Disentangling the contribution of hospitals and municipalities for understanding patient level differences in one-year mortality risk after hip-fracture: A cross-classified multilevel analysis in Sweden
Background One-year mortality after hip-fracture is a widely used outcome measure when comparing hospital care performance. However, traditional analyses do not explicitly consider the referral of patients to municipality care after just a few days of hospitalization. Furthermore, traditional analys...
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| description | Background One-year mortality after hip-fracture is a widely used outcome measure when comparing hospital care performance. However, traditional analyses do not explicitly consider the referral of patients to municipality care after just a few days of hospitalization. Furthermore, traditional analyses investigates hospital (or municipality) variation in patient outcomes in isolation rather than as a component of the underlying patient variation. We therefore aimed to extend the traditional approach to simultaneously estimate both case-mix adjusted hospital and municipality comparisons in order to disentangle the amount of the total patient variation in clinical outcomes that was attributable to the hospital and municipality level, respectively. Methods We determined 1-year mortality risk in patients aged 65 or above with hip fractures registered in Sweden between 2011 and 2014. We performed cross-classified multilevel analysis with 54,999 patients nested within 54 hospitals and 290 municipalities. We adjusted for individual demographic, socioeconomic and clinical characteristics. To quantify the size of the hospital and municipality variation we calculated the variance partition coefficient (VPC) and the area under the receiver operator characteristic curve (AUC). Results The overall 1-year mortality rate was 25.1%. The case-mix adjusted rates varied from 21.7% to 26.5% for the 54 hospitals, and from 18.9% to 29.5% for the 290 municipalities. The VPC was just 0.2% for the hospital and just 0.1% for the municipality level. Patient sociodemographic and clinical characteristics were strong predictors of 1-year mortality (AUC = 0.716), but adding the hospital and municipality levels in the cross-classified model had a minor influence (AUC = 0.718). Conclusions Overall in Sweden, one-year mortality after hip-fracture is rather high. However, only a minor part of the patient variation is explained by the hospital and municipality levels. Therefore, a possible intervention should be nation-wide rather than directed to specific hospitals or municipalities. |
| doi_str_mv | 10.1371/journal.pone.0234041 |
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However, traditional analyses do not explicitly consider the referral of patients to municipality care after just a few days of hospitalization. Furthermore, traditional analyses investigates hospital (or municipality) variation in patient outcomes in isolation rather than as a component of the underlying patient variation. We therefore aimed to extend the traditional approach to simultaneously estimate both case-mix adjusted hospital and municipality comparisons in order to disentangle the amount of the total patient variation in clinical outcomes that was attributable to the hospital and municipality level, respectively. Methods We determined 1-year mortality risk in patients aged 65 or above with hip fractures registered in Sweden between 2011 and 2014. We performed cross-classified multilevel analysis with 54,999 patients nested within 54 hospitals and 290 municipalities. We adjusted for individual demographic, socioeconomic and clinical characteristics. To quantify the size of the hospital and municipality variation we calculated the variance partition coefficient (VPC) and the area under the receiver operator characteristic curve (AUC). Results The overall 1-year mortality rate was 25.1%. The case-mix adjusted rates varied from 21.7% to 26.5% for the 54 hospitals, and from 18.9% to 29.5% for the 290 municipalities. The VPC was just 0.2% for the hospital and just 0.1% for the municipality level. Patient sociodemographic and clinical characteristics were strong predictors of 1-year mortality (AUC = 0.716), but adding the hospital and municipality levels in the cross-classified model had a minor influence (AUC = 0.718). Conclusions Overall in Sweden, one-year mortality after hip-fracture is rather high. However, only a minor part of the patient variation is explained by the hospital and municipality levels. Therefore, a possible intervention should be nation-wide rather than directed to specific hospitals or municipalities.