Is Survival Better at Hospitals With Higher "End-of-Life" Treatment Intensity?
Background: Concern regarding wide variations in spending and intensive care unit use for patients at the end of life hinges on the assumption that such treatment offers little or no survival benefit. Objective: To explore the relationship between hospital "end-of-life" (EOL) treatment int...
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| creator | Barnato, Amber E. Chang, Chung-Chou H. Farrell, Max H. Lave, Judith R. Roberts, Mark S. Angus, Derek C. |
| description | Background: Concern regarding wide variations in spending and intensive care unit use for patients at the end of life hinges on the assumption that such treatment offers little or no survival benefit. Objective: To explore the relationship between hospital "end-of-life" (EOL) treatment intensity and postadmission survival. Research Design: Retrospective cohort analysis of Pennsylvania Health Care Cost Containment Council discharge data April 2001 to March 2005 linked to vital statistics data through September 2005 using hospital-level correlation, admission-level marginal structural logistic regression, and pooled logistic regression to approximate a Cox survival model. Subjects: A total of 1,021,909 patients ≥65 years old, incurring 2,216,815 admissions in 169 Pennsylvania acute care hospitals. Measures: EOL treatment intensity (a summed index of standardized intensive care unit and life-sustaining treatment use among patients with a high predicted probability of dying [PPD] at admission) and 30- and 180-day postadmission mortality. Results: There was a nonlinear negative relationship between hospital EOL treatment intensity and 30-day mortality among all admissions, although patients with higher PPD derived the greatest benefit. Compared with admission at an average intensity hospital, admission to a hospital 1 standard deviation below versus 1 standard deviation above average intensity resulted in an adjusted odds ratio of mortality for admissions at low PPD of 1.06 (1.04–1.08) versus 0.97 (0.96–0.99); average PPD: 1.06 (1.04–1.09) versus 0.97 (0.96–0.99); and high PPD: 1.09 (1.07–1.11) versus 0.97 (0.95–0.99), respectively. By 180 days, the benefits to intensity attenuated (low PPD: 1.03 [1.01–1.04] vs. 1.00 [0.98–1.01]; average PPD: 1.03 [1.02–1.05] vs. 1.00 [0.98–1.01]; and high PPD: 1.06 [1.04–1.09] vs. 1.00 [0.98–1.02]), respectively. Conclusions: Admission to higher EOL treatment intensity hospitals is associated with small gains in postadmission survival. The marginal returns to intensity diminish for admission to hospitals above average EOL treatment intensity and wane with time. |
| doi_str_mv | 10.1097/MLR.0b013e3181c161e4 |
| format | Article |
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Objective: To explore the relationship between hospital "end-of-life" (EOL) treatment intensity and postadmission survival. Research Design: Retrospective cohort analysis of Pennsylvania Health Care Cost Containment Council discharge data April 2001 to March 2005 linked to vital statistics data through September 2005 using hospital-level correlation, admission-level marginal structural logistic regression, and pooled logistic regression to approximate a Cox survival model. Subjects: A total of 1,021,909 patients ≥65 years old, incurring 2,216,815 admissions in 169 Pennsylvania acute care hospitals. Measures: EOL treatment intensity (a summed index of standardized intensive care unit and life-sustaining treatment use among patients with a high predicted probability of dying [PPD] at admission) and 30- and 180-day postadmission mortality. Results: There was a nonlinear negative relationship between hospital EOL treatment intensity and 30-day mortality among all admissions, although patients with higher PPD derived the greatest benefit. Compared with admission at an average intensity hospital, admission to a hospital 1 standard deviation below versus 1 standard deviation above average intensity resulted in an adjusted odds ratio of mortality for admissions at low PPD of 1.06 (1.04–1.08) versus 0.97 (0.96–0.99); average PPD: 1.06 (1.04–1.09) versus 0.97 (0.96–0.99); and high PPD: 1.09 (1.07–1.11) versus 0.97 (0.95–0.99), respectively. By 180 days, the benefits to intensity attenuated (low PPD: 1.03 [1.01–1.04] vs. 1.00 [0.98–1.01]; average PPD: 1.03 [1.02–1.05] vs. 1.00 [0.98–1.01]; and high PPD: 1.06 [1.04–1.09] vs. 1.00 [0.98–1.02]), respectively. Conclusions: Admission to higher EOL treatment intensity hospitals is associated with small gains in postadmission survival. The marginal returns to intensity diminish for admission to hospitals above average EOL treatment intensity and wane with time.