Using Data Analytics to Improve Nursing Home Quality. Issue 2 (24th April 2023)

• Record Type: Journal Article
• Authors: Pitocco, Christine; Sexton, Thomas R.
• Is Part Of: Quality management in health care. Volume 32:Issue 2(2023)
• Page Start: 87
• Page End: 93
• Publication Date: 2023-04-24
• Subjects: nursing home -- performance measurement -- quality; Medical care -- Quality control -- Periodicals; Total quality management -- Periodicals; Health services administration -- Periodicals; 362.1068
• DOI: 10.1097/QMH.0000000000000376
• Languages: English
• ISSNs: 1063-8628

Abstract

Abstract : 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.