{"id":5191,"date":"2012-10-09T00:00:00","date_gmt":"2012-10-09T04:00:00","guid":{"rendered":"https:\/\/icesontario.wpengine.com\/journal-articles\/comparing-methods-to-calculate-hospital-specific-rates-of-early-death-or-urgent-readmission\/"},"modified":"2023-06-14T19:25:46","modified_gmt":"2023-06-14T23:25:46","slug":"comparing-methods-to-calculate-hospital-specific-rates-of-early-death-or-urgent-readmission","status":"publish","type":"journal_article","link":"https:\/\/www.ices.on.ca\/fr\/publications\/journal-articles\/comparing-methods-to-calculate-hospital-specific-rates-of-early-death-or-urgent-readmission\/","title":{"rendered":"Comparing methods to calculate hospital-specific rates of early death or urgent readmission"},"content":{"rendered":"<p><strong>Background<\/strong> &#x2014; Hospital readmissions are important patient outcomes that can be accurately captured with routinely collected administrative data. Hospital-specific readmission rates have been reported as a quality-of-care indicator. However, the extent to which these measures vary with different calculation methods is uncertain.<\/p>\n<p><strong>Methods<\/strong> &#x2014; The researchers identified all discharges from Ontario hospitals from 2005 to 2010 and determined whether patients died or were urgently readmitted within 30 days. For each hospital, the researchers calculated 4 distinct observed-to-expected ratios, estimating the expected number of events using different adjustments for confounders (age and sex vs. complete) and different units of analysis (all admissions vs. single admission per patient).<\/p>\n<p><strong>Results<\/strong> &#x2014; The researchers included 3,148,648 admissions to hospital for 1,802,704 patients in 162 hospitals. Ratios adjusted for age and sex alone had the greatest variation. Within hospitals, ranges of the 4 ratios averaged 31% of the overall estimate. Readmission ratios adjusted for age and sex showed the lowest correlation (Spearman correlation coefficient 0.48&#x2013;0.68). Hospital rankings based on the different measures had an average range of 47.4 (standard deviation 32.2) out of 162.<\/p>\n<p><strong>Interpretation<\/strong> &#x2014; The researchers found notable variation in rates of death or urgent readmission within 30 days based on the extent of adjustment for confounders and the unit of analysis. Slight changes in the methods used to calculate hospital-specific readmission rates influence their values and the consequent rankings of hospitals. Our results highlight the caution required when comparing hospital performance using rates of death or urgent readmission within 30 days.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Background &#x2014; Hospital readmissions are important patient outcomes that can be accurately captured with routinely collected administrative data. Hospital-specific readmission rates have been reported as a quality-of-care indicator. However, the extent to which these measures vary with different calculation methods is uncertain. Methods &#x2014; The researchers identified all discharges from Ontario hospitals from 2005 to [&hellip;]<\/p>\n","protected":false},"template":"","migration-helper-automated":[],"migration-manual":[],"topic":[24,62],"migration-helper-qa-sample-set":[],"class_list":["post-5191","journal_article","type-journal_article","status-publish","hentry","topic-acute-and-emergency-services","topic-health-services-research"],"acf":{"citation":"van Walraven C, Wong J, Hawken S, Forster AJ. <em>CMAJ<\/em>. 2012; 184(15):E810-7. Epub 2012 Oct 9.","source_url":"http:\/\/www.cmaj.ca\/content\/184\/15\/E810.long","ices_scientist":[1119,1231,1260],"site":[6734],"research_program":[6740],"news_release":[7482],"journal_article":[],"atlas":[],"research_report":[],"infographic":[],"video":[],"downloads":null,"links":null,"sitecore_item_id":"E6D941C3-C028-46BB-AEBF-22D299D28F65","sitecore_item_name":"Comparing-methods-to-calculate-hospital-specific-rates-of-early-death-or-urgent-readmission","sitecore_field_values":"{\n  \"Title\": \"Comparing methods to calculate hospital-specific rates of early death or urgent readmission\",\n  \"Short title\": \"Comparing methods to calculate\",\n  \"Citation\": \"<p>van Walraven C, Wong J, Hawken S, Forster AJ. <em>CMAJ<\/em>. 2012; 184(15):E810-7. Epub 2012 Oct 9.<\/p>\",\n  \"Abstract\": \"<p><strong>Background<\/strong> &mdash; Hospital readmissions are important patient outcomes that can be accurately captured with routinely collected administrative data. Hospital-specific readmission rates have been reported as a quality-of-care indicator. However, the extent to which these measures vary with different calculation methods is uncertain.<\/p>n<p><strong>Methods<\/strong> &mdash; The researchers identified all discharges from Ontario hospitals from 2005 to 2010 and determined whether patients died or were urgently readmitted within 30 days. For each hospital, the researchers calculated 4 distinct observed-to-expected ratios, estimating the expected number of events using different adjustments for confounders (age and sex vs. complete) and different units of analysis (all admissions vs. single admission per patient).<\/p>n<p><strong>Results<\/strong> &mdash; The researchers included 3,148,648 admissions to hospital for 1,802,704 patients in 162 hospitals. Ratios adjusted for age and sex alone had the greatest variation. Within hospitals, ranges of the 4 ratios averaged 31% of the overall estimate. Readmission ratios adjusted for age and sex showed the lowest correlation (Spearman correlation coefficient 0.48&ndash;0.68). Hospital rankings based on the different measures had an average range of 47.4 (standard deviation 32.2) out of 162.<\/p>n<p><strong>Interpretation<\/strong> &mdash; The researchers found notable variation in rates of death or urgent readmission within 30 days based on the extent of adjustment for confounders and the unit of analysis. Slight changes in the methods used to calculate hospital-specific readmission rates influence their values and the consequent rankings of hospitals. Our results highlight the caution required when comparing hospital performance using rates of death or urgent readmission within 30 days.<\/p>n<p><a href=\"http:\/\/www.cmaj.ca\/content\/184\/15\/E810.long\" title=\"Opens external link\">View full text<\/a><\/p>\",\n  \"Keywords\": \"{E93E0287-ACCB-4952-BB98-00EF52815525}|{95BBE8DE-D10D-45F0-8843-79306044E334}|{53FC76BF-785B-4A1C-805E-1E03634BE9CF}\",\n  \"Related Products\": \"<h2>News Release<\/h2>rn<h3><a href=\"~\/link.aspx?_id=63C3DE62B3F34250BD5EAF36FCAD5B76&amp;_z=z\">Hospital rankings dramatically affected by calculation methods<\/a><\/h3>\",\n  \"Research Programs\": \"{5B1AF319-EC9B-4BF0-A9CD-D066ABE49D71}|{46DF28D2-EDE8-4DF2-8CC0-87CEF464E435}\",\n  \"ICES Locations\": \"{0AD77E2C-C883-4E93-8B9A-40B82D50E3A5}\",\n  \"ICES Scientists\": \"{372EE381-9B1A-49F5-AC1B-0D8675558A8D}|{1F2D3B95-23E8-4B8B-9D60-D6E77DB0A4C8}|{C3E4F5EF-B2E3-40B3-8FFB-9BE638B8F35B}\",\n  \"Posted Date\": \"20121009T000000\"\n}","previous_url":"https:\/\/www.ices.on.ca\/Publications\/Journal-Articles\/2012\/January\/Comparing-methods-to-calculate-hospital-specific-rates-of-early-death-or-urgent-readmission"},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>ICES | Comparing methods to calculate hospital-specific rates of early death or urgent readmission<\/title>\n<meta name=\"description\" content=\"Background &#x2014; 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