</description><identifier>ISSN: 0025-7079</identifier><identifier>EISSN: 1537-1948</identifier><identifier>DOI: 10.1097/MLR.0b013e3181c161e4</identifier><identifier>PMID: 20057328</identifier><identifier>CODEN: MELAAD</identifier><language>eng</language><publisher>United States: Lippincott Williams & Wilkins</publisher><subject>Aged ; Cost-Benefit Analysis ; Death ; Female ; Health Care Costs ; Hospital admissions ; Hospital units ; Hospitalization ; Humans ; Intensive care ; Intensive care units ; Intensive Care Units - economics ; Life Support Care - economics ; Logistic Models ; Logistic regression ; Male ; Medicare ; Medicare - economics ; Modeling ; Mortality ; Multivariate Analysis ; Palliative care ; Patient admissions ; Pennsylvania - epidemiology ; Proportional Hazards Models ; Quality of Health Care ; Regression analysis ; Retrospective Studies ; Survival analysis ; Teaching hospitals ; Terminal Care - economics ; United States - epidemiology</subject><ispartof>Medical care, 2010-02, Vol.48 (2), p.125-132</ispartof><rights>Copyright © 2010 Lippincott Williams & Wilkins</rights><rights>2010 Lippincott Williams & Wilkins, Inc.</rights><rights>Copyright Lippincott Williams & Wilkins Feb 2010</rights><rights>Copyright © 2010 by Lippincott Williams & Wilkins 2010</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5017-3490cbcd38ef4138f4ad5b5098a0418768f063958e3175c537f720338bb24a5a3</citedby><cites>FETCH-LOGICAL-c5017-3490cbcd38ef4138f4ad5b5098a0418768f063958e3175c537f720338bb24a5a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/27798418$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/27798418$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>230,314,780,784,803,885,27924,27925,58017,58250</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/20057328$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Barnato, Amber E.</creatorcontrib><creatorcontrib>Chang, Chung-Chou H.</creatorcontrib><creatorcontrib>Farrell, Max H.</creatorcontrib><creatorcontrib>Lave, Judith R.</creatorcontrib><creatorcontrib>Roberts, Mark S.</creatorcontrib><creatorcontrib>Angus, Derek C.</creatorcontrib><title>Is Survival Better at Hospitals With Higher "End-of-Life" Treatment Intensity?</title><title>Medical care</title><addtitle>Med Care</addtitle><description>Background: Concern regarding wide variations in spending and intensive care unit use for patients at the end of life hinges on the assumption that such treatment offers little or no survival benefit. Objective: To explore the relationship between hospital "end-of-life" (EOL) treatment intensity and postadmission survival. Research Design: Retrospective cohort analysis of Pennsylvania Health Care Cost Containment Council discharge data April 2001 to March 2005 linked to vital statistics data through September 2005 using hospital-level correlation, admission-level marginal structural logistic regression, and pooled logistic regression to approximate a Cox survival model. Subjects: A total of 1,021,909 patients ≥65 years old, incurring 2,216,815 admissions in 169 Pennsylvania acute care hospitals. Measures: EOL treatment intensity (a summed index of standardized intensive care unit and life-sustaining treatment use among patients with a high predicted probability of dying [PPD] at admission) and 30- and 180-day postadmission mortality. Results: There was a nonlinear negative relationship between hospital EOL treatment intensity and 30-day mortality among all admissions, although patients with higher PPD derived the greatest benefit. Compared with admission at an average intensity hospital, admission to a hospital 1 standard deviation below versus 1 standard deviation above average intensity resulted in an adjusted