Address correspondence to Joanne Spetz, Ph.D., Associate Professor, Center for the Health Professions & School of Nursing, University of California, San Francisco, 3333 California Street, Suite 410, San Francisco, CA, 94118; e-mail: firstname.lastname@example.org. Nancy Donaldson, DNSc., R.N., F.A.A.N., Clinical Professor and Director, is with the Center for Research & Innovation in Patient Care, UCSF School of Nursing, San Francisco, CA. Carolyn Aydin, Ph.D., Research Scientist and CalNOC Data Manager, Nursing Research and Development, is with the Cedars-Sinai Medical Center, Los Angeles, CA. Diane S. Brown, R.N., Ph.D., F.N.A.H.Q., C.P.H.Q., Kaiser Permanente Northern California, Clinical Practice Leader, is with the Hospital Accreditation Programs, Accreditation, Regulation & Licensing, Oakland, CA.
How Many Nurses per Patient? Measurements of Nurse Staffing in Health Services Research
Version of Record online: 5 MAY 2008
© Health Research and Educational Trust
Health Services Research
Volume 43, Issue 5p1, pages 1674–1692, October 2008
How to Cite
Spetz, J., Donaldson, N., Aydin, C. and Brown, D. S. (2008), How Many Nurses per Patient? Measurements of Nurse Staffing in Health Services Research. Health Services Research, 43: 1674–1692. doi: 10.1111/j.1475-6773.2008.00850.x
- Issue online: 20 SEP 2008
- Version of Record online: 5 MAY 2008
- Nurse staffing;
- hospital surveys;
Objective. To compare alternative measures of nurse staffing and assess the relative strengths and limitations of each measure.
Data Sources/Study Setting. Primary and secondary data from 2000 and 2002 on hospital nurse staffing from the American Hospital Association, California Office of Statewide Health Planning and Development, California Nursing Outcomes Coalition, and the California Workforce Initiative Survey.
Study Design. Hospital-level and unit-level data were compared using summary statistics, t-tests, and correlations.
Data Collection/Extraction Methods. Data sources were matched for each hospital. When possible, hospital units or types of units were matched within each hospital. Productive nursing hours and direct patient care hours were converted to full-time equivalent employment and to nurse-to-patient ratios to compare nurse staffing as measured by different surveys.
Principal Findings. The greatest differences in staffing measurement arise when unit-level data are compared with hospital-level aggregated data reported in large administrative databases. There is greater dispersion in the data obtained from publicly available, administrative data sources than in unit-level data; however, the unit-level data sources are limited to a select set of hospitals and are not available to many researchers.
Conclusions. Unit-level data collection may be more precise. Differences between databases may account for differences in research findings.