Lorena Androutsou (p), Theodore Metaxas

EU Member States in 2013 were engaged to adopt and implement the cross-borders health Directive 2011/24/EU (European Commission, 2011), which is the key tool offering an opportunity for access to high-quality healthcare to another Member State. Under this directive medical tourism and cross borders health can be considered as related terms regarding the freedom to move to get medical treatment to any EU Member State within the defined procedures for reimbursement. Due to the rising number of citizens mobility, there is a need to look in depth into the determinant role of the cross-borders health/medical tourism industry and measure its efficiency. Little is known empirically with regards to the efficiency of this industry. To our knowledge this is the first study that aims to use available data that would provide evidence on measuring the efficiency of the cross-borders health / medical tourism industry in Europe, by using Data Envelopment Analysis. This study has used 2 models each of which had 3 inputs (hospital beds, total number of practising physicians, practising qualified nurses and midwives) and model 1: 2 outputs (hospital discharges in-patients, number of non-resident people among all people discharged from hospital); model 2: 2 outputs (day cases/outpatients, number of non-resident people among all people discharged from hospital). DEA was run using input oriented model. The results of the two models show that the Members States health systems were very efficient handling non-residents in-patients for the years 2010-2014, however when managing day cases/outpatients the efficiency scores dropped. Moreover, there were no considerable differences in scores before or after the year 2013 – the year of the Directive 2011/24/EU engagement. The findings of this study will be useful to industry, academics, policymakers, media, and anyone seeking to better understand cross borders health and medical tourism industry efficiency.

Anna-Theresa Renner (p)

After the recent financial crises, reductions in healthcare spending are considered relevant austerity measures in many European countries. One possibility to achieve such reductions in a publicly financed healthcare system is to cut hospital costs by reducing avoidable hospitalisations for conditions that are best treated in the primary healthcare sector. Without jeopardizing the health of the population, this goal can only be attained by increasing the efficiency and accessibility of primary healthcare. This is especially relevant for countries that do not exert any direct restrictions on the utilization of healthcare services, and which might therefore suffer, from supplier-induced-demand, and consumer moral hazard; both of these behaviours likely lead to inefficiencies. The aim of this study is to investigate whether regional variations in avoidable hospitalisations are related to consumer or to supply-side characteristics or both.
As patients in Austria are not restricted to certain regional outpatient healthcare providers, the supply of geographically close districts is of high importance. Therefore, an analysis of demand- and supply-side characteristics on avoidable hospitalisations, has to take into account spatial dependencies. To operationalize the notion of avoidable hospitalisations we used a set of acute and chronic clinical conditions for which hospitalisation can potentially be avoided by high-quality primary healthcare. There is considerable variation in the rates of avoidable hospitalisations between districts, ranging from under 28 to over 65 per 1,000 inhabitants (2013). To investigate the drivers of these variations, a panel dataset containing information about hospitalisation rates for all Austrian political districts from 2008 to 2013 was exploited. For the initial selection of relevant covariates Bayesian model averaging was used with time and regional fixed effects. Based on the results the relevant explanatory variables were selected and included in different spatial panel model specifications (e.g. spatial error or spatial Durbin error model). Various spatial weights matrices, such as first-order queen contiguity, 5-nearest-neighbours and distance-decay were applied.
The results regarding the signs and significance of the main covariates are consistent across all estimated model specifications. Education was insignificant in all specifications, whereas age significantly increases avoidable hospitalisations. The coefficients on care allowance and long-term unemployment were both significant, but with opposing signs. The included supply-side variables - outpatient physician density, outpatient specialist’s age (proxying experience) and hospital beds - showed a significantly negative effect of GP density and age of specialists. The coefficient on specialist density was positive, but not significant, in all model specifications.

Aileen Murphy (p), Jane Bourke

Despite efforts to create a universal, single-tiered health system in Ireland, a “two-tiered” system persists. The latter means those who can afford to pay privately or have private health insurance receive faster access to diagnostics and treatments. While those who access health care through the public system (financed through general taxation) face long waiting lists. The austerity measures ensuing from the financial crisis has impeded progress towards universal health care, resulting in poorer access to essential healthcare through the public system.

Recent forecasts, project continued rapid population growth in Ireland, and so increased demand for health and social care is expected. In particular, this will be driven by expected increases in older age cohorts. Based on these population growth forecasts and current utilisation patterns, increased demand for both public and private hospitals is anticipated. To date, limited data on private hospital care utilisation and expenditure has constrained our understanding of this important section of the Irish health care system. Furthermore, we know little about regional disparities in the utilisation of private hospital care across Ireland. This study aims to examine expenditures on private hospitals to examine utilisation patterns from a regional perspective, whilst controlling for social demographic, economic and health characteristics. Regression analysis, employing nationally collected data from the EU-SILC (2015), will be performed.

Investigating if regional disparities exist and which regions are most reliant on private hospital care is an important and may have future policy implications for implementing universal health care. In addition, the results of the study could be used to inform decision-making with respect to hospital infrastructure, as well as associated staffing and resource issues. This is of particular importance in the context of the recently launched National Development Plan (2018-2027).