odds ratio of mortality for admissions at low PPD of 1.06 (1.04–1.08) versus 0.97 (0.96–0.99); average PPD: 1.06 (1.04–1.09) versus 0.97 (0.96–0.99); and high PPD: 1.09 (1.07–1.11) versus 0.97 (0.95–0.99), respectively. By 180 days, the benefits to intensity attenuated (low PPD: 1.03 [1.01–1.04] vs. 1.00 [0.98–1.01]; average PPD: 1.03 [1.02–1.05] vs. 1.00 [0.98–1.01]; and high PPD: 1.06 [1.04–1.09] vs. 1.00 [0.98–1.02]), respectively. Conclusions: Admission to higher EOL treatment intensity hospitals is associated with small gains in postadmission survival. The marginal returns to intensity diminish for admission to hospitals above average EOL treatment intensity and wane with time.</description><subject>Aged</subject><subject>Cost-Benefit Analysis</subject><subject>Death</subject><subject>Female</subject><subject>Health Care Costs</subject><subject>Hospital admissions</subject><subject>Hospital units</subject><subject>Hospitalization</subject><subject>Humans</subject><subject>Intensive care</subject><subject>Intensive care units</subject><subject>Intensive Care Units - economics</subject><subject>Life Support Care - economics</subject><subject>Logistic Models</subject><subject>Logistic regression</subject><subject>Male</subject><subject>Medicare</subject><subject>Medicare - economics</subject><subject>Modeling</subject><subject>Mortality</subject><subject>Multivariate Analysis</subject><subject>Palliative care</subject><subject>Patient admissions</subject><subject>Pennsylvania - epidemiology</subject><subject>Proportional Hazards Models</subject><subject>Quality of Health Care</subject><subject>Regression analysis</subject><subject>Retrospective Studies</subject><subject>Survival analysis</subject><subject>Teaching hospitals</subject><subject>Terminal Care - economics</subject><subject>United States - epidemiology</subject><issn>0025-7079</issn><issn>1537-1948</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpdUU1vEzEUtBAVTQv_ANAqF07bPn-t7QsVVIVECiBBEUfLu_F2HTbrYHtT9d_XUfpFfbH83sxoxoPQWwwnGJQ4_bb4eQI1YGoplrjBFbbsBZpgTkWJFZMv0QSA8FKAUIfoKMYVABaUk1fokABwQYmcoO_zWPwaw9ZtTV98tinZUJhUzHzcuGT6WPxxqStm7qrLi-nFsCx9Wy5ca6fFZbAmre2QivmQ7BBdujl7jQ7azLJv7u5j9PvLxeX5rFz8-Do__7QoG55NlJQpaOpmSaVtGaayZWbJaw5KGmBYikq2UFHFZc4meJMjtYIApbKuCTPc0GP0ca-7Geu1XTbZRTC93gS3NuFGe-P0_5vBdfrKbzUVlVJUZYEPdwLB_xttTHrtYmP73gzWj1ELyggXFSYZOX2GXPkxDDmdJiAYp0B2cmwPaoKPMdj2wQoGvatL57r087oy7f3TGA-k-34eda99n6uJf_vx2gbdWdOnTkM-vOJQEsC56_wqdyORae_2tFVMPjzKCqFk_l96Cyt-qSE</recordid><startdate>20100201</startdate><enddate>20100201</enddate><creator>Barnato, Amber E.</creator><creator>Chang, Chung-Chou H.</creator><creator>Farrell, Max H.</creator><creator>Lave, Judith R.</creator><creator>Roberts, Mark S.</creator><creator>Angus, Derek C.</creator><general>Lippincott Williams & Wilkins</general><general>Lippincott Williams & Wilkins, Inc</general><general>Lippincott Williams & Wilkins Ovid Technologies</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>K9.</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20100201</creationdate><title>Is Survival Better at Hospitals With Higher "End-of-Life" Treatment Intensity?</title><author>Barnato, Amber E. ; Chang, Chung-Chou H. ; Farrell, Max H. ; Lave, Judith R. ; Roberts, Mark S. ; Angus, Derek C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5017-3490cbcd38ef4138f4ad5b5098a0418768f063958e3175c537f720338bb24a5a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Aged</topic><topic>Cost-Benefit Analysis</topic><topic>Death</topic><topic>Female</topic><topic>Health Care Costs</topic><topic>Hospital admissions</topic><topic>Hospital units</topic><topic>Hospitalization</topic><topic>Humans</topic><topic>Intensive care</topic><topic>Intensive care units</topic><topic>Intensive Care Units - economics</topic><topic>Life Support Care - economics</topic><topic>Logistic Models</topic><topic>Logistic regression</topic><topic>Male</topic><topic>Medicare</topic><topic>Medicare - economics</topic><topic>Modeling</topic><topic>Mortality</topic><topic>Multivariate Analysis</topic><topic>Palliative care</topic><topic>Patient admissions</topic><topic>Pennsylvania - epidemiology</topic><topic>Proportional Hazards Models</topic><topic>Quality of Health Care</topic><topic>Regression analysis</topic><topic>Retrospective Studies</topic><topic>Survival analysis</topic><topic>Teaching hospitals</topic><topic>Terminal Care - economics</topic><topic>United States - epidemiology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Barnato, Amber E.