{"title":"使用医疗补助分析提取方法识别活产的比较。","authors":"Sara E Heins, Laura J Faherty, Ashley M Kranz","doi":"10.1007/s10742-021-00252-w","DOIUrl":null,"url":null,"abstract":"<p><p>Medicaid claims are an important, but underutilized source of data for neonatal health services research in the United States. However, identifying live births in Medicaid claims data is challenging due to variation in coding practices by state and year. Methods of identifying live births in Medicaid claims data have not been validated, and it is not known which methods are most appropriate for different research questions. The objective of this study is to describe and validate five approaches to identifying births using Medicaid Analytic eXtract (MAX) from 45 states (2006-2014). We calculated total number of MAX births by state-year using five definitions: (1) any claim within 30 days of birth date listed in personal summary (PS) file, (2) any claim within 7 days of PS birth date, (3) live birth ICD-9 in inpatient or other therapies file, (4) live birth ICD-9 code in inpatient file, (5) live birth ICD-9 in inpatient file with matching PS birth date. We then compared the number of MAX births by state and year to expected counts using outside data sources. Definition 1 identified the most births (14,189,870) and was closest to total expected count (98.3%). Each definition produced over- and underestimates compared to expected counts for given state-years. Findings suggest that the broadest definition of live births (Definition 1) was closest to expected counts, but that the most appropriate definition depends on research question and state-years of interest.</p>","PeriodicalId":45600,"journal":{"name":"Health Services and Outcomes Research Methodology","volume":null,"pages":null},"PeriodicalIF":1.6000,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s10742-021-00252-w","citationCount":"2","resultStr":"{\"title\":\"A comparison of approaches to identify live births using the medicaid analytic extract.\",\"authors\":\"Sara E Heins, Laura J Faherty, Ashley M Kranz\",\"doi\":\"10.1007/s10742-021-00252-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Medicaid claims are an important, but underutilized source of data for neonatal health services research in the United States. However, identifying live births in Medicaid claims data is challenging due to variation in coding practices by state and year. Methods of identifying live births in Medicaid claims data have not been validated, and it is not known which methods are most appropriate for different research questions. The objective of this study is to describe and validate five approaches to identifying births using Medicaid Analytic eXtract (MAX) from 45 states (2006-2014). We calculated total number of MAX births by state-year using five definitions: (1) any claim within 30 days of birth date listed in personal summary (PS) file, (2) any claim within 7 days of PS birth date, (3) live birth ICD-9 in inpatient or other therapies file, (4) live birth ICD-9 code in inpatient file, (5) live birth ICD-9 in inpatient file with matching PS birth date. We then compared the number of MAX births by state and year to expected counts using outside data sources. Definition 1 identified the most births (14,189,870) and was closest to total expected count (98.3%). Each definition produced over- and underestimates compared to expected counts for given state-years. Findings suggest that the broadest definition of live births (Definition 1) was closest to expected counts, but that the most appropriate definition depends on research question and state-years of interest.</p>\",\"PeriodicalId\":45600,\"journal\":{\"name\":\"Health Services and Outcomes Research Methodology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2022-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1007/s10742-021-00252-w\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Health Services and Outcomes Research Methodology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s10742-021-00252-w\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Health Services and Outcomes Research Methodology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s10742-021-00252-w","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
A comparison of approaches to identify live births using the medicaid analytic extract.
Medicaid claims are an important, but underutilized source of data for neonatal health services research in the United States. However, identifying live births in Medicaid claims data is challenging due to variation in coding practices by state and year. Methods of identifying live births in Medicaid claims data have not been validated, and it is not known which methods are most appropriate for different research questions. The objective of this study is to describe and validate five approaches to identifying births using Medicaid Analytic eXtract (MAX) from 45 states (2006-2014). We calculated total number of MAX births by state-year using five definitions: (1) any claim within 30 days of birth date listed in personal summary (PS) file, (2) any claim within 7 days of PS birth date, (3) live birth ICD-9 in inpatient or other therapies file, (4) live birth ICD-9 code in inpatient file, (5) live birth ICD-9 in inpatient file with matching PS birth date. We then compared the number of MAX births by state and year to expected counts using outside data sources. Definition 1 identified the most births (14,189,870) and was closest to total expected count (98.3%). Each definition produced over- and underestimates compared to expected counts for given state-years. Findings suggest that the broadest definition of live births (Definition 1) was closest to expected counts, but that the most appropriate definition depends on research question and state-years of interest.
期刊介绍:
The journal reflects the multidisciplinary nature of the field of health services and outcomes research. It addresses the needs of multiple, interlocking communities, including methodologists in statistics, econometrics, social and behavioral sciences; designers and analysts of health policy and health services research projects; and health care providers and policy makers who need to properly understand and evaluate the results of published research. The journal strives to enhance the level of methodologic rigor in health services and outcomes research and contributes to the development of methodologic standards in the field. In pursuing its main objective, the journal also provides a meeting ground for researchers from a number of traditional disciplines and fosters the development of new quantitative, qualitative, and mixed methods by statisticians, econometricians, health services researchers, and methodologists in other fields. Health Services and Outcomes Research Methodology publishes: Research papers on quantitative, qualitative, and mixed methods; Case Studies describing applications of quantitative and qualitative methodology in health services and outcomes research; Review Articles synthesizing and popularizing methodologic developments; Tutorials; Articles on computational issues and software reviews; Book reviews; and Notices. Special issues will be devoted to papers presented at important workshops and conferences.