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Updated: Aug 31, 2025

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
Published on: July 27, 2018
Using Data Analytics to Improve Nursing Home Quality
Christine Pitocco1, Thomas R Sexton
1College of Business, Stony Brook University, Stony Brook, New York.
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.
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