Two morbidity indices developed in a nationwide population permitted performant outcome-specific severity adjustment
The objective of the study was to develop and validate two outcome-specific morbidity indices in a population-based setting: the Mortality-Related Morbidity Index (MRMI) predictive of all-cause mortality and the Expenditure-Related Morbidity Index (ERMI) predictive of health care expenditure. A coho...
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| Veröffentlicht in: | Journal of clinical epidemiology 2018-11, Vol.103, p.60-70 |
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| container_title | Journal of clinical epidemiology |
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| creator | Constantinou, Panayotis Tuppin, Philippe Fagot-Campagna, Anne Gastaldi-Ménager, Christelle Schellevis, François G. Pelletier-Fleury, Nathalie |
| description | The objective of the study was to develop and validate two outcome-specific morbidity indices in a population-based setting: the Mortality-Related Morbidity Index (MRMI) predictive of all-cause mortality and the Expenditure-Related Morbidity Index (ERMI) predictive of health care expenditure.
A cohort including all beneficiaries of the main French health insurance scheme aged 65 years or older on December 31, 2013 (N = 7,672,111), was randomly split into a development population for index elaboration and a validation population for predictive performance assessment. Age, gender, and selected lists of conditions identified through standard algorithms available in the French health insurance database (SNDS) were used as predictors for 2-year mortality and 2-year health care expenditure in separate models. Overall performance and calibration of the MRMI and ERMI were measured and compared to various versions of the Charlson Comorbidity Index (CCI).
The MRMI included 16 conditions, was more discriminant than the age-adjusted CCI (c-statistic: 0.825 [95% confidence interval: 0.824–0.826] vs. 0.800 [0.799–0.801]), and better calibrated. The ERMI included 19 conditions, explained more variance than the cost-adapted CCI (21.8% vs. 13.0%), and was better calibrated.
The proposed MRMI and ERMI indices are performant tools to account for health-state severity according to outcomes of interest. |
| doi_str_mv | 10.1016/j.jclinepi.2018.07.003 |
| format | Article |
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A cohort including all beneficiaries of the main French health insurance scheme aged 65 years or older on December 31, 2013 (N = 7,672,111), was randomly split into a development population for index elaboration and a validation population for predictive performance assessment. Age, gender, and selected lists of conditions identified through standard algorithms available in the French health insurance database (SNDS) were used as predictors for 2-year mortality and 2-year health care expenditure in separate models. Overall performance and calibration of the MRMI and ERMI were measured and compared to various versions of the Charlson Comorbidity Index (CCI).
The MRMI included 16 conditions, was more discriminant than the age-adjusted CCI (c-statistic: 0.825 [95% confidence interval: 0.824–0.826] vs. 0.800 [0.799–0.801]), and better calibrated. The ERMI included 19 conditions, explained more variance than the cost-adapted CCI (21.8% vs. 13.0%), and was better calibrated.
The proposed MRMI and ERMI indices are performant tools to account for health-state severity according to outcomes of interest.</description><identifier>ISSN: 0895-4356</identifier><identifier>EISSN: 1878-5921</identifier><identifier>DOI: 10.1016/j.jclinepi.2018.07.003</identifier><identifier>PMID: 30016643</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Age ; Alzheimer's disease ; Asthma ; Calibration ; Cancer ; Cardiac arrhythmia ; Cardiovascular disease ; Comorbidity ; Confidence intervals ; Dementia ; Diabetes ; Drug abuse ; Emotional disorders ; Epidemiology ; Expenditures ; Gender ; Health care ; Health expenditure ; Health information systems ; Health insurance ; Heart failure ; HIV ; Human immunodeficiency virus ; Information systems ; Insurance ; Insurance coverage ; Morbidity ; Morbidity indices ; Mortality ; Multimorbidity ; Paralysis ; Parkinson's disease ; Performance assessment ; Performance prediction ; Population ; Respiratory diseases ; Rheumatoid arthritis ; Risk-adjustment ; Statistical analysis</subject><ispartof>Journal of clinical epidemiology, 2018-11, Vol.103, p.60-70</ispartof><rights>2018 Elsevier Inc.</rights><rights>Copyright © 2018 Elsevier Inc. All rights reserved.</rights><rights>Copyright Elsevier Limited Nov 2018</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c510t-e4dba27e32b32a1bfb9ee58ad83c64ff1d4d08a6bffd20f6b7f1767a806cbe4a3</citedby><cites>FETCH-LOGICAL-c510t-e4dba27e32b32a1bfb9ee58ad83c64ff1d4d08a6bffd20f6b7f1767a806cbe4a3</cites><orcidid>0000-0001-5698-9215</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/2116009984?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,777,781,3537,27905,27906,45976,64364,64366,64368,72218</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30016643$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Constantinou, Panayotis</creatorcontrib><creatorcontrib>Tuppin, Philippe</creatorcontrib><creatorcontrib>Fagot-Campagna, Anne</creatorcontrib><creatorcontrib>Gastaldi-Ménager, Christelle</creatorcontrib><creatorcontrib>Schellevis, François G.</creatorcontrib><creatorcontrib>Pelletier-Fleury, Nathalie</creatorcontrib><title>Two morbidity indices developed in a nationwide population permitted performant outcome-specific severity adjustment</title><title>Journal of clinical epidemiology</title><addtitle>J Clin Epidemiol</addtitle><description>The objective of the study was to develop and validate two outcome-specific morbidity indices in a population-based setting: the Mortality-Related Morbidity Index (MRMI) predictive of all-cause mortality and the Expenditure-Related Morbidity Index (ERMI) predictive of health care expenditure.
