Author
Listed:
- Bjerregaard, Uffe
(University of Southern Denmark, DaCHE - Danish Centre for Health Economics)
- Hølge-Hazelton, Bibi
(Institute of Regional Studies, University of Southern Denmark; Zealand University Hospital)
- Rud Kristensen, Søren
(University of Southern Denmark, DaCHE - Danish Centre for Health Economics)
- Rose Olsen, Kim
(University of Southern Denmark, DaCHE - Danish Centre for Health Economics)
Abstract
Objectives: To study and compare the longitudinal and cross-sectional relationship between nurse hours perpatient day and patient outcomes (30‐day mortality and length of stay [LOS]). Data source: Retrospective administrative register data (2015-2017) with all hospital admissions, LOS, andmortality rates from five medical departments combined with monthly data on staffing levels of registerednurses, physicians, and nurse assistants from the hospital’s payroll systems, as well as detailed patient-levelmorbidity and sociodemographic characteristics. Study design: We used a flexible within‐between random effect (REWB) model to exploit longitudinal andcross-sectional variation among homogenous medical departments. We applied a rich patient‐level dataset, leaving little risk of omitted variable bias due to patient‐level heterogeneity. Data Collection: The study population covered all hospital inpatient discharges from five medical departments over the period 2015-17 (N=172,132). Hospital payroll data were merged using hospital department identification codes. Principal findings: For both outcomes, we found evidence of endogeneity in within estimates when failing to control for patient heterogeneity. When controlling for patient characteristics, we found that a greater nurse to-patient ratio was associated with a statistically significant decrease in LOS when using both within- and between‐department variations. However, only between estimates were significant for nurses when it came to mortality, whereas the significance of the within estimate was absorbed by physicians. Conclusions: Most longitudinal studies apply fixed effects and, hence, only assess within variations. We found that between estimates were higher in magnitude and were more robust to omitted variable bias than within estimates. Therefore, as between variations are likely to identify structural recruitment problems, we argue for the importance of studying between estimators as well as in longitudinal studies.
Suggested Citation
Bjerregaard, Uffe & Hølge-Hazelton, Bibi & Rud Kristensen, Søren & Rose Olsen, Kim, 2020.
"Nurse staffing and patient outcomes: Analyzing within- and between-variation,"
DaCHE discussion papers
2020:3, University of Southern Denmark, Dache - Danish Centre for Health Economics.
Handle:
RePEc:hhs:sduhec:2020_003
DOI: 10.21996/d5ef-1y69
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hhs:sduhec:2020_003. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Christian Volmar Skovsgaard (email available below). General contact details of provider: https://edirc.repec.org/data/hesdudk.html .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.