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0234041</identifier><identifier>PMID: 32492053</identifier><language>eng</language><publisher>San Francisco: Public Library of Science</publisher><subject>Biology and Life Sciences ; Bone surgery ; Care and treatment ; Coefficient of variation ; Demographic aspects ; Disposable income ; Education ; Elderly patients ; Epidemiology ; Ethics ; Fractures ; Fractures (Injuries) ; Health care policy ; Health Care Service and Management, Health Policy and Services and Health Economy ; Health Sciences ; Hip ; Hip fractures ; Hospitals ; Hälso- och sjukvårdsorganisation, hälsopolitik och hälsoekonomi ; Hälsovetenskap ; Income distribution ; Isolation ; Levels ; Mathematical analysis ; Medical and Health Sciences ; Medicin och hälsovetenskap ; Medicine and Health Sciences ; Mortality ; Municipalities ; Patient outcomes ; Patients ; People and places ; Physical Sciences ; Population ; Research and Analysis Methods ; Sociodemographics ; Studies ; Variables ; Variation</subject><ispartof>PloS one, 2020-06, Vol.15 (6), p.e0234041-e0234041</ispartof><rights>COPYRIGHT 2020 Public Library of Science</rights><rights>2020 Kristensen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2020 Kristensen et al 2020 Kristensen et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c6531-292748314bd8b7dfa4ce9a2d3d36c8639d93e36fa26cc38c08978ec3a19529453</citedby><cites>FETCH-LOGICAL-c6531-292748314bd8b7dfa4ce9a2d3d36c8639d93e36fa26cc38c08978ec3a19529453</cites><orcidid>0000-0001-8379-9708 ; 0000-0001-5473-9386 ; 0000-0003-1486-745X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7269247/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7269247/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,550,723,776,780,860,881,2095,2914,23846,27903,27904,53769,53771,79346,79347</link.rule.ids><backlink>$$Uhttps://lup.lub.lu.se/record/0315ee9b-cbbb-45fa-b695-3328786a7c63$$DView record from Swedish Publication Index$$Hfree_for_read</backlink></links><search><contributor>Garcia de Frutos, Pablo</contributor><creatorcontrib>Kristensen, Pia Kjær</creatorcontrib><creatorcontrib>Perez-Vicente, Raquel</creatorcontrib><creatorcontrib>Leckie, George</creatorcontrib><creatorcontrib>Johnsen, Søren Paaske</creatorcontrib><creatorcontrib>Merlo, Juan</creatorcontrib><creatorcontrib>Garcia de Frutos, Pablo</creatorcontrib><title>Disentangling the contribution of hospitals and municipalities for understanding patient level differences in one-year mortality risk after hip-fracture: A cross-classified multilevel analysis in Sweden</title><title>PloS one</title><description>Background One-year mortality after hip-fracture is a widely used outcome measure when comparing hospital care performance. However, traditional analyses do not explicitly consider the referral of patients to municipality care after just a few days of hospitalization. Furthermore, traditional analyses investigates hospital (or municipality) variation in patient outcomes in isolation rather than as a component of the underlying patient variation. We therefore aimed to extend the traditional approach to simultaneously estimate both case-mix adjusted hospital and municipality comparisons in order to disentangle the amount of the total patient variation in clinical outcomes that was attributable to the hospital and municipality level, respectively. Methods We determined 1-year mortality risk in patients aged 65 or above with hip fractures registered in Sweden between 2011 and 2014. We performed cross-classified multilevel analysis with 54,999 patients nested within 54 hospitals and 290 municipalities. We adjusted for individual demographic, socioeconomic and clinical characteristics. To quantify the size of the hospital and municipality variation we calculated the variance partition coefficient (VPC) and the area under the receiver operator characteristic curve (AUC). Results The overall 1-year mortality rate was 25.1%. The case-mix adjusted rates varied from 21.7% to 26.5% for the 54 hospitals, and from 18.9% to 29.5% for the 290 municipalities. The VPC was just 0.2% for the hospital and just 0.1% for the municipality level. Patient sociodemographic and clinical characteristics were strong predictors of 1-year mortality (AUC = 0.716), but adding the hospital and municipality levels in the cross-classified model had a minor influence (AUC = 0.718). Conclusions Overall in Sweden, one-year mortality after hip-fracture is rather high. However, only a minor part of the patient variation is explained by the hospital and municipality levels. Therefore, a possible intervention should be nation-wide rather than directed to specific hospitals or municipalities.