A cohort including all beneficiaries of the main French health insurance scheme aged 65 years or older on December 31, 2013 (N = 7,672,111), was randomly split into a development population for index elaboration and a validation population for predictive performance assessment. Age, gender, and selected lists of conditions identified through standard algorithms available in the French health insurance database (SNDS) were used as predictors for 2-year mortality and 2-year health care expenditure in separate models. Overall performance and calibration of the MRMI and ERMI were measured and compared to various versions of the Charlson Comorbidity Index (CCI).
The MRMI included 16 conditions, was more discriminant than the age-adjusted CCI (c-statistic: 0.825 [95% confidence interval: 0.824–0.826] vs. 0.800 [0.799–0.801]), and better calibrated. The ERMI included 19 conditions, explained more variance than the cost-adapted CCI (21.8% vs. 13.0%), and was better calibrated.
The proposed MRMI and ERMI indices are performant tools to account for health-state severity according to outcomes of interest.</description><subject>Age</subject><subject>Alzheimer's disease</subject><subject>Asthma</subject><subject>Calibration</subject><subject>Cancer</subject><subject>Cardiac arrhythmia</subject><subject>Cardiovascular disease</subject><subject>Comorbidity</subject><subject>Confidence intervals</subject><subject>Dementia</subject><subject>Diabetes</subject><subject>Drug abuse</subject><subject>Emotional disorders</subject><subject>Epidemiology</subject><subject>Expenditures</subject><subject>Gender</subject><subject>Health care</subject><subject>Health expenditure</subject><subject>Health information systems</subject><subject>Health insurance</subject><subject>Heart failure</subject><subject>HIV</subject><subject>Human immunodeficiency virus</subject><subject>Information systems</subject><subject>Insurance</subject><subject>Insurance 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Epidemiol</addtitle><date>2018-11</date><risdate>2018</risdate><volume>103</volume><spage>60</spage><epage>70</epage><pages>60-70</pages><issn>0895-4356</issn><eissn>1878-5921</eissn><abstract>The objective of the study was to develop and validate two outcome-specific morbidity indices in a population-based setting: the Mortality-Related Morbidity Index (MRMI) predictive of all-cause mortality and the Expenditure-Related Morbidity Index (ERMI) predictive of health care expenditure.
A cohort including all beneficiaries of the main French health insurance scheme aged 65 years or older on December 31, 2013 (N = 7,672,111), was randomly split into a development population for index elaboration and a validation population for predictive performance assessment. Age, gender, and selected lists of conditions identified through standard algorithms available in the French health insurance database (SNDS) were used as predictors for 2-year mortality and 2-year health care expenditure in separate models. Overall performance and calibration of the MRMI and ERMI were measured and compared to various versions of the Charlson Comorbidity Index (CCI).
The MRMI included 16 conditions, was more discriminant than the age-adjusted CCI (c-statistic: 0.825 [95% confidence interval: 0.824–0.826] vs. 0.800 [0.799–0.801]), and better calibrated. The ERMI included 19 conditions, explained more variance than the cost-adapted CCI (21.8% vs. 13.0%), and was better calibrated.
The proposed MRMI and ERMI indices are performant tools to account for health-state severity according to outcomes of interest.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>30016643</pmid><doi>10.1016/j.jclinepi.2018.07.003</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0001-5698-9215</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | Journal of clinical epidemiology, 2018-11, Vol.103, p.60-70 |
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| language | eng |
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| source | Elsevier ScienceDirect Journals; ProQuest Central UK/Ireland |
| subjects | Age Alzheimer's disease Asthma Calibration Cancer Cardiac arrhythmia Cardiovascular disease Comorbidity Confidence intervals Dementia Diabetes Drug abuse Emotional disorders Epidemiology Expenditures Gender Health care Health expenditure Health information systems Health insurance Heart failure HIV Human immunodeficiency virus Information systems Insurance Insurance coverage Morbidity Morbidity indices Mortality Multimorbidity Paralysis Parkinson's disease Performance assessment Performance prediction Population Respiratory diseases Rheumatoid arthritis Risk-adjustment Statistical analysis |
| title | Two morbidity indices developed in a nationwide population permitted performant outcome-specific severity adjustment |
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