The health care sector in the economies of the European Union: an overview using an input-output framework.

BACKGROUND: This study aims to analyse the relative importance of the health care sector (health care activities and services), its interrelations with the rest of productive activities, aggregate supply and demand, employment requirements and apparent labour productivity in the European Union (EU) economy as a whole, and in the economies of member countries. METHODS: The methodology used is based on input-output analysis. Data are extracted from National Accounts and, specifically, from the input-output framework for 2010. Data in national currencies are adjusted using as a conversion factor, specific purchasing power parities for health. RESULTS: In the EU, market production predominates in the provision of health care activities, which are financed mainly by public funding. However, there is significant variability among countries, and, in fact, non-market production predominates in most EU countries. The health care sector has direct backward and forward linkages lower than the average for all sectors of the economy and the average for the services sector. Thus, this sector is relatively independent of the rest of the productive structure in the EU. The health care activities industry is key because of its ability to generate value added and employment. Regarding apparent labour productivity, there are significant differences among EU countries, showing that productivity is positively related to the weight of market production in health care activities and negatively related to the number of hours worked per person employed. CONCLUSIONS: Our results provide useful insights for health authorities in the EU, as they analyse the effect of health policies on macroeconomic indicators using an input-output framework, as well as comparing these effects with those in EU member countries. To the best of our knowledge, an analysis of the health care sector in the EU economy and the countries that integrate it using an input-output framework has not been undertaken. In addition, to compare health care expenditure between countries, data in national currencies have been adjusted using specific purchasing power parities for "health", and not ones referring to the total economy (GDP), which is common practice in many previous studies.

Hospital productivity bias when not adjusting for cost heterogeneity: The case of Spain.

This research quantifies the bias caused in hospital productivity measurements when cost heterogeneity is not considered. A multi-output stochastic cost frontier under a normalised translog specification is used to approximate the structure of technology of a sample of public general hospitals in Spain during the period 2002-2009. To control for observable heterogeneity in costs, a set of variables related to hospital characteristics are included in the cost frontier specification (i.e., hospital complexity, degree of specialisation, availability of outpatient clinics, variety of high-technology equipment available, teaching activity and quality of care), whereas unobservable heterogeneity is accounted for by means of individual dummy variables. A measure of hospitals' cost efficiency is first obtained, and the analysis is then completed by measuring and decomposing the total factor productivity index (TFP-I) change. Findings reveal that controlling for heterogeneity decreases total productivity from an annual average rate of 0.028% to 1.330%, mainly driven by the negative contribution of the cost efficiency change component. Hence, a bias of 1.303 percentage points in the overall TFP-I is found as consequence of not controlling for heterogeneity. In addition to this, if heterogeneity factors are not accounted for, the mean cost efficiency index during the period analysed is 0.730, figure that increases up to 0.974 if heterogeneity is considered. Hence, the omission of heterogeneity leads to a bias of 24.4 percentage points in the mean cost efficiency. Therefore, not adjusting for heterogeneity in costs gives rise to distorted measurements of hospital productivity, as well as distortions in the contribution of each of its components, which may lead to the adoption of inadequate policies and decisions on resource allocation.

The effect of a change in co-payment on prescription drug demand in a National Health System: The case of 15 drug families by price elasticity of demand.

