Paola Bertoli

Does Experience Rating Improve Obstetric Practices? Evidence from Geographical Discontinuities in Italy

Using data from 2002 to 2009 inpatient discharge records on deliveries in the Italian region of Piedmont, we assess the impact of an increase in malpractice pressure on obstetric practices, as identified by the introduction of experience-rated malpractice liability insurance. Our identification strategy exploits the exogenous location of public hospitals in court districts with and without schedules for noneconomic damages. We perform difference-in-differences and difference-in-discontinuities analyses. We find that the increase in medical malpractice pressure is associated with a decrease in the probability of performing a C-section from 2.3 to 3.7 percentage points (7% to 11.6% at the mean value of C-section) with no consequences for a broadly defined measure of complications or neonatal outcomes. We show that these results are robust to the different methodologies and can be explained by a reduction in the discretion of obstetric decision making rather than by patient cream skimming.

Does Experience Rating Improve Obstetric Practices? Evidence from Italy

Using inpatient discharge records from the Italian region of Piedmont, we estimate the impact of an increase in malpractice pressure brought about by experience-rated liability insurance on obstetric practices. Our identification strategy exploits the exogenous location of public hospitals in court districts with and without schedules for noneconomic damages. We perform difference-in-differences analysis on the entire sample and on a subsample which only considers the nearest hospitals in the neighborhood of court district boundaries. We find that the increase in medical malpractice pressure is associated with a decrease in the probability of performing a C-section from 2.3 to 3.7 percentage points (7-11.6%) with no consequences for medical complications or neonatal outcomes. The impact can be explained by a reduction in the discretion of obstetric decision-making rather than by patient cream skimming.

The political economy of diagnosis-related groups☆

A well-established political economic literature has shown as multi-level governance affects the inefficiency of public expenditures. Yet, this expectation has not been empirically tested on health expenditures. We provide a political economy interpretation of the variation in the prices of 6 obstetric DRGs using Italy as a case study. Italy offers a unique institutional setting since its 21 regional governments can decide whether to adopt the national DRG system or to adjust/waive it. We investigate whether the composition and characteristics of regional governments do matter for the average DRG level and, if so, why. To address both questions, we first use a panel fixed effects model exploiting the results of 66 elections between 2000 and 2013 (i.e., 294 obs) to estimate the link between DRGs and the composition and characteristics of regional governments. Second, we investigate these results exploiting the implementation of a budget constraint policy through a difference-in-differences framework. The incidence of physicians in the regional government explains the variation of DRGs with low technological intensity, such as normal newborn, but not of those with high technological intensity, as severely premature newborn. We also observe a decrease in the average levels of DRGs after the budget constraint implementation, but the magnitude of this decrease depends primarily on the presence of physicians among politicians and the political alignment between the regional and the national government. To understand which kind of role the relevance of the political components plays (i.e., waste vs. better defined DRGs), we check whether any of the considered political economy variables have a positive impact on the quality of regional obstetric systems finding no effect. These results are a first evidence that a system of standardized prices, such as the DRGs, is not immune to political pressures.

Courts, Scheduled Damages, and Medical Malpractice Insurance

Medical malpractice insurance is considered a unprofitable market in many countries, and this is why many policies have been implemented to increase its attractiveness for private insurers. We test the effects of limits to noneconomic compensations- scheduled damages- using Italian data. We estimate the average treated effect of schedules and whether it depends on the judicial efficiency, measured as court backlog. Our identification rests on the partial overlap between healthcare authorities districts and judicial districts, thus the caseload of a court and malpractice events at the healthcare provider level are not perfectly correlated. On average, the adoption of schedules does not produce any significant effect on insurers and paid premiums. However, it has a robust and significant effect on the number of insurers only in inefficient courts. We further investigate these findings using data for 17,578 malpractice insurance claims. We find evidence of a composition effect among claims which is triggered by higher levels of judicial inefficiency: the more inefficient a court, the lower the probability to have a case not decided on the merits, and the higher the level of reserve and recovery per claim. These results shed light on previous conflicting evidence in the literature.

The Life-Saving Effect of Hospital Proximity

We assess the lifesaving effect of hospital proximity using data on fatality rates of road-traffic accidents. While most of the literature on this topic is based on changes in distance to the nearest hospital triggered by hospital closures and use OLS estimates, our identification comes from the exogenous variation in the proximity to cities that are allowed by law to have a hospital based on their population size. Our instrumental variable results, based on Italian municipalities data from 2000 to 2012, show that an increase by a standard deviation of distance to the nearest hospital (5 km) increases the fatality rate by 13.84% on the sample average. This is equal to a 0.92 additional death per every 100 accidents. We show that OLS estimates provide a downward biased measure of the real effect of hospital proximity because they do not fully solve spatial sorting problems. Proximity matters more when the road safety is low; the emergency service is not properly organized, and the nearest hospital has lower quality standards.

Exploring the nexus between certainty in injury compensation and treatment selection

We study the effect of reduced medical liability due to the implementation of scheduled damages on the overuse of cesarean sections. Using data from inpatient discharge records on deliveries in Italy, we exploit the fact that hospitals are distributed across court districts and that only some courts introduced schedules during the period of observation. This allows us to identify the effect of a decrease in liability using a difference-in-difference approach while minimizing the heterogeneities between treated and control hospitals. We show that decreased medical liability increases the incidence of unnecessary cesarean sections by 7 percentage points, which corresponds to a 20% increase at the mean of cesarean sections. The magnitude of the response is higher for hospitals with lower quality and that are far from consumer association headquarters. Lower schedules and higher levels of reimbursements per delivery also increase the overuse of cesarean section. The analysis of the response times, combining the difference-in-difference approach with a regression discontinuity design, shows that the response to decreased liability is already detectable in the short run. Our findings are robust to several sets of robustness checks and are not driven by anticipatory effects or a change in the composition of the treated patients.

Not All Silver Lining? The Great Recession and Road Traffic Accidents

We provide new evidence on the impact of recessions on traffic accidents by exploiting the case of Spain, where the effects of the 2008 economic crisis have been among the strongest in the developed world. We exploit differences in the incidence of the recession across Spanish provinces due to the unequal evolution of the real estate bubble across the territory. We use a unique dataset on the universe of traffic accidents in Spain between 2004 and 2011. We first follow the literature on the topic and examine the impact of the economic crisis on the probability of having a traffic accident. However, we also go one step further, as we are able to identify any changes in the composition of both victims and driving behaviors as a result of the crisis. First, our results show that the Great Recession reduced traffic accidents in Spain. Second, for the compositional effects, we report decreased probabilities of dying or reporting a serious injury. More important, we also detect an increase in the probability that people involved in an accident abuse alcohol and drugs. Our results are robust to different measures of the treatment (i.e., employment in the construction sector) and the use of a spatial fixed effects model and are not biased by anticipatory effects. Finally, we show that our findings are driven by less-populated areas. Thus, we suggest that alcohol and drug control measures be reinforced during recessions and more attention should be devoted to rural areas to to strengthen the reduction of road traffic accidents.

The life-saving effect of hospital proximity: The Life-saving Effect of Hospital Proximity

We provide a new assessment of the effect of hospital proximity in an emergency situation-road-traffic accidents-exploiting the exogenous variation in the proximity to cities that are legally allowed to have a hospital on the basis of their population size. Our instrumental variable results show that a one-standard-deviation increase in the distance to the nearest hospital (5 km) raises the fatality rate by 13.84% at the sample average. This figure is equal to 0.92 additional deaths per 100 accidents. We show that both ordinary least squares and difference-in-differences estimates, common approaches in the literature, provide a downward-biased measure of the true effect of hospital proximity because they do not fully solve spatial sorting problems. Proximity is more important when the level of road safety is low, when emergency services are less responsive, and when the nearest hospital has relatively low quality standards.