Optimizing the Practice Environment for Medical Staff in the Post-pandemic Era: A Discrete Choice Experiment - Wu, Peilin; Li, Zhenjing; Guo, Wei; Wang, Li; Chang, Xiangxiang; Zhang, Yanqun; Wang, Li; Wang, Lidan; Liu, Qunying (Frontiers in Public Health, 2022)
Objective: This study aimed to elicit the stated job preferences of medical staff in China and identify the relative importance of this preference in providing decision-making references to improve the practice environment of medical staff. Methods: We used an online discrete choice experiment (DCE) survey instrument to understand the job preferences of medical staff (doctors and nurses) in tertiary hospitals in Anhui. Attributes and levels were generated using qualitative methods, and four attributes were considered: career development, workload, respect from society, and monthly income. A set of profiles was created using a D-efficiency design. The data were analyzed considering potential preference heterogeneity, using the conditional logit model and the latent class logit (LCL) model. Results: A total of 789 valid questionnaires were included in the analysis. Career development, workload, respect from society, and monthly income were significant factors that influenced job preferences. Three classes were identified based on the LCL model, and preference heterogeneity among different medical staff was demonstrated. Class 1 (16.17%) and Class 2 (43.51%) valued respect from society most, whereas Class 3 (40.32%) prioritized monthly income. Conclusion: We found that when respect from society was raised to a satisfactory level (50-75% positive reviews), the probability of medical staff choosing a certain job increased by 69.9%. We found that respect from society was the preferred attribute overall, while workload, monthly income, and career development were all key factors in the medical staff’s job choices. The heterogeneity of their preferences shows that effective policy interventions should be customized to accommodate these different medical staff preferences.