Summary
One relevant cost category in the healthcare system are wages. The hospital setting in Switzerland, where wages can differ widely, is attractive because it enables an examination of the impact of wages on patient safety. We would expect that once wages differ within hospitals, it will cause differences in recruitment and retention, especially of well-trained workers, as satisfactory wage is a known significant factor in job-seeking behaviour and is important in keeping hospital workers in their current positions. Lacking well-trained workers in turn should lead to worse service quality and thus to worse patient safety. Current research has shown that hospitals with well-trained nurse staffing and work environments have better nurse and patient outcomes. However, many researchers fail to account for wage effects, the neglect of which may confound findings. Objectives: To describe physician and nurse wages in Swiss hospitals and to identify their main drivers (aim 1). To assess the association between physician and nurse wage and patient safety (aim 2). To conduct a cost-effectiveness analysis and a budget impact analysis of hospitals’ investments in nurses’ and physicians’ wages. (aim 3). Methodology: I will access 2 datasets from The Swiss Federal Statistical Office: the hospital statistics (4 subsets on the hospital level) and the medical statistics (inpatient episodes in the hospital on individual level). To test my hypothesis (aim 1, 2), I will use regression analyses with the wage per full-time equivalent as dependent variable. I will adjust the results for employers’ characteristics on the hospital level and individual patient characteristics as possible confounding variables. As the dataset is large (>1.2 million cases/year), I will use also Generalized Additive Models in order to adjust for clustering. Besides regression analysis, I will perform also Bayesian analysis in order to explore uncertainty of the results estimate. All analyses will be conducted in R
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| Web resources: | https://cordis.europa.eu/project/id/101029311 |
| Start date: | 01-02-2022 |
| End date: | 01-12-2024 |
| Total budget - Public funding: | 191 149,44 Euro - 191 149,00 Euro |
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Original description
One relevant cost category in the healthcare system are wages. The hospital setting in Switzerland, where wages can differ widely, is attractive because it enables an examination of the impact of wages on patient safety. We would expect that once wages differ within hospitals, it will cause differences in recruitment and retention, especially of well-trained workers, as satisfactory wage is a known significant factor in job-seeking behaviour and is important in keeping hospital workers in their current positions. Lacking well-trained workers in turn should lead to worse service quality and thus to worse patient safety. Current research has shown that hospitals with well-trained nurse staffing and work environments have better nurse and patient outcomes. However, many researchers fail to account for wage effects, the neglect of which may confound findings. Objectives: To describe physician and nurse wages in Swiss hospitals and to identify their main drivers (aim 1). To assess the association between physician and nurse wage and patient safety (aim 2). To conduct a cost-effectiveness analysis and a budget impact analysis of hospitals’ investments in nurses’ and physicians’ wages. (aim 3). Methodology: I will access 2 datasets from The Swiss Federal Statistical Office: the hospital statistics (4 subsets on the hospital level) and the medical statistics (inpatient episodes in the hospital on individual level). To test my hypothesis (aim 1, 2), I will use regression analyses with the wage per full-time equivalent as dependent variable. I will adjust the results for employers’ characteristics on the hospital level and individual patient characteristics as possible confounding variables. As the dataset is large (>1.2 million cases/year), I will use also Generalized Additive Models in order to adjust for clustering. Besides regression analysis, I will perform also Bayesian analysis in order to explore uncertainty of the results estimate. All analyses will be conducted in RStatus
SIGNEDCall topic
MSCA-IF-2020Update Date
28-04-2024
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