</description><subject>Biology and Life Sciences</subject><subject>Bone surgery</subject><subject>Care and treatment</subject><subject>Coefficient of variation</subject><subject>Demographic aspects</subject><subject>Disposable income</subject><subject>Education</subject><subject>Elderly patients</subject><subject>Epidemiology</subject><subject>Ethics</subject><subject>Fractures</subject><subject>Fractures (Injuries)</subject><subject>Health care policy</subject><subject>Health Care Service and Management, Health Policy and Services and Health Economy</subject><subject>Health Sciences</subject><subject>Hip</subject><subject>Hip fractures</subject><subject>Hospitals</subject><subject>Hälso- och sjukvårdsorganisation, hälsopolitik och hälsoekonomi</subject><subject>Hälsovetenskap</subject><subject>Income distribution</subject><subject>Isolation</subject><subject>Levels</subject><subject>Mathematical analysis</subject><subject>Medical and Health Sciences</subject><subject>Medicin och hälsovetenskap</subject><subject>Medicine and Health Sciences</subject><subject>Mortality</subject><subject>Municipalities</subject><subject>Patient outcomes</subject><subject>Patients</subject><subject>People and places</subject><subject>Physical Sciences</subject><subject>Population</subject><subject>Research and Analysis 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the contribution of hospitals and municipalities for understanding patient level differences in one-year mortality risk after hip-fracture: A cross-classified multilevel analysis in Sweden</title><author>Kristensen, Pia Kjær ; Perez-Vicente, Raquel ; Leckie, George ; Johnsen, Søren Paaske ; Merlo, Juan ; Garcia de Frutos, Pablo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c6531-292748314bd8b7dfa4ce9a2d3d36c8639d93e36fa26cc38c08978ec3a19529453</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Biology and Life Sciences</topic><topic>Bone surgery</topic><topic>Care and treatment</topic><topic>Coefficient of variation</topic><topic>Demographic aspects</topic><topic>Disposable income</topic><topic>Education</topic><topic>Elderly patients</topic><topic>Epidemiology</topic><topic>Ethics</topic><topic>Fractures</topic><topic>Fractures (Injuries)</topic><topic>Health care policy</topic><topic>Health Care Service and Management, Health Policy and Services and Health Economy</topic><topic>Health Sciences</topic><topic>Hip</topic><topic>Hip fractures</topic><topic>Hospitals</topic><topic>Hälso- och sjukvårdsorganisation, hälsopolitik och hälsoekonomi</topic><topic>Hälsovetenskap</topic><topic>Income distribution</topic><topic>Isolation</topic><topic>Levels</topic><topic>Mathematical analysis</topic><topic>Medical and Health Sciences</topic><topic>Medicin och hälsovetenskap</topic><topic>Medicine and Health Sciences</topic><topic>Mortality</topic><topic>Municipalities</topic><topic>Patient outcomes</topic><topic>Patients</topic><topic>People and places</topic><topic>Physical Sciences</topic><topic>Population</topic><topic>Research and Analysis Methods</topic><topic>Sociodemographics</topic><topic>Studies</topic><topic>Variables</topic><topic>Variation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kristensen, 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Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kristensen, Pia Kjær</au><au>Perez-Vicente, Raquel</au><au>Leckie, George</au><au>Johnsen, Søren Paaske</au><au>Merlo, Juan</au><au>Garcia de Frutos, Pablo</au><au>Garcia de Frutos, Pablo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Disentangling the contribution of hospitals and municipalities for understanding patient level differences in one-year mortality risk after hip-fracture: A cross-classified multilevel analysis in Sweden</atitle><jtitle>PloS one</jtitle><date>2020-06-03</date><risdate>2020</risdate><volume>15</volume><issue>6</issue><spage>e0234041</spage><epage>e0234041</epage><pages>e0234041-e0234041</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Background One-year mortality after hip-fracture is