Address correspondence to Robert H. Lee, Ph.D., Associate Professor, Department of Health Policy and Management, School of Medicine, University of Kansas Medical Center, 5004 Student Center, Mail Stop 3044, 3901 Rainbow Boulevard, Kansas City, KS 66160; e-mail: email@example.com. Marjorie J. Bott, R.N., Ph.D., Associate Dean for Nursing Research, and Roma Lee L. Taunton, R.N., Ph.D., Professor Emeritus, are with School of Nursing, University of Kansas Medical Center, Kansas City, KS. Byron Gajewski, Ph.D., Biostatistician, is with Schools of Nursing and Allied Health, University of Kansas Medical Center, Kansas City, KS.
Modeling Efficiency at the Process Level: An Examination of the Care Planning Process in Nursing Homes
Version of Record online: 8 SEP 2008
© Health Research and Educational Trust
Health Services Research
Volume 44, Issue 1, pages 15–32, February 2009
How to Cite
Lee, R. H., Bott, M. J., Gajewski, B. and Taunton, R. L. (2009), Modeling Efficiency at the Process Level: An Examination of the Care Planning Process in Nursing Homes. Health Services Research, 44: 15–32. doi: 10.1111/j.1475-6773.2008.00895.x
- Issue online: 15 JAN 2009
- Version of Record online: 8 SEP 2008
- Data envelopment analysis;
- corrected ordinary least squares;
- long-term care;
- care planning
Objective. To examine the efficiency of the care planning process in nursing homes.
Methods: We collected detailed primary data about the care planning process for a stratified random sample of 107 nursing homes from Kansas and Missouri. We used these data to calculate the average direct cost per care plan and used data on selected deficiencies from the Online Survey Certification and Reporting System to measure the quality of care planning. We then analyzed the efficiency of the assessment process using corrected ordinary least squares (COLS) and data envelopment analysis (DEA).
Results: Both approaches suggested that there was considerable inefficiency in the care planning process. The average COLS score was 0.43; the average DEA score was 0.48. The correlation between the two sets of scores was quite high, and there was no indication that lower costs resulted in lower quality. For-profit facilities were significantly more efficient than not-for-profit facilities.
Conclusions. Multiple studies of nursing homes have found evidence of inefficiency, but virtually all have had measurement problems that raise questions about the results. This analysis, which focuses on a process with much simpler measurement issues, finds evidence of inefficiency that is largely consistent with earlier studies. Making nursing homes more efficient merits closer attention as a strategy for improving care. Increasing efficiency by adopting well-designed, reliable processes can simultaneously reduce costs and improve quality.