利用不同的数据来源来识别和描述美国的医疗保健服务系统。

Genna R Cohen, David J Jones, Jessica Heeringa, Kirsten Barrett, Michael F Furukawa, Dan Miller, Anne Mutti, James D Reschovsky, Rachel Machta, Stephen M Shortell, Taressa Fraze, Eugene Rich
{"title":"利用不同的数据来源来识别和描述美国的医疗保健服务系统。","authors":"Genna R Cohen, David J Jones, Jessica Heeringa, Kirsten Barrett, Michael F Furukawa, Dan Miller, Anne Mutti, James D Reschovsky, Rachel Machta, Stephen M Shortell, Taressa Fraze, Eugene Rich","doi":"10.5334/egems.200","DOIUrl":null,"url":null,"abstract":"<p><p>Health care delivery systems are a growing presence in the U.S., yet research is hindered by the lack of universally agreed-upon criteria to denote formal systems. A clearer understanding of how to leverage real-world data sources to empirically identify systems is a necessary first step to such policy-relevant research. We draw from our experience in the Agency for Healthcare Research and Quality's Comparative Health System Performance (CHSP) initiative to assess available data sources to identify and describe systems, including system members (for example, hospitals and physicians) and relationships among the members (for example, hospital ownership of physician groups). We highlight five national data sources that either explicitly track system membership or detail system relationships: (1) American Hospital Association annual survey of hospitals; (2) Healthcare Relational Services Databases; (3) SK&A Healthcare Databases; (4) Provider Enrollment, Chain, and Ownership System; and (5) Internal Revenue Service 990 forms. Each data source has strengths and limitations for identifying and describing systems due to their varied content, linkages across data sources, and data collection methods. In addition, although no single national data source provides a complete picture of U.S. systems and their members, the CHSP initiative will create an early model of how such data can be combined to compensate for their individual limitations. Identifying systems in a way that can be repeated over time and linked to a host of other data sources will support analysis of how different types of organizations deliver health care and, ultimately, comparison of their performance.</p>","PeriodicalId":72880,"journal":{"name":"EGEMS (Washington, DC)","volume":"5 3","pages":"9"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5983023/pdf/","citationCount":"17","resultStr":"{\"title\":\"Leveraging Diverse Data Sources to Identify and Describe U.S. Health Care Delivery Systems.\",\"authors\":\"Genna R Cohen, David J Jones, Jessica Heeringa, Kirsten Barrett, Michael F Furukawa, Dan Miller, Anne Mutti, James D Reschovsky, Rachel Machta, Stephen M Shortell, Taressa Fraze, Eugene Rich\",\"doi\":\"10.5334/egems.200\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Health care delivery systems are a growing presence in the U.S., yet research is hindered by the lack of universally agreed-upon criteria to denote formal systems. A clearer understanding of how to leverage real-world data sources to empirically identify systems is a necessary first step to such policy-relevant research. We draw from our experience in the Agency for Healthcare Research and Quality's Comparative Health System Performance (CHSP) initiative to assess available data sources to identify and describe systems, including system members (for example, hospitals and physicians) and relationships among the members (for example, hospital ownership of physician groups). We highlight five national data sources that either explicitly track system membership or detail system relationships: (1) American Hospital Association annual survey of hospitals; (2) Healthcare Relational Services Databases; (3) SK&A Healthcare Databases; (4) Provider Enrollment, Chain, and Ownership System; and (5) Internal Revenue Service 990 forms. Each data source has strengths and limitations for identifying and describing systems due to their varied content, linkages across data sources, and data collection methods. In addition, although no single national data source provides a complete picture of U.S. systems and their members, the CHSP initiative will create an early model of how such data can be combined to compensate for their individual limitations. Identifying systems in a way that can be repeated over time and linked to a host of other data sources will support analysis of how different types of organizations deliver health care and, ultimately, comparison of their performance.</p>\",\"PeriodicalId\":72880,\"journal\":{\"name\":\"EGEMS (Washington, DC)\",\"volume\":\"5 3\",\"pages\":\"9\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5983023/pdf/\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"EGEMS (Washington, DC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5334/egems.200\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"EGEMS (Washington, DC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5334/egems.200","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17

摘要

在美国,医疗保健服务系统的存在越来越多,但由于缺乏普遍认可的标准来表示正式系统,研究受到阻碍。更清楚地了解如何利用真实世界的数据源来经验地识别系统,是进行此类政策相关研究的必要的第一步。我们借鉴我们在医疗保健研究和质量机构的比较卫生系统绩效(CHSP)计划中的经验,评估可用的数据源,以识别和描述系统,包括系统成员(例如,医院和医生)和成员之间的关系(例如,医生团体的医院所有权)。我们重点介绍了五个明确跟踪系统成员或详细系统关系的国家数据来源:(1)美国医院协会对医院的年度调查;(2)医疗保健关系服务数据库;(3) SK&A医疗保健数据库;(4)供应商注册、连锁和所有权制度;(5)美国国税局990表格。由于不同的内容、数据源之间的链接和数据收集方法,每个数据源在识别和描述系统方面都有其优点和局限性。此外,尽管没有单一的国家数据来源提供美国系统及其成员的完整图景,但CHSP计划将创建一个早期模型,说明如何将这些数据结合起来,以弥补各自的局限性。以一种可随时间重复并与大量其他数据源相关联的方式确定系统,将有助于分析不同类型的组织如何提供卫生保健,并最终对其绩效进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Leveraging Diverse Data Sources to Identify and Describe U.S. Health Care Delivery Systems.

Leveraging Diverse Data Sources to Identify and Describe U.S. Health Care Delivery Systems.

Leveraging Diverse Data Sources to Identify and Describe U.S. Health Care Delivery Systems.

Health care delivery systems are a growing presence in the U.S., yet research is hindered by the lack of universally agreed-upon criteria to denote formal systems. A clearer understanding of how to leverage real-world data sources to empirically identify systems is a necessary first step to such policy-relevant research. We draw from our experience in the Agency for Healthcare Research and Quality's Comparative Health System Performance (CHSP) initiative to assess available data sources to identify and describe systems, including system members (for example, hospitals and physicians) and relationships among the members (for example, hospital ownership of physician groups). We highlight five national data sources that either explicitly track system membership or detail system relationships: (1) American Hospital Association annual survey of hospitals; (2) Healthcare Relational Services Databases; (3) SK&A Healthcare Databases; (4) Provider Enrollment, Chain, and Ownership System; and (5) Internal Revenue Service 990 forms. Each data source has strengths and limitations for identifying and describing systems due to their varied content, linkages across data sources, and data collection methods. In addition, although no single national data source provides a complete picture of U.S. systems and their members, the CHSP initiative will create an early model of how such data can be combined to compensate for their individual limitations. Identifying systems in a way that can be repeated over time and linked to a host of other data sources will support analysis of how different types of organizations deliver health care and, ultimately, comparison of their performance.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信