Using a unique survey of more than 7,000 respondents conducted immediately after the first wave of the COVID-19 pandemic in Italy, we investigate potential drivers of the job satisfaction of healthcare workers. Relying on a representative sample of Italian physicians and nurses, we show that, in addition to personal characteristics (e.g., age, gender, health status), contextual factors (i.e., working conditions) play the leading role in explaining variation in the level of satisfaction (58%). In particular, working in a high-quality facility increases worker satisfaction and willingness to remain in the profession, and in the current medical specialization, while working in a province with a perceived shortage of medical personnel yields the opposite result. Direct experience with COVID-19 (e.g., having tested positive) is not significantly correlated with the level of job satisfaction, which is instead significantly reduced by changes in the working conditions caused by the health emergency.
Fee equalization in health care brings under a unique tariff several medical treatments, coded under different Diagnosis Related Groups (DRGs). The aim is to improve healthcare quality and efficiency by discouraging unnecessary, but better-paid, treatments. We evaluate its effectiveness on childbirth procedures to reduce overuse of c-sections by equalizing the DRGs for vaginal and cesarean deliveries. Using data from Italy and a difference-indifferences approach, we show that setting an equal fee decreased c-sections by 2.5%. This improved the appropriateness of medical decisions, with more low-risk mothers delivering naturally and no significant changes in the incidence of complications for vaginal deliveries. Our analysis supports the effectiveness of fee equalization in avoiding c-sections, but highlights the marginal role of financial incentives in driving c-section overuse. The observed drop was only temporary and in about a year the use of C-section went back to the initial level. We found a greater reduction in lower quality, more capacity-constrained hospitals. Moreover, the effect is driven by districts where the availability of Ob-Gyn specialists is higher and where women are predominant in the gender composition of Ob-Gyn specialists.
We investigate potential mechanisms of information transmission among patients when explaining territorial variations in the use of cesarean sections. Defining networks as mothers living in the same Italian municipality (average size approximately 10,000 residents), we show that a one standard deviation increase of the incidence of cesarean sections for the 12 months before the delivery date in the future mother's municipality of residence increases the probability of her receiving the treatment by 3%. This result captures mainly network effects for Italian mothers, while it captures both network and neighborhood effects for foreign mothers. Both groups adjust for the transmission of complementary information, such as the incidence of complications due to cesarean sections. The selection of mothers across hospitals does not uniquely explain our results, which are robust to alternative sample selections.
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We investigate potential mechanisms of information transmission among patients when explaining territorial variations in the use of cesarean sections. Defining networks as mothers living in the same Italian municipality (average size approximately 10,000 residents), we show that a one standard deviation increase of the incidence of cesarean sections for the 12 months before the delivery date in the future mother's municipality of residence increases the probability of her receiving the treatment by 3%. This result captures mainly network effects for Italian mothers, while it captures both network and neighborhood effects for foreign mothers. Both groups adjust for the transmission of complementary information, such as the incidence of complications due to cesarean sections. The selection of mothers across hospitals does not uniquely explain our results, which are robust to alternative sample selections.
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