Management of nursing homes using data envelopment analysis.

Area of Science:

• Healthcare Management
• Operations Research
• Performance Measurement

Background:

• Nursing home management requires robust efficiency evaluation methods.
• Traditional performance metrics may not capture quality of care or administrator control.
• Data Envelopment Analysis (DEA) is a tool for assessing relative technical efficiency.

Purpose of the Study:

• To assess the impact of including quality of care variables in DEA models for nursing homes.
• To examine the appropriateness of using non-controllable variables like operating income in administrator evaluations.
• To demonstrate how DEA can inform management decisions for improving nursing home operations.

Main Methods:

• Application of Data Envelopment Analysis (DEA) to a chain of nursing homes.
• Comparative analysis of DEA efficiency scores with varying variable inclusions (financial, economic, quality, operating income).
• Evaluation of the influence of controllable versus non-controllable variables on efficiency scores.

Main Results:

• Efficiency scores significantly differ when quality of care variables are incorporated into DEA models.
• Including non-controllable variables like operating income can distort administrator performance assessments.
• DEA provides actionable insights for both individual nursing home administrators and chain management.

Conclusions:

• DEA models for nursing homes should integrate quality of care measures for accurate administrator evaluation.
• Performance metrics should prioritize controllable variables to ensure fair and effective management assessment.
• DEA is a valuable tool for enhancing operational efficiency and strategic decision-making in nursing home chains.