Giuliano Masiero

Quality incentives in a regulated market with imperfect information and switching costs: capitation in general practice

We model a system akin to the British National Health Service (NHS), in which general practictioners (GPs) are paid by capitation from general taxation. GPs are horizontally and vertically differentiated and compete for patients via their imperfect observed quality. We show that for any given capitation fee quality is lower and the incentive effects of the fee on quality are smaller when there is imperfect information. There are diminishing welfare gains from improving patient information but increasing welfare gains from reducing switching costs. GPs do not act efficiently to improve patient information via advertising or to reduce the costs of switching.

Socioeconomic determinants of outpatient antibiotic use in Europe

ObjectivesOutpatient antibiotic consumption widely varies across Europe. The investigation of the causes of such variation may help to identify interventions that would improve the efficient use of antibiotics. The aim of this study was to assess the impact of socioeconomic determinants and the role played by information about bacterial resistance.MethodsComparable data on systemically administered antibiotics and socioeconomic determinants in 17 European countries were available between 2000 and 2005. We estimated an ad hoc econometric model by means of a hybrid log–log functional form and random effects generalised least squares regressions. Lagged values and the instrumental variable method were applied to address endogeneity of bacterial resistance and infections. Bacterial resistance was measured by the rate of penicillin non-susceptible Streptococcus pneumoniae isolates (PNSP) and methicillin-resistant Staphylococcus aureus (MRSA).ResultsThe population income, demographic structure, density of general practitioners and their remuneration method appeared to be significant determinants of antibiotic consumption. Although countries with higher levels of bacterial resistance exhibited significantly higher levels of per capita antibiotic use, ceteris paribus, the responsiveness of antibiotic use to changes in bacterial resistance was relatively low (0.09–0.18).ConclusionsThe study confirms that socioeconomic factors should be taken into account while explaining differences in outpatient antibiotic use across countries. The impact of supply-side factors and incentives attached to payment schemes for physicians need to be considered in government interventions to reduce inequalities and improve effectiveness in antibiotic utilisation.

Small area variations and welfare loss in the use of outpatient antibiotics

This article seeks to explain local variations in the use of antibiotics in the community and to assess the welfare loss due to heterogeneous attitudes towards the risk of bacterial resistance. Quarterly data on antibiotic sales from 240 small areas in Switzerland over the course of one year are used. An econometric ad-hoc model with spatial lags is proposed in which the demand for antibiotics varies according to the socioeconomic characteristics of the population, the incidence of infections, antibiotic price and local health care supply. Using residual variations we then evaluate the welfare loss due to varying antibiotic prescription styles. Significant differences are observed in the per capita antibiotic consumption across local areas. Individual income, the demographic structure of the population, physician density and the price of drugs are all relevant determinants. We estimate that unexplained variations may account for 12% of the total antibiotic spending in the community, thus leading to a Euro 6.8 ml loss per year. Understanding the determinants of variations in outpatient antibiotic consumption may help to design more effective policies to counter the threat of bacterial resistance. Our estimate of the welfare loss due to heterogeneous attitudes towards antibiotic treatment is comparable to the expected cost of implementing measures to improve the dissemination of information on bacterial resistance among patients and doctors.

Migrant integration policies and health inequalities in Europe

BackgroundResearch on socio-economic determinants of migrant health inequalities has produced a large body of evidence. There is lack of evidence on the influence of structural factors on lives of fragile groups, frequently exposed to health inequalities. The role of poor socio-economic status and country level structural factors, such as migrant integration policies, in explaining migrant health inequalities is unclear. The objective of this paper is to examine the role of migrant socio-economic status and the impact of migrant integration policies on health inequalities during the recent economic crisis in Europe.MethodsUsing the 2012 wave of Eurostat EU-SILC data for a set of 23 European countries, we estimate multilevel mixed-effects ordered logit models for self-assessed poor health (SAH) and self-reported limiting long-standing illnesses (LLS), and multilevel mixed-effects logit models for self-reported chronic illness (SC). We estimate two-level models with individuals nested within countries, allowing for both individual socio-economic determinants of health and country-level characteristics (healthy life years expectancy, proportion of health care expenditure over the GDP, and problems in migrant integration policies, derived from the Migrant Integration Policy Index (MIPEX).ResultsBeing a non-European citizen or born outside Europe does not increase the odds of reporting poor health conditions, in accordance with the “healthy migrant effect”. However, the country context in terms of problems in migrant integration policies influences negatively all of the three measures of health (self-reported health status, limiting long-standing illnesses, and self-reported chronic illness) in foreign people living in European countries, and partially offsets the “healthy migrant effect”.ConclusionsPolicies for migrant integration can reduce migrant health disparities.

