key: cord-0692797-xtk44acf
authors: García-Corchero, Juan David; Jiménez-Rubio, Dolores
title: How do policy levers shape the quality of a national health system?
date: 2021-10-21
journal: J Policy Model
DOI: 10.1016/j.jpolmod.2021.09.003
sha: 50e5e7ad34e67c3885ae88f9dfdd303e3ed08e4c
doc_id: 692797
cord_uid: xtk44acf

Poor quality of care may have a detrimental effect on access and take-up and can become a serious barrier to the universality of health services. This consideration is of particular interest in view of the fact that health systems in many countries must address a growing public-sector deficit and respond to increasing pressures due to COVID-19 and aging population, among other factors. In line with a rapidly emerging literature, we focus on patient satisfaction as a proxy for quality of health care. Drawing on rich longitudinal and cross-sectional data for Spain and multilevel estimation techniques, we show that in addition to individual level differences, policy levers (such as public health spending and the patient-doctor ratio, in particular) exert a considerable influence on the quality of a health care system. Our results suggest that policymakers seeking to enhance the quality of care should be cautious when compromising the level of health resources, and in particular, health personnel, as a response to economic downturns in a sector that traditionally had insufficient human resources in many countries, which have become even more evident in the light of the current health crisis. Additionally, we provide evidence that the increasing reliance on the private health sector may be indicative of inefficiencies in the public system and/or the existence of features of private insurance which are deemed important by patients.

Quality of care is widely recognised as a fundamental objective of a health system and is a major concern for many national and supranational organisations. Poor quality of care may have a detrimental effect on access and take-up and can become a serious barrier to the universality of health services (World Health Organization, 2019) . While most initiatives to improve health care quality focus on clinical aspects of health services, the adoption of a more patient-centred approach is becoming a universally accepted core dimension of healthcare quality (Hanefeld et al., 2017) . The use of carequality measures, from the patients' perspective, in addition to the consideration of other, more traditional health system outcomes (effectiveness, equity, efficiency, etc.), enriches the monitoring of health service performance and strengthens decision-making (Barbazza et al., 2019) . Indeed, the use of self-reported measures to evaluate policy outcomes is not exclusive to the health system, but is increasingly accepted as a valuable contribution to the evaluation of many other public policies, in line with the recommendations of Stiglitz-Sen-Fittoussi (Pak, 2020) .

One patient-centred outcome which is attracting growing attention in many countries is the level of satisfaction with the care received. In universal health systems in which patients are allowed to select the provider, such as the Netherlands and the UK, the information obtained from patient experience surveys is used not only to monitor health care delivery but also to promote patient choice. Although health care satisfaction is a self-reported quality outcome, several studies have recorded a strong J o u r n a l P r e -p r o o f association between subjective and objective measures of this parameter, which suggests that selfreported measures of satisfaction can be considered valid predictors of more objective mechanisms and can legitimately be used to evaluate the performance of health systems (Fiorentini, Robone and Verzulli, 2018) .

In this field, too, recent systematic literature reviews (Doyle et al., 2013; Price et al., 2014) provide suggestive evidence of a positive association between patient experience and clinical quality. Thus, focusing on the patient's perspective might make managers and policy makers more alert to the user's needs, perceptions and concerns and help anticipate areas of failure, thus enhancing health service performance (Pascoe, 1983; Doyle et al., 2013; Park et al., 2016) . Satisfied patients are more likely to comply with treatment recommendations, whereas lower levels of patient satisfaction might lead to an underutilisation of public services and negatively impact on public health . Previous studies have also reported that individuals who express dissatisfaction with the public health system are more likely to opt out of public health insurance, and that the privately insured are less likely to favour increased spending on the NHS, or to view public healthcare spending as a priority (Costa-Font & Jofre-Bonet, 2008 ).

In the present study we explore the key drivers of the performance of a National Health System (NHS) -in terms of patient reported quality of care-by drawing on the monitoring framework proposed by Barbazza et al., (2019) , which establishes direct links between the capacity, performance and impact of health care in terms of population health status and well-being. Given that many of the factors analysed (most notably public health expenditure and health resources) are directly subject to the influence of policy makers, our study enables a better understanding of the key drivers of quality of care with the aim of informing policymaking and in turn improving population health.

We contribute to the existing literature along several lines. First, in contrast to much previous work (see section 2.1) our study focuses on variations in health system performance (both users and nonusers of the NHS) over a long time series. Second, we use data at the regional rather than the national level, thus increasing the homogeneity in the measurement of the variables considered, and the reliability of the comparisons made (Fiorentini et al., 2018) . In addition, unlike some previous studies (e.g. Kotzian, 2009; Robone et al., 2011; Xesfingi & Vozikis, 2016) we disentangle the resources of health care funding, since there is evidence that reliance on private care might reveal certain drawbacks of a NHS (Costa-Font & García, 2003; Epstein & Jiménez-Rubio, 2019) . Finally, we scrutinise and compare the different areas within a NHS (primary, specialised, hospital and emergency services) in terms of service quality, enabling us to target policy recommendations more precisely. Our focus on the situation in Spain provides a unique opportunity to study the drivers of health care quality, given J o u r n a l P r e -p r o o f the highly decentralised nature of health services in this country and the long-time span covered by our data (2002) (2003) (2004) (2005) (2006) (2007) (2008) (2009) (2010) (2011) (2012) (2013) (2014) (2015) (2016) , including the onset of the Great Depression in 2008. In addition, since Spain was one the European countries hardest hit by the economic recession, the extended time span of our analysis provides the opportunity to consider the major financial cutbacks in the health care sector that followed the 2008 recession 3 (Grigorakis et al., 2018) and which were asymmetrically implemented across the regions (Gené-Badia et al., 2012; Gallo & Gené-Badia, 2013 ).

