{"title":"埃利克豪斯综合症指数在预测美国全国住院无家可归成年人死亡率方面的表现。","authors":"Jack Tsai, Youngran Kim","doi":"10.1097/MLR.0000000000002019","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The Elixhauser Comorbidity Index (ECI) is widely used, but its performance in homeless populations has not been evaluated.</p><p><strong>Objectives: </strong>Using a national sample of inpatients, this study compared homeless and nonhomeless inpatients on common clinical diagnoses and evaluated ECI performance in predicting mortality among homeless inpatients.</p><p><strong>Research design: </strong>A retrospective study was conducted using 2019 National Inpatient Sample (NIS) data, the largest publicly available all-payer inpatient health care database in the United States.</p><p><strong>Subjects: </strong>Among 4,347,959 hospitalizations, 78,819 (weighted 1.8%) were identified as homeless.</p><p><strong>Measures: </strong>The ECI consists of 38 medical conditions; homelessness was defined using the International Classification of Diseases Tenth Revision Clinical Modification (ICD-10-CM) diagnostic code, and clinical conditions were based on the Clinical Classifications Software Refined (CCSR) for ICD-10-CM.</p><p><strong>Results: </strong>Leading clinical diagnoses for homeless inpatients included schizophrenia and other psychotic disorders (13.3%), depressive disorders (9.4%), and alcohol-related disorders (7.2%); leading diagnoses for nonhomeless inpatients were septicemia (10.2%), heart failure (5.2%), and acute myocardial infarction (3.0%). Metastatic cancer and liver disease were the most common ECI diagnoses for both homeless and nonhomeless inpatients. ECI indicators and summary scores were predictive of in-hospital mortality for homeless and nonhomeless inpatients, with all models yielding concordance statistics above 0.80, with better performance found among homeless inpatients.</p><p><strong>Conclusions: </strong>These findings underlie the high rates of behavioral health conditions among homeless inpatients and the strong performance of the ECI in predicting in-hospital mortality among homeless inpatients, supporting its continued use as a case-mix control method and predictor of hospital readmissions.</p>","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Performance of the Elixhauser Comorbidity Index in Predicting Mortality Among a National US Sample of Hospitalized Homeless Adults.\",\"authors\":\"Jack Tsai, Youngran Kim\",\"doi\":\"10.1097/MLR.0000000000002019\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The Elixhauser Comorbidity Index (ECI) is widely used, but its performance in homeless populations has not been evaluated.</p><p><strong>Objectives: </strong>Using a national sample of inpatients, this study compared homeless and nonhomeless inpatients on common clinical diagnoses and evaluated ECI performance in predicting mortality among homeless inpatients.</p><p><strong>Research design: </strong>A retrospective study was conducted using 2019 National Inpatient Sample (NIS) data, the largest publicly available all-payer inpatient health care database in the United States.</p><p><strong>Subjects: </strong>Among 4,347,959 hospitalizations, 78,819 (weighted 1.8%) were identified as homeless.</p><p><strong>Measures: </strong>The ECI consists of 38 medical conditions; homelessness was defined using the International Classification of Diseases Tenth Revision Clinical Modification (ICD-10-CM) diagnostic code, and clinical conditions were based on the Clinical Classifications Software Refined (CCSR) for ICD-10-CM.</p><p><strong>Results: </strong>Leading clinical diagnoses for homeless inpatients included schizophrenia and other psychotic disorders (13.3%), depressive disorders (9.4%), and alcohol-related disorders (7.2%); leading diagnoses for nonhomeless inpatients were septicemia (10.2%), heart failure (5.2%), and acute myocardial infarction (3.0%). Metastatic cancer and liver disease were the most common ECI diagnoses for both homeless and nonhomeless inpatients. ECI indicators and summary scores were predictive of in-hospital mortality for homeless and nonhomeless inpatients, with all models yielding concordance statistics above 0.80, with better performance found among homeless inpatients.</p><p><strong>Conclusions: </strong>These findings underlie the high rates of behavioral health conditions among homeless inpatients and the strong performance of the ECI in predicting in-hospital mortality among homeless inpatients, supporting its continued use as a case-mix control method and predictor of hospital readmissions.</p>\",\"PeriodicalId\":3,\"journal\":{\"name\":\"ACS Applied Electronic Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Electronic Materials\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/MLR.0000000000002019\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/6/5 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/MLR.0000000000002019","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/6/5 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Performance of the Elixhauser Comorbidity Index in Predicting Mortality Among a National US Sample of Hospitalized Homeless Adults.
Background: The Elixhauser Comorbidity Index (ECI) is widely used, but its performance in homeless populations has not been evaluated.
Objectives: Using a national sample of inpatients, this study compared homeless and nonhomeless inpatients on common clinical diagnoses and evaluated ECI performance in predicting mortality among homeless inpatients.
Research design: A retrospective study was conducted using 2019 National Inpatient Sample (NIS) data, the largest publicly available all-payer inpatient health care database in the United States.
Subjects: Among 4,347,959 hospitalizations, 78,819 (weighted 1.8%) were identified as homeless.
Measures: The ECI consists of 38 medical conditions; homelessness was defined using the International Classification of Diseases Tenth Revision Clinical Modification (ICD-10-CM) diagnostic code, and clinical conditions were based on the Clinical Classifications Software Refined (CCSR) for ICD-10-CM.
Results: Leading clinical diagnoses for homeless inpatients included schizophrenia and other psychotic disorders (13.3%), depressive disorders (9.4%), and alcohol-related disorders (7.2%); leading diagnoses for nonhomeless inpatients were septicemia (10.2%), heart failure (5.2%), and acute myocardial infarction (3.0%). Metastatic cancer and liver disease were the most common ECI diagnoses for both homeless and nonhomeless inpatients. ECI indicators and summary scores were predictive of in-hospital mortality for homeless and nonhomeless inpatients, with all models yielding concordance statistics above 0.80, with better performance found among homeless inpatients.
Conclusions: These findings underlie the high rates of behavioral health conditions among homeless inpatients and the strong performance of the ECI in predicting in-hospital mortality among homeless inpatients, supporting its continued use as a case-mix control method and predictor of hospital readmissions.
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