADE0A}|{4BF52DAD-DEB2-4DEE-9C76-F4EFADDD454A}|{9896A0CF-1FD3-454E-B574-37CFAA5B2613}\",\n  \"Posted Date\": \"20141031T000000\",\n  \"Show on Publications Landing Page\": \"1\"\n}","previous_url":"https:\/\/www.ices.on.ca\/Publications\/Journal-Articles\/2014\/January\/High-cost-health-care-users-in-Ontario-demographic-socio-economic-and-health-status-characteristics"},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.0 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>ICES | High-cost healthcare users in Ontario, Canada: demographic, socio-economic, and health status characteristics<\/title>\n<meta name=\"description\" content=\"Background &#x2014; 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