a widely used outcome measure when comparing hospital care performance. However, traditional analyses do not explicitly consider the referral of patients to municipality care after just a few days of hospitalization. Furthermore, traditional analyses investigates hospital (or municipality) variation in patient outcomes in isolation rather than as a component of the underlying patient variation. We therefore aimed to extend the traditional approach to simultaneously estimate both case-mix adjusted hospital and municipality comparisons in order to disentangle the amount of the total patient variation in clinical outcomes that was attributable to the hospital and municipality level, respectively. Methods We determined 1-year mortality risk in patients aged 65 or above with hip fractures registered in Sweden between 2011 and 2014. We performed cross-classified multilevel analysis with 54,999 patients nested within 54 hospitals and 290 municipalities. We adjusted for individual demographic, socioeconomic and clinical characteristics. To quantify the size of the hospital and municipality variation we calculated the variance partition coefficient (VPC) and the area under the receiver operator characteristic curve (AUC). Results The overall 1-year mortality rate was 25.1%. The case-mix adjusted rates varied from 21.7% to 26.5% for the 54 hospitals, and from 18.9% to 29.5% for the 290 municipalities. The VPC was just 0.2% for the hospital and just 0.1% for the municipality level. Patient sociodemographic and clinical characteristics were strong predictors of 1-year mortality (AUC = 0.716), but adding the hospital and municipality levels in the cross-classified model had a minor influence (AUC = 0.718). Conclusions Overall in Sweden, one-year mortality after hip-fracture is rather high. However, only a minor part of the patient variation is explained by the hospital and municipality levels. Therefore, a possible intervention should be nation-wide rather than directed to specific hospitals or municipalities.</abstract><cop>San Francisco</cop><pub>Public Library of Science</pub><pmid>32492053</pmid><doi>10.1371/journal.pone.0234041</doi><tpages>e0234041</tpages><orcidid>https://orcid.org/0000-0001-8379-9708</orcidid><orcidid>https://orcid.org/0000-0001-5473-9386</orcidid><orcidid>https://orcid.org/0000-0003-1486-745X</orcidid><oa>free_for_read</oa></addata></record> |
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| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_2409182009 |
| source | DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; SWEPUB Freely available online; Public Library of Science (PLoS); PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Biology and Life Sciences Bone surgery Care and treatment Coefficient of variation Demographic aspects Disposable income Education Elderly patients Epidemiology Ethics Fractures Fractures (Injuries) Health care policy Health Care Service and Management, Health Policy and Services and Health Economy Health Sciences Hip Hip fractures Hospitals Hälso- och sjukvårdsorganisation, hälsopolitik och hälsoekonomi Hälsovetenskap Income distribution Isolation Levels Mathematical analysis Medical and Health Sciences Medicin och hälsovetenskap Medicine and Health Sciences Mortality Municipalities Patient outcomes Patients People and places Physical Sciences Population Research and Analysis Methods Sociodemographics Studies Variables Variation |
| title | Disentangling the contribution of hospitals and municipalities for understanding patient level differences in one-year mortality risk after hip-fracture: A cross-classified multilevel analysis in Sweden |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-25T13%3A27%3A31IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Disentangling%20the%20contribution%20of%20hospitals%20and%20municipalities%20for%20understanding%20patient%20level%20differences%20in%20one-year%20mortality%20risk%20after%20hip-fracture:%20A%20cross-classified%20multilevel%20analysis%20in%20Sweden&rft.jtitle=PloS%20one&rft.au=Kristensen,%20Pia%20Kj%C3%A6r&rft.date=2020-06-03&rft.volume=15&rft.issue=6&rft.spage=e0234041&rft.epage=e0234041&rft.pages=e0234041-e0234041&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0234041&rft_dat=%3Cgale_plos_%3EA625650655%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2409182009&rft_id=info:pmid/32492053&rft_galeid=A625650655&rft_doaj_id=oai_doaj_org_article_eeb49bbee8f8457e9811731e7f972667&rfr_iscdi=true |