OBJECTIVES: To test the heterogeneity of the effect of a change in pharmaceutical cost-sharing by therapeutic groups in a Spanish region. METHODS: Data: random sample (provided by the Canary Islands Health Service) of 40,471 people covered by the Spanish National Health System (SNHS) in the Canary Islands. The database includes individualised monthly-dispensed medications (prescribed by the SNHS) from one year before (August 2011) to one year after (June 2013) the Royal Decree Law 16/2012 (RDL 16/2012). Sample: two intervention groups (low-income pensioners and middle-income working population) and one control group (low-income working population). Empirical model: quasi-experimental difference-in-differences design to study the change in consumption (measured in number of monthly Defined Daily Dose (DDDs) per individual) among 13 therapeutic groups. The policy break indicator (three-level categorical variable) tested the existence of stockpiling between the reform's announcement and its implementation. We ran 16 linear regression models (general, by therapeutic groups and by comorbidities) that considered whether the exclusion of some drugs from public provision impacted on consumption more than the co-payment increase. RESULTS: General: Reduction (-13.04) in consumption after the reform's implementation, which was fully compensated by a previous increase (16.60 i.e., stockpiling) among low-income pensioners. The middle-income working population maintained its trend of increasing consumption. Therapeutic groups: Reductions in consumption after the reform's implementation among low-income pensioners in 7 of the 13 groups, which were fully compensated for by a previous increase (i.e., stockpiling) in 4 groups and partially compensated for in the remaining 3. The analysis without the excluded medicines provided fewer negative coefficients. Comorbidities: Reduction in consumption that was only slightly compensated for by a previous increase (i.e., stockpiling). CONCLUSIONS: The negative impact of cost-sharing produced, among low-income pensioners, a risk of loss of adherence to treatments, which could deteriorate the health status of individuals, especially among pensioners within the most inelastic therapeutic groups (associated with chronic diseases) and patients with comorbidities (also, associated with chronic diseases). Notwithstanding the above, this risk was more related to the exclusion of some drugs from provision than to the cost-sharing increase.

Economic crisis and obesity in the Canary Islands: an exploratory study through the relationship between body mass index and educational level.

BACKGROUND: The Canary Islands is one of the Spanish Regions with the highest obesity prevalence, and one of the Autonomous Communities that was hit hard by the economic crisis that arrived to Spain in 2008. This research studies the education-related inequalities in adult obesity in the Canary Islands and their evolution in recent years, considering the possible impact of the economic recession. METHODS: A repeated cross-sectional analysis is carried out with data obtained from the Canary Islands Health Surveys of 2004, 2009 and 2015. Obesity is measured through the body mass index (BMI). The analysis is performed using linear regression models for the general population and by gender, adjusting by age, educational attainment and island of residence. Likewise, the models also include dummy variables for each year and the corresponding interactions between the years and the education variable. RESULTS: The results show a decrease in the obesity prevalence in 2015 compared to 2009 (from 19.54 to 18.64%). An increase in the BMI of the population and that of women (+ 0.33 and + 0.59 units, respectively) in 2009, as well as a decline in the BMI of women with medium education (- 0.21 units) are also observed. Besides, there is an inverse correlation between education and BMI, and statistically significant differences among some islands. CONCLUSIONS: Obesity figures in the Canary Islands have decreased and women have been more greatly affected by the changes in BMI during the economic crisis. Due to the fact that educational attainment is a protective factor in general (and for women with medium education levels in times of crisis, in particular), regional authorities should implement actions that promote access to education and healthy lifestyles, paying attention to territorial disparities.

Socioeconomic differences in body mass index in Spain: An intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy.

Many studies have demonstrated the existence of simple, unidimensional socioeconomic gradients in body mass index (BMI). However, in the present paper we move beyond such traditional analyses by simultaneously considering multiple demographic and socioeconomic dimensions. Using the Spanish National Health Survey 2011-2012, we apply intersectionality theory and multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) to analyze 14,190 adults nested within 108 intersectional strata defined by combining categories of gender, age, income, educational achievement and living situation. We develop two multilevel models to obtain information on stratum-specific BMI averages and the degree of clustering of BMI within strata expressed by the intra-class correlation coefficient (ICC). The first model is a simple variance components analysis that provides a detailed mapping of the BMI disparities in the population and measures the accuracy of stratum membership to predict individual BMI. The second model includes the variables used to define the intersectional strata as a way to identify stratum-specific interactions. The first model suggests moderate but meaningful clustering of individual BMI within the intersectional strata (ICC = 12.4%). Compared with the population average (BMI = 26.07 Kg/m2), the stratum of cohabiting 18-35-year-old females with medium income and high education presents the lowest BMI (-3.7 Kg/m2), while cohabiting 36-64-year-old females with low income and low education show the highest BMI (+2.6 Kg/m2). In the second model, the ICC falls to 1.9%, suggesting the existence of only very small stratum specific interaction effects. We confirm the existence of a socioeconomic gradient in BMI. Compared with traditional analyses, the intersectional MAIHDA approach provides a better mapping of socioeconomic and demographic inequalities in BMI. Because of the moderate clustering, public health policies aiming to reduce BMI in Spain should not solely focus on the intersectional strata with the highest BMI, but should also consider whole population polices.