While we focus our analysis on multilevel modeling, our results are robust to a battery of robustness tests, including first differences estimations, which are less likely to produce spurious results, and lagged estimations of our key policy levers, to account for a non-contemporary effect of our variables of interest.

The study results suggest that regional characteristics such as public health expenditure or the doctorpatient ratio exert a considerable influence on health service quality. Another significant finding is that there seems to be a considerable interaction between private and public health sectors, as for some of the NHS services analysed, the proxy for private healthcare is negatively associated with patient satisfaction.

The remainder of this paper is organised as follows: in the following section, we conduct a review of the main existing literature in the area and describe the main characteristics of the Spanish National Health System, after which we show the empirical strategy employed. The study findings are detailed in section 4 and section 5 presents the main conclusions drawn and identifies relevant policy implications.

Several recent studies have evaluated health system reforms on the basis of self-reported health system satisfaction and other non-clinical factors (Hekkert et al., 2009; N. Valentine et al., 2010; Barbazza et al., 2019) , in contrast to previous literature in this area, which has mainly focused on the effect of demand-side characteristics ("patient expectations") usually in terms of individual covariates such as gender, education, age or income (Pascoe, 1983; Costa-Font & Jofre-Bonet, 2008; Kotzian, 2009; Price et al., 2014; Park et al., 2016; Pak, 2020) . However, in recent years, there has been growing interest in analysing the influence on service quality of the patient's socioeconomic environment and of health system supply factors. Hekkert et al. (2009) argued that although an important part of the patient satisfaction-explained variance depends on the patient's own characteristics (such as socioeconomic status), hospital-specific attributes like hospital type and size and catchment-area population density also play an important role. In this line, Robone et al. (2011) examined how the characteristics of health systems, the structure of the population and the economic, cultural and institutional characteristics of the health system context may influence patient-perceived quality and health system responsiveness in different countries 4 . This study concluded that a country's education level and overall health expenditure have a significant impact on responsiveness. On the other hand, the percentage of public health care expenditure in total expenditure is inversely related to this responsiveness, which suggests that market incentives may play an important role in promoting patient responsiveness.

In this context, Malhotra and Do (2017) explored disparities in health service quality in a large set of richer and poorer countries and found that public health expenditure appears to be closely related to patient-perceived quality, especially in the case of less well-off individuals. The authors concluded that increasing the capacity of the public health service, by improving healthcare coverage and reducing out-of-pocket expenditure, could significantly reduce socio-economic disparities in terms of health system responsiveness. Several empirical studies of the role played by publicly-financed health services have measured the capacity of the health system, for example in terms of the health care resources allocated to the health system. In this regard, Xesfingi and Vozikis (2016) reported that patient satisfaction was mostly influenced by healthcare-related indicators proxied by the proportion of clinical staff (positively) and of hospital beds (negatively). In Spain, Pérez-Romero et al. (2017) looked into the influence of socioeconomic and health factors on satisfaction with the health system. These authors highlighted the existence of considerable differences among Spanish regions in terms of supply-side factors such as total health expenditure. On the other hand, Gené-Badia et al. (2012) argued that the substantial increase in public spending that took place in Spain immediately before the 2008 recession did not seem to have directly increased the health-care satisfaction of the population.

Indeed, patient-reported satisfaction with health care was reported to have increased during the subsequent economic recession in Spain (2009 Spain ( -2011 .

Overall, most previous studies have observed a positive impact of public health-related resources on quality, proxied by satisfaction with the health services, although the results are somewhat inconclusive. In addition, owing to the cross-sectional nature of the data employed, most previous research in this respect (e.g. Gené-Badia et al., 2012; Pérez-Romero et al., 2017; Xesfingi & Vozikis, 2016) does not reflect the long-term evolution of the main variables of interest, thus ignoring the lagged effect of macroeconomic policies.

Spain has a universal health care system that is free at the point of delivery with the exception of pharmaceuticals, which may require co-payment (Bernal-Delgado et al., 2018) . To a large extent, health services are publicly provided (the public sector accounted for 70.8% of total health spending in 2019) (OECD Statistics, 2020) . Decentralisation was negotiated region by region over a period of twenty years in a transformation that was largely politically motivated (Bustillo et al., 2014; Costa-Font & Ferrer-i-Carbonell, 2019) . In addition to a comprehensive common health care package, a complementary package is provided at the discretion of each of the highly devolved Autonomous Communities.

While the Spanish NHS provides universal health care to all individuals residing in the country and is funded mainly by general taxation, the last decade has witnessed a considerable increase in the importance of health services that are publicly financed but privately produced, through different forms of management (Bernal-Delgado et al., 2018) . In addition, the proportion of the population covered by private insurance rapidly increased from 7.6 per cent in 2001 to 16.5 per cent in 2017 (OECD Statistics, 2020), a growing trend that have also experienced many other countries in recent years (OECD, 2019).

To a large extent, private insurance in Spain provides either a larger choice of providers or a faster access to health care services (duplicate insurance), a feature which is also shared by many other OECD countries.

In view of the strong decentralisation of the Spanish health system and the resulting geographic heterogeneity (see Figure 1 ), this country provides an excellent setting in which to study the drivers of 

The main dependent variable is the level of satisfaction with the Spanish public health system, as measured by the Spanish Health Barometer using the question: "How well do you think the Spanish public health system is working?". As an alternative dependent variable, we use the level