Disentangling spillover effects of antibiotic consumption: a spatial panel approach

Literature on socioeconomic determinants of antibiotic consumption in the community is limited to few countries using cross-sectional data. This article analyses regional variations in outpatient antibiotics in Italy using a balanced panel dataset covering the period 2000 to 2008. We specify an econometric model in which antibiotic consumption depends upon demographic and socioeconomic characteristics of the population, the supply of health care services in the community, and antibiotic copayments. The model is estimated by means of Ordinary Least Squares (OLS) techniques with Fixed Effects (FE). The implications of consumption externalities across geographical areas are investigated by means of Spatial-Lag and Spatial-Error models (SLFE and SEFE). We find significant and positive income elasticity and negative effects of copayments. Antibiotic use is also affected by the age structure of the population and the supply of community health care. Finally, we find evidence of spatial dependency in the use of antibiotics across regions. This suggests that regional policies (e.g. public campaigns) aimed at increasing efficiency in antibiotic consumption and controlling bacterial resistance may be influenced by policy makers in neighbouring regions. There will be scope for a strategic and coordinated view of regional policies towards the use of antibiotics.

Implications of global budget payment system on nursing home costs

Pressure on health care systems due to the increasing expenditures of the elderly population is pushing policy makers to adopt new regulation and payment schemes for nursing home services. We consider the behavior of nonprofit nursing homes under different payment schemes and empirically investigate the implications of prospective payments on nursing home costs under tightly regulated quality aspects. To evaluate the impact of the policy change introduced in 2006 in Southern Switzerland - from retrospective to prospective payment - we use a panel of 41 homes observed over a 10-years period (2001-2010). We employ a fixed effects model with a time trend that is allowed to change after the policy reform. There is evidence that the new payment system slightly reduces costs without impacting quality.

Is higher nursing home quality more costly

Widespread issues regarding quality in nursing homes call for an improved understanding of the relationship with costs. This relationship may differ in European countries, where care is mainly delivered by nonprofit providers. In accordance with the economic theory of production, we estimate a total cost function for nursing home services using data from 45 nursing homes in Switzerland between 2006 and 2010. Quality is measured by means of clinical indicators regarding process and outcome derived from the minimum data set. We consider both composite and single quality indicators. Contrary to most previous studies, we use panel data and control for omitted variables bias. This allows us to capture features specific to nursing homes that may explain differences in structural quality or cost levels. Additional analysis is provided to address simultaneity bias using an instrumental variable approach. We find evidence that poor levels of quality regarding outcome, as measured by the prevalence of severe pain and weight loss, lead to higher costs. This may have important implications for the design of payment schemes for nursing homes.

Rational habits in residential electricity demand

Dynamic partial adjustment models of residential electricity demand account for the fact that households may not adjust electricity consumption immediately in response to changes in prices, income, and other relevant factors, because of behavioral habits or adjustment costs for the capital stock of appliances. However, forward-looking behavior is generally neglected. Expectations about future prices or consumption may have an impact on current decisions. In this paper we propose rational habit models for residential electricity demand and apply them to a panel of 48 US states between 1995 and 2011. We estimate lead consumption models using fixed effects, instrumental variables, and the GMM Blundell-Bond estimator. We find that expectations about future consumption significantly influence current consumption decisions, which suggests that households behave rationally when making electricity consumption decisions. This novel approach may improve our understanding of the dynamics of residential electricity demand and the evaluation of the effects of energy policies.