Shira G Winter1,2, Ann P Bartel3, Pamela B de Cordova4, Jack Needleman5,6, Susan K Schmitt7,8, Patricia W Stone9, Ciaran S Phibbs7,8. 1. Center for Innovation to Implementation, Veterans Affairs Palo Alto Health Care System, Palo Alto, California, USA. 2. Stanford University School of Medicine, Stanford, California, USA. 3. Columbia Business School, New York, New York, USA. 4. Rutgers, The State University of New Jersey School of Nursing, Newark, New Jersey, USA. 5. Department of Health Policy and Management, UCLA Fielding School of Public Health, Los Angeles, California, USA. 6. UCLA Center for Health Policy Research, Los Angeles, California, USA. 7. Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA. 8. Health Economics Resource Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, California, USA. 9. Columbia University School of Nursing, New York, New York, USA.
Abstract
OBJECTIVE: To examine how estimates of the association between nurse staffing and patient length of stay (LOS) change with data aggregation over varying time periods and settings, and statistical controls for unobserved heterogeneity. DATA SOURCES/STUDY SETTING: Longitudinal secondary data from October 2002 to September 2006 for 215 intensive care units and 438 general acute care units at 143 facilities in the Veterans Affairs (VA) health care system. RESEARCH DESIGN: This retrospective observational study used unit-level panel data to analyze the association between nurse staffing and LOS. This association was measured over both a month-long and a year-long period, with and without fixed effects. DATA COLLECTION: We used VA administrative data to obtain patient data on the severity of illness and LOS, as well as labor hours and wages for each unit by month. PRINCIPAL FINDINGS: Overall, shorter LOS was associated with higher nurse staffing hours and lower proportions of hours provided by licensed professional nurses (LPNs), unlicensed personnel, and contract staff. Estimates of the association between nurse staffing and LOS changed in magnitude when aggregating data over years instead of months, in different settings, and when controlling for unobserved heterogeneity. CONCLUSIONS: Estimating the association between nurse staffing and LOS is contingent on the time period of analysis and specific methodology. In future studies, researchers should be aware of these differences when exploring nurse staffing and patient outcomes.
OBJECTIVE: To examine how estimates of the association between nurse staffing and patient length of stay (LOS) change with data aggregation over varying time periods and settings, and statistical controls for unobserved heterogeneity. DATA SOURCES/STUDY SETTING: Longitudinal secondary data from October 2002 to September 2006 for 215 intensive care units and 438 general acute care units at 143 facilities in the Veterans Affairs (VA) health care system. RESEARCH DESIGN: This retrospective observational study used unit-level panel data to analyze the association between nurse staffing and LOS. This association was measured over both a month-long and a year-long period, with and without fixed effects. DATA COLLECTION: We used VA administrative data to obtain patient data on the severity of illness and LOS, as well as labor hours and wages for each unit by month. PRINCIPAL FINDINGS: Overall, shorter LOS was associated with higher nurse staffing hours and lower proportions of hours provided by licensed professional nurses (LPNs), unlicensed personnel, and contract staff. Estimates of the association between nurse staffing and LOS changed in magnitude when aggregating data over years instead of months, in different settings, and when controlling for unobserved heterogeneity. CONCLUSIONS: Estimating the association between nurse staffing and LOS is contingent on the time period of analysis and specific methodology. In future studies, researchers should be aware of these differences when exploring nurse staffing and patient outcomes.
Authors: Jack Needleman; Peter Buerhaus; V Shane Pankratz; Cynthia L Leibson; Susanna R Stevens; Marcelline Harris Journal: N Engl J Med Date: 2011-03-17 Impact factor: 91.245
Authors: Grant R Martsolf; Teresa B Gibson; Richele Benevent; H Joanna Jiang; Carol Stocks; Emily D Ehrlich; Ryan Kandrack; David I Auerbach Journal: Health Serv Res Date: 2016-02-21 Impact factor: 3.402
Authors: Shira G Winter; Ann P Bartel; Pamela B de Cordova; Jack Needleman; Susan K Schmitt; Patricia W Stone; Ciaran S Phibbs Journal: Health Serv Res Date: 2021-09-02 Impact factor: 3.402
Authors: Patricia W Stone; Cathy Mooney-Kane; Elaine L Larson; Teresa Horan; Laurent G Glance; Jack Zwanziger; Andrew W Dick Journal: Med Care Date: 2007-06 Impact factor: 2.983
Authors: Shira G Winter; Ann P Bartel; Pamela B de Cordova; Jack Needleman; Susan K Schmitt; Patricia W Stone; Ciaran S Phibbs Journal: Health Serv Res Date: 2021-09-02 Impact factor: 3.402