Contact

Prof. Dr. Kathrin Boerner

+49(441)798 - 2896

Division for Prevention and Rehabilitation Research
Department of Health Services Research
School of Medicine and Health Sciences
Carl von Ossietzky University Oldenburg 
Germany

Postal address: 
Carl von Ossietzky Universität Oldenburg 
26111 Oldenburg 
Germany
 

Visitor address: 
Campus Haarentor, Building V04
Ammerländer Heerstraße 140
26129 Oldenburg

BAStell

BAStell - Offer more, demand less? Retention measures and job requirements in physician job advertisements of hospitals

Scientific project leaders:
Prof. Dr. Lena Ansmann
Helge Schnack

Operative project leader:
Helge Schnack

Student assistants:
Hannah Ramsauer

Duration:
1.03.2021 – 31.03.2022

Funding institution:
Own resources

Project description:
The demand for physicians in the German hospital sector has risen steadily in recent years, while in contrast the supply of physicians has changed little. This has led to a change in the labor market position of physicians, and competition for physicians between hospitals has increased. On the one hand, this leads to hospitals expanding their retention measures in order to attract physicians, and on the other hand, hospitals lower their job requirements for physicians.

The project examines how hospitals react to the changed labor market position of physicians. It examines which retention measures hospitals undertake to increase their attractiveness (e.g. flexible working time) and which job requirements hospitals expect from physicians (e.g. license to practice medicine). Therefore, physician job advertisements of hospitals in the German employment websites “Ärztestellen.de”, “Jobs.springermedizin.de”, “Krankenhaus-Stellen.de” and “Jobs.kliniken.de” will be examined. In a first step, the collected job advertisements are analyzed via content analysis. In a second step, a data set is created on the basis of the content analysis and further hospital-specific data (e.g. ownership or location). The data will be analyzed descriptively, by variance analysis, and via multi-level regression analysis.

(Changed: 20 Jun 2024)  | 
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