</creatorcontrib><creatorcontrib>Chang, Chung-Chou H.</creatorcontrib><creatorcontrib>Farrell, Max H.</creatorcontrib><creatorcontrib>Lave, Judith R.</creatorcontrib><creatorcontrib>Roberts, Mark S.</creatorcontrib><creatorcontrib>Angus, Derek C.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Medical care</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Barnato, Amber E.</au><au>Chang, Chung-Chou H.</au><au>Farrell, Max H.</au><au>Lave, Judith R.</au><au>Roberts, Mark S.</au><au>Angus, Derek C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Is Survival Better at Hospitals With Higher "End-of-Life" Treatment Intensity?</atitle><jtitle>Medical care</jtitle><addtitle>Med Care</addtitle><date>2010-02-01</date><risdate>2010</risdate><volume>48</volume><issue>2</issue><spage>125</spage><epage>132</epage><pages>125-132</pages><issn>0025-7079</issn><eissn>1537-1948</eissn><coden>MELAAD</coden><abstract>Background: Concern regarding wide variations in spending and intensive care unit use for patients at the end of life hinges on the assumption that such treatment offers little or no survival benefit. Objective: To explore the relationship between hospital "end-of-life" (EOL) treatment intensity and postadmission survival. Research Design: Retrospective cohort analysis of Pennsylvania Health Care Cost Containment Council discharge data April 2001 to March 2005 linked to vital statistics data through September 2005 using hospital-level correlation, admission-level marginal structural logistic regression, and pooled logistic regression to approximate a Cox survival model. Subjects: A total of 1,021,909 patients ≥65 years old, incurring 2,216,815 admissions in 169 Pennsylvania acute care hospitals. Measures: EOL treatment intensity (a summed index of standardized intensive care unit and life-sustaining treatment use among patients with a high predicted probability of dying [PPD] at admission) and 30- and 180-day postadmission mortality. Results: There was a nonlinear negative relationship between hospital EOL treatment intensity and 30-day mortality among all admissions, although patients with higher PPD derived the greatest benefit. Compared with admission at an average intensity hospital, admission to a hospital 1 standard deviation below versus 1 standard deviation above average intensity resulted in an adjusted odds ratio of mortality for admissions at low PPD of 1.06 (1.04–1.08) versus 0.97 (0.96–0.99); average PPD: 1.06 (1.04–1.09) versus 0.97 (0.96–0.99); and high PPD: 1.09 (1.07–1.11) versus 0.97 (0.95–0.99), respectively. By 180 days, the benefits to intensity attenuated (low PPD: 1.03 [1.01–1.04] vs. 1.00 [0.98–1.01]; average PPD: 1.03 [1.02–1.05] vs. 1.00 [0.98–1.01]; and high PPD: 1.06 [1.04–1.09] vs. 1.00 [0.98–1.02]), respectively. Conclusions: Admission to higher EOL treatment intensity hospitals is associated with small gains in postadmission survival. The marginal returns to intensity diminish for admission to hospitals above average EOL treatment intensity and wane with time.</abstract><cop>United States</cop><pub>Lippincott Williams & Wilkins</pub><pmid>20057328</pmid><doi>10.1097/MLR.0b013e3181c161e4</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Aged Cost-Benefit Analysis Death Female Health Care Costs Hospital admissions Hospital units Hospitalization Humans Intensive care Intensive care units Intensive Care Units - economics Life Support Care - economics Logistic Models Logistic regression Male Medicare Medicare - economics Modeling Mortality Multivariate Analysis Palliative care Patient admissions Pennsylvania - epidemiology Proportional Hazards Models Quality of Health Care Regression analysis Retrospective Studies Survival analysis Teaching hospitals Terminal Care - economics United States - epidemiology |
| title | Is Survival Better at Hospitals With Higher "End-of-Life" Treatment Intensity? |
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