Loading…

The Best Use of the Charlson Comorbidity Index With Electronic Health Care Database to Predict Mortality

BACKGROUND:The most used score to measure comorbidity is the Charlson index. Its application to a health care administrative database including International Classification of Diseases, 10th edition (ICD-10) codes, medical procedures, and medication required studying its properties on survival. Our...

Full description

Saved in:
Bibliographic Details
Published in:Medical care 2016-02, Vol.54 (2), p.188-194
Main Authors: Bannay, Aurélie, Chaignot, Christophe, Blotière, Pierre-Olivier, Basson, Mickaël, Weill, Alain, Ricordeau, Philippe, Alla, François
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c5101-941cd2f72cd83d772be7f54eedb900bae7ab39389045fe249aae3c83dc1f57ea3
cites cdi_FETCH-LOGICAL-c5101-941cd2f72cd83d772be7f54eedb900bae7ab39389045fe249aae3c83dc1f57ea3
container_end_page 194
container_issue 2
container_start_page 188
container_title Medical care
container_volume 54
creator Bannay, Aurélie
Chaignot, Christophe
Blotière, Pierre-Olivier
Basson, Mickaël
Weill, Alain
Ricordeau, Philippe
Alla, François
description BACKGROUND:The most used score to measure comorbidity is the Charlson index. Its application to a health care administrative database including International Classification of Diseases, 10th edition (ICD-10) codes, medical procedures, and medication required studying its properties on survival. Our objectives were to adapt the Charlson comorbidity index to the French National Health Insurance database to predict 1-year mortality of discharged patients and to compare discrimination and calibration of different versions of the Charlson index. METHODS:Our cohort included all adults discharged from a hospital stay in France in 2010 registered in the French National Health Insurance general scheme. The pathologies of the Charlson index were identified through ICD-10 codes of discharge diagnoses and long-term disease, specific medical procedures, and reimbursement of specific medications in the past 12 months before inclusion. RESULTS:We included 6,602,641 subjects at the date of their first discharge from medical, surgical, or obstetrical department in 2010. One-year survival was 94.88%, decreasing from 98.41% for Charlson index of 0–71.64% for Charlson index of ≥5. With a discrimination of 0.91 and an appropriate calibration curve, we retained the crude Cox model including the age-adjusted Charlson index as a 4-level score. CONCLUSIONS:Our study is the first to adapt the Charlson index to a large health care database including >6 million of inpatients. When mortality is the outcome, we recommended using the age-adjusted Charlson index as 4-level score to take into account comorbidities.
doi_str_mv 10.1097/MLR.0000000000000471
format article
fullrecord <record><control><sourceid>jstor_hal_p</sourceid><recordid>TN_cdi_hal_primary_oai_HAL_hal_01817541v1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><jstor_id>26418120</jstor_id><sourcerecordid>26418120</sourcerecordid><originalsourceid>FETCH-LOGICAL-c5101-941cd2f72cd83d772be7f54eedb900bae7ab39389045fe249aae3c83dc1f57ea3</originalsourceid><addsrcrecordid>eNqFkUFv1DAQhS0EokvhHwCy1Et7SBk7zjo5lrSwlbYCoVYcLceZKFm8cbGdlv57vE2pql7wxfLoe0-e9wh5z-CYQSU_Xax_HMPTIyR7QRasyGXGKlG-JAsAXmQSZLVH3oSwAWAyL_hrsseXyzKXslyQ_rJH-hlDpFcBqetoTO-6194GN9LabZ1vhnaId_R8bPEP_TnEnp5ZNNG7cTB0hdqmSa090lMddaOTTXT0u8d2MJFeOB-1Tfq35FWnbcB3D_c-ufpydlmvsvW3r-f1yTozBQOWVYKZlneSm7bMWyl5g7IrBGLbVACNRqmbvMrLCkTRIReV1pibhBrWFRJ1vk-OZt9eW3Xth632d8rpQa1O1mo3A1YyWQh2wxJ7OLPX3v2eUghqOwSD1uoR3RQUk0sol1xwSOjBM3TjJj-mTXYUB84kiESJmTLeheCxe_wBA7VrTaXW1PPWkuzjg_nUbLF9FP2rKQHlDNw6G9GHX3a6Ra_6-_D_5_1hlm5CdP6JtUg5pMX-AkTvq1s</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1762021704</pqid></control><display><type>article</type><title>The Best Use of the Charlson Comorbidity Index With Electronic Health Care Database to Predict Mortality</title><source>JSTOR-E-Journals</source><creator>Bannay, Aurélie ; Chaignot, Christophe ; Blotière, Pierre-Olivier ; Basson, Mickaël ; Weill, Alain ; Ricordeau, Philippe ; Alla, François</creator><creatorcontrib>Bannay, Aurélie ; Chaignot, Christophe ; Blotière, Pierre-Olivier ; Basson, Mickaël ; Weill, Alain ; Ricordeau, Philippe ; Alla, François</creatorcontrib><description>BACKGROUND:The most used score to measure comorbidity is the Charlson index. Its application to a health care administrative database including International Classification of Diseases, 10th edition (ICD-10) codes, medical procedures, and medication required studying its properties on survival. Our objectives were to adapt the Charlson comorbidity index to the French National Health Insurance database to predict 1-year mortality of discharged patients and to compare discrimination and calibration of different versions of the Charlson index. METHODS:Our cohort included all adults discharged from a hospital stay in France in 2010 registered in the French National Health Insurance general scheme. The pathologies of the Charlson index were identified through ICD-10 codes of discharge diagnoses and long-term disease, specific medical procedures, and reimbursement of specific medications in the past 12 months before inclusion. RESULTS:We included 6,602,641 subjects at the date of their first discharge from medical, surgical, or obstetrical department in 2010. One-year survival was 94.88%, decreasing from 98.41% for Charlson index of 0–71.64% for Charlson index of ≥5. With a discrimination of 0.91 and an appropriate calibration curve, we retained the crude Cox model including the age-adjusted Charlson index as a 4-level score. CONCLUSIONS:Our study is the first to adapt the Charlson index to a large health care database including &gt;6 million of inpatients. When mortality is the outcome, we recommended using the age-adjusted Charlson index as 4-level score to take into account comorbidities.</description><identifier>ISSN: 0025-7079</identifier><identifier>EISSN: 1537-1948</identifier><identifier>DOI: 10.1097/MLR.0000000000000471</identifier><identifier>PMID: 26683778</identifier><identifier>CODEN: MELAAD</identifier><language>eng</language><publisher>United States: Lippincott Williams &amp; Wilkins</publisher><subject>Adult ; Aged ; Calibration ; Comorbidity ; Electronic Health Records ; Electronic Health Records - statistics &amp; numerical data ; Female ; France ; Humans ; Insurance Claim Review ; Insurance Claim Review - statistics &amp; numerical data ; International Classification of Diseases ; Life Sciences ; Male ; Middle Aged ; Mortality ; National health insurance ; Original Article ; Prognosis ; Risk Adjustment ; Risk Adjustment - methods ; Santé publique et épidémiologie ; Survival analysis</subject><ispartof>Medical care, 2016-02, Vol.54 (2), p.188-194</ispartof><rights>Copyright © 2015 Wolters Kluwer Health, Inc.</rights><rights>Copyright © 2016 Wolters Kluwer Health, Inc. All rights reserved.</rights><rights>Copyright Lippincott Williams &amp; Wilkins Feb 2016</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5101-941cd2f72cd83d772be7f54eedb900bae7ab39389045fe249aae3c83dc1f57ea3</citedby><cites>FETCH-LOGICAL-c5101-941cd2f72cd83d772be7f54eedb900bae7ab39389045fe249aae3c83dc1f57ea3</cites><orcidid>0000-0002-1631-566X ; 0000-0001-8687-9092</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/26418120$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/26418120$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>230,314,776,780,881,27901,27902,58213,58446</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26683778$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://hal.univ-lorraine.fr/hal-01817541$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Bannay, Aurélie</creatorcontrib><creatorcontrib>Chaignot, Christophe</creatorcontrib><creatorcontrib>Blotière, Pierre-Olivier</creatorcontrib><creatorcontrib>Basson, Mickaël</creatorcontrib><creatorcontrib>Weill, Alain</creatorcontrib><creatorcontrib>Ricordeau, Philippe</creatorcontrib><creatorcontrib>Alla, François</creatorcontrib><title>The Best Use of the Charlson Comorbidity Index With Electronic Health Care Database to Predict Mortality</title><title>Medical care</title><addtitle>Med Care</addtitle><description>BACKGROUND:The most used score to measure comorbidity is the Charlson index. Its application to a health care administrative database including International Classification of Diseases, 10th edition (ICD-10) codes, medical procedures, and medication required studying its properties on survival. Our objectives were to adapt the Charlson comorbidity index to the French National Health Insurance database to predict 1-year mortality of discharged patients and to compare discrimination and calibration of different versions of the Charlson index. METHODS:Our cohort included all adults discharged from a hospital stay in France in 2010 registered in the French National Health Insurance general scheme. The pathologies of the Charlson index were identified through ICD-10 codes of discharge diagnoses and long-term disease, specific medical procedures, and reimbursement of specific medications in the past 12 months before inclusion. RESULTS:We included 6,602,641 subjects at the date of their first discharge from medical, surgical, or obstetrical department in 2010. One-year survival was 94.88%, decreasing from 98.41% for Charlson index of 0–71.64% for Charlson index of ≥5. With a discrimination of 0.91 and an appropriate calibration curve, we retained the crude Cox model including the age-adjusted Charlson index as a 4-level score. CONCLUSIONS:Our study is the first to adapt the Charlson index to a large health care database including &gt;6 million of inpatients. When mortality is the outcome, we recommended using the age-adjusted Charlson index as 4-level score to take into account comorbidities.</description><subject>Adult</subject><subject>Aged</subject><subject>Calibration</subject><subject>Comorbidity</subject><subject>Electronic Health Records</subject><subject>Electronic Health Records - statistics &amp; numerical data</subject><subject>Female</subject><subject>France</subject><subject>Humans</subject><subject>Insurance Claim Review</subject><subject>Insurance Claim Review - statistics &amp; numerical data</subject><subject>International Classification of Diseases</subject><subject>Life Sciences</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Mortality</subject><subject>National health insurance</subject><subject>Original Article</subject><subject>Prognosis</subject><subject>Risk Adjustment</subject><subject>Risk Adjustment - methods</subject><subject>Santé publique et épidémiologie</subject><subject>Survival analysis</subject><issn>0025-7079</issn><issn>1537-1948</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNqFkUFv1DAQhS0EokvhHwCy1Et7SBk7zjo5lrSwlbYCoVYcLceZKFm8cbGdlv57vE2pql7wxfLoe0-e9wh5z-CYQSU_Xax_HMPTIyR7QRasyGXGKlG-JAsAXmQSZLVH3oSwAWAyL_hrsseXyzKXslyQ_rJH-hlDpFcBqetoTO-6194GN9LabZ1vhnaId_R8bPEP_TnEnp5ZNNG7cTB0hdqmSa090lMddaOTTXT0u8d2MJFeOB-1Tfq35FWnbcB3D_c-ufpydlmvsvW3r-f1yTozBQOWVYKZlneSm7bMWyl5g7IrBGLbVACNRqmbvMrLCkTRIReV1pibhBrWFRJ1vk-OZt9eW3Xth632d8rpQa1O1mo3A1YyWQh2wxJ7OLPX3v2eUghqOwSD1uoR3RQUk0sol1xwSOjBM3TjJj-mTXYUB84kiESJmTLeheCxe_wBA7VrTaXW1PPWkuzjg_nUbLF9FP2rKQHlDNw6G9GHX3a6Ra_6-_D_5_1hlm5CdP6JtUg5pMX-AkTvq1s</recordid><startdate>201602</startdate><enddate>201602</enddate><creator>Bannay, Aurélie</creator><creator>Chaignot, Christophe</creator><creator>Blotière, Pierre-Olivier</creator><creator>Basson, Mickaël</creator><creator>Weill, Alain</creator><creator>Ricordeau, Philippe</creator><creator>Alla, François</creator><general>Lippincott Williams &amp; Wilkins</general><general>Copyright Wolters Kluwer Health, Inc. All rights reserved</general><general>Lippincott Williams &amp; Wilkins Ovid Technologies</general><general>American Public Health Association</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>1XC</scope><orcidid>https://orcid.org/0000-0002-1631-566X</orcidid><orcidid>https://orcid.org/0000-0001-8687-9092</orcidid></search><sort><creationdate>201602</creationdate><title>The Best Use of the Charlson Comorbidity Index With Electronic Health Care Database to Predict Mortality</title><author>Bannay, Aurélie ; Chaignot, Christophe ; Blotière, Pierre-Olivier ; Basson, Mickaël ; Weill, Alain ; Ricordeau, Philippe ; Alla, François</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5101-941cd2f72cd83d772be7f54eedb900bae7ab39389045fe249aae3c83dc1f57ea3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Calibration</topic><topic>Comorbidity</topic><topic>Electronic Health Records</topic><topic>Electronic Health Records - statistics &amp; numerical data</topic><topic>Female</topic><topic>France</topic><topic>Humans</topic><topic>Insurance Claim Review</topic><topic>Insurance Claim Review - statistics &amp; numerical data</topic><topic>International Classification of Diseases</topic><topic>Life Sciences</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Mortality</topic><topic>National health insurance</topic><topic>Original Article</topic><topic>Prognosis</topic><topic>Risk Adjustment</topic><topic>Risk Adjustment - methods</topic><topic>Santé publique et épidémiologie</topic><topic>Survival analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bannay, Aurélie</creatorcontrib><creatorcontrib>Chaignot, Christophe</creatorcontrib><creatorcontrib>Blotière, Pierre-Olivier</creatorcontrib><creatorcontrib>Basson, Mickaël</creatorcontrib><creatorcontrib>Weill, Alain</creatorcontrib><creatorcontrib>Ricordeau, Philippe</creatorcontrib><creatorcontrib>Alla, François</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 &amp; Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><collection>Hyper Article en Ligne (HAL)</collection><jtitle>Medical care</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bannay, Aurélie</au><au>Chaignot, Christophe</au><au>Blotière, Pierre-Olivier</au><au>Basson, Mickaël</au><au>Weill, Alain</au><au>Ricordeau, Philippe</au><au>Alla, François</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Best Use of the Charlson Comorbidity Index With Electronic Health Care Database to Predict Mortality</atitle><jtitle>Medical care</jtitle><addtitle>Med Care</addtitle><date>2016-02</date><risdate>2016</risdate><volume>54</volume><issue>2</issue><spage>188</spage><epage>194</epage><pages>188-194</pages><issn>0025-7079</issn><eissn>1537-1948</eissn><coden>MELAAD</coden><abstract>BACKGROUND:The most used score to measure comorbidity is the Charlson index. Its application to a health care administrative database including International Classification of Diseases, 10th edition (ICD-10) codes, medical procedures, and medication required studying its properties on survival. Our objectives were to adapt the Charlson comorbidity index to the French National Health Insurance database to predict 1-year mortality of discharged patients and to compare discrimination and calibration of different versions of the Charlson index. METHODS:Our cohort included all adults discharged from a hospital stay in France in 2010 registered in the French National Health Insurance general scheme. The pathologies of the Charlson index were identified through ICD-10 codes of discharge diagnoses and long-term disease, specific medical procedures, and reimbursement of specific medications in the past 12 months before inclusion. RESULTS:We included 6,602,641 subjects at the date of their first discharge from medical, surgical, or obstetrical department in 2010. One-year survival was 94.88%, decreasing from 98.41% for Charlson index of 0–71.64% for Charlson index of ≥5. With a discrimination of 0.91 and an appropriate calibration curve, we retained the crude Cox model including the age-adjusted Charlson index as a 4-level score. CONCLUSIONS:Our study is the first to adapt the Charlson index to a large health care database including &gt;6 million of inpatients. When mortality is the outcome, we recommended using the age-adjusted Charlson index as 4-level score to take into account comorbidities.</abstract><cop>United States</cop><pub>Lippincott Williams &amp; Wilkins</pub><pmid>26683778</pmid><doi>10.1097/MLR.0000000000000471</doi><tpages>7</tpages><orcidid>https://orcid.org/0000-0002-1631-566X</orcidid><orcidid>https://orcid.org/0000-0001-8687-9092</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 0025-7079
ispartof Medical care, 2016-02, Vol.54 (2), p.188-194
issn 0025-7079
1537-1948
language eng
recordid cdi_hal_primary_oai_HAL_hal_01817541v1
source JSTOR-E-Journals
subjects Adult
Aged
Calibration
Comorbidity
Electronic Health Records
Electronic Health Records - statistics & numerical data
Female
France
Humans
Insurance Claim Review
Insurance Claim Review - statistics & numerical data
International Classification of Diseases
Life Sciences
Male
Middle Aged
Mortality
National health insurance
Original Article
Prognosis
Risk Adjustment
Risk Adjustment - methods
Santé publique et épidémiologie
Survival analysis
title The Best Use of the Charlson Comorbidity Index With Electronic Health Care Database to Predict Mortality
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-31T19%3A36%3A48IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-jstor_hal_p&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=The%20Best%20Use%20of%20the%20Charlson%20Comorbidity%20Index%20With%20Electronic%20Health%20Care%20Database%20to%20Predict%20Mortality&rft.jtitle=Medical%20care&rft.au=Bannay,%20Aur%C3%A9lie&rft.date=2016-02&rft.volume=54&rft.issue=2&rft.spage=188&rft.epage=194&rft.pages=188-194&rft.issn=0025-7079&rft.eissn=1537-1948&rft.coden=MELAAD&rft_id=info:doi/10.1097/MLR.0000000000000471&rft_dat=%3Cjstor_hal_p%3E26418120%3C/jstor_hal_p%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c5101-941cd2f72cd83d772be7f54eedb900bae7ab39389045fe249aae3c83dc1f57ea3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1762021704&rft_id=info:pmid/26683778&rft_jstor_id=26418120&rfr_iscdi=true