Medical Malpractice Liability and Its Effect on Prenatal Care Utilization and Infant Health
ABSTRACT In this paper we conduct the first national evaluation of the effect of malpractice liability pressure, as measured by malpractice premiums, on prenatal care utilization and infant health. Our results indicate that a decrease in malpractice premiums that would result from a feasible policy reform would lead to a decrease in the incidence of late prenatal care by between 3.0 and 5.9% for black women and between 2.2 and 4.7% for white women. Although, we found evidence that malpractice liability pressure was associated with greater prenatal care delay and fewer prenatal care visits, we did not find evidence that such pressure negatively affected infant health.
- SourceAvailable from: SSRN
[Show abstract] [Hide abstract]
- "Dubay and Kaestner (1999) found that greater malpractice pressure leads to a higher probability of Cesarean delivery but no significant improvement in Apgar scores. Later, Dubay et al. (2001) found that liability pressure reduced utilization of prenatal carein some low-income cases. Sloan et al (1995), using mortality of the child and Apgar scores as indicators of health outcomes, found no systematic improvement in birth outcomes due to increased threat of medical malpractice litigation. "
ABSTRACT: This study evaluates tort reform's impact on private health insurance coverage. Tort reform may reduce costly damage awards and defensive medicine. On the other hand, tort reform may increase health care costs by reducing doctors' caretaking or increasing questionable treatments. Reducing health care costs should increase health insurance coverage rates, while cost increases should decrease coverage rates. We find that between 1981 and 2007 damage caps, collateral source reform, and joint-and-several liability reform increased health insurance coverage among price-sensitive groups between one-half and one percentage points each. We conclude that tort reform reduces health care costs, at least for price-sensitive groups. Copyright 2010, Oxford University Press.American Law and Economics Review 09/2010; 12(2):263-264. DOI:10.1093/aler/ahq003 · 1.14 Impact Factor
[Show abstract] [Hide abstract]
- "Physicians may have a stronger defensive response to women with Medicaid and other low income women as they are more likely to have a bad birth outcome and physicians may perceive them as more likely to file a malpractice claim (Dubay et al., 1999). Moreover, physicians respond differently to different reimbursement policies of Medicaid and private insurance (Dubay et al., 2001). "
ABSTRACT: Although “defensive medicine” is defined as utilization of medical resources beyond the optimal level of use due to malpractice threat, empirical studies often consider increased use or provision of medical care itself as the indicator of defensive medicine. This study estimates the changes in resource use as well as health outcomes in obstetric care due to medical malpractice lawsuits. Improved health outcomes associated with medical malpractice pressure may lead to cost-savings in the health sector. If this cost-saving exceeds the marginal cost of malpractice-triggered use of medical services, the increased use represents an improvement in net social benefits rather than a decline, as should be the case for defensive medicine. To measure malpractice risk, we use the National Practitioner Data Bank (NPDB), a comprehensive data set of all paid claims for medical malpractice. For the inpatient data we use the Nationwide Inpatient Sample (NIS) which provides detailed information on all inpatient hospital stays. Unlike other studies, we have estimated the effect of malpractice risk on “resource use” after controlling for underlying risk factors associated with obstetric interventions. Cross-state variations in risk-factors may confound the effect of malpractice on resource use. In this study, all pregnancy cases have been divided into two groups: pregnant women with and without the presence of medical indications for C-section. Results suggest that a higher degree of malpractice risk increases the probability of C-section delivery for both the groups. For majority of patients (86% of all patients), short-run marginal benefits are found to be higher than the marginal costs implying that malpractice pressure has actually pushed resource use towards a higher level from a sub-optimal level. Presence of defensive medicine may be a problem only for Medicaid patients with clinical indications for Csection.SSRN Electronic Journal 08/2009; DOI:10.2139/ssrn.1443555
[Show abstract] [Hide abstract]
- "Some studies that use instrumental variables were described in Section 2 above (Arendt (2005); Auld and Sidhu (2005); Evans and Lien (2005); Gardner and Oswald (2007); Lakdawalla et al. (2006); Lindahl (2005)). Other applications are too numerous to describe in detail here (some examples are Cawley et al. (2006); Contoyannis et al. (2005); Dor et al. (2006); Dubay et al. (2001); Dusheiko et al. (2004); Dusheiko et al. (2007); Elliott et al. (2007) "
ABSTRACT: Much of the empirical analysis done by health economists seeks to estimate the impact of specific health policies and the greatest challenge for successful applied work is to find appropriate sources of variation to identify the treatment effects of interest. Estimation can be prone to selection bias, when the assignment to treatments is associated with the potential outcomes of the treatment. Overcoming this bias requires variation in the assignment of treatments that is independent of the outcomes. One source of independent variation comes from randomised controlled experiments. But, in practice, most economic studies have to draw on non-experimental data. Many studies seek to use variation across time and events that takes the form of a quasi-experimental design, or “natural experiment”, that mimics the features of a genuine experiment. This chapter reviews the data and methods that are used in applied health economics with a particular emphasis on the use of panel data. The focus is on nonlinear models and methods that can accommodate unobserved heterogeneity. These include conditional estimators, maximum simulated likelihood, Bayesian MCMC, finite mixtures and copulas.