{"title":"利用数据分析提高疗养院质量。","authors":"Christine Pitocco, Thomas R Sexton","doi":"10.1097/QMH.0000000000000376","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>There exists an array of quality performance measures for nursing homes. They can confuse consumers, administrators, and government regulators. Our methodology provides a unified multidimensional evaluation.</p><p><strong>Objective: </strong>To present a methodology to perform a multidimensional assessment of each nursing home within any specified group of nursing homes to aid policy makers, administrators, and consumers with a clear, easy-to-interpret evaluation of a nursing home quality performance.</p><p><strong>Methods: </strong>We use data envelopment analysis (DEA) to integrate several quality measures into a comprehensive benchmarking model. We present statewide results comparing DEA performance scores with the Five-Star rating using data from New York State (NYS) Department of Health.</p><p><strong>Results: </strong>In total, 212 of the 526 nursing homes performed as well as possible. Public nursing homes are most likely to lie on the frontier and have the highest average performance scores. The relationship between the DEA-based performance scores and the NYS Five-Star quality ratings is very weak.</p><p><strong>Conclusion: </strong>DEA is a comprehensive methodology for measuring nursing home quality. The DEA factor performance scores provide detailed information for individual nursing homes, enabling administrators to benchmark their facility's quality performance and to focus quality improvement efforts more effectively.</p>","PeriodicalId":20986,"journal":{"name":"Quality Management in Health Care","volume":null,"pages":null},"PeriodicalIF":1.2000,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Using Data Analytics to Improve Nursing Home Quality.\",\"authors\":\"Christine Pitocco, Thomas R Sexton\",\"doi\":\"10.1097/QMH.0000000000000376\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>There exists an array of quality performance measures for nursing homes. They can confuse consumers, administrators, and government regulators. Our methodology provides a unified multidimensional evaluation.</p><p><strong>Objective: </strong>To present a methodology to perform a multidimensional assessment of each nursing home within any specified group of nursing homes to aid policy makers, administrators, and consumers with a clear, easy-to-interpret evaluation of a nursing home quality performance.</p><p><strong>Methods: </strong>We use data envelopment analysis (DEA) to integrate several quality measures into a comprehensive benchmarking model. We present statewide results comparing DEA performance scores with the Five-Star rating using data from New York State (NYS) Department of Health.</p><p><strong>Results: </strong>In total, 212 of the 526 nursing homes performed as well as possible. Public nursing homes are most likely to lie on the frontier and have the highest average performance scores. The relationship between the DEA-based performance scores and the NYS Five-Star quality ratings is very weak.</p><p><strong>Conclusion: </strong>DEA is a comprehensive methodology for measuring nursing home quality. The DEA factor performance scores provide detailed information for individual nursing homes, enabling administrators to benchmark their facility's quality performance and to focus quality improvement efforts more effectively.</p>\",\"PeriodicalId\":20986,\"journal\":{\"name\":\"Quality Management in Health Care\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2023-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Quality Management in Health Care\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/QMH.0000000000000376\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2022/8/24 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q4\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quality Management in Health Care","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/QMH.0000000000000376","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/8/24 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
Using Data Analytics to Improve Nursing Home Quality.
Background: There exists an array of quality performance measures for nursing homes. They can confuse consumers, administrators, and government regulators. Our methodology provides a unified multidimensional evaluation.
Objective: To present a methodology to perform a multidimensional assessment of each nursing home within any specified group of nursing homes to aid policy makers, administrators, and consumers with a clear, easy-to-interpret evaluation of a nursing home quality performance.
Methods: We use data envelopment analysis (DEA) to integrate several quality measures into a comprehensive benchmarking model. We present statewide results comparing DEA performance scores with the Five-Star rating using data from New York State (NYS) Department of Health.
Results: In total, 212 of the 526 nursing homes performed as well as possible. Public nursing homes are most likely to lie on the frontier and have the highest average performance scores. The relationship between the DEA-based performance scores and the NYS Five-Star quality ratings is very weak.
Conclusion: DEA is a comprehensive methodology for measuring nursing home quality. The DEA factor performance scores provide detailed information for individual nursing homes, enabling administrators to benchmark their facility's quality performance and to focus quality improvement efforts more effectively.
期刊介绍：
Quality Management in Health Care (QMHC) is a peer-reviewed journal that provides a forum for our readers to explore the theoretical, technical, and strategic elements of health care quality management. The journal''s primary focus is on organizational structure and processes as these affect the quality of care and patient outcomes. In particular, it:
-Builds knowledge about the application of statistical tools, control charts, benchmarking, and other devices used in the ongoing monitoring and evaluation of care and of patient outcomes;
-Encourages research in and evaluation of the results of various organizational strategies designed to bring about quantifiable improvements in patient outcomes;
-Fosters the application of quality management science to patient care processes and clinical decision-making;
-Fosters cooperation and communication among health care providers, payers and regulators in their efforts to improve the quality of patient outcomes;
-Explores links among the various clinical, technical, administrative, and managerial disciplines involved in patient care, as well as the role and responsibilities of organizational governance in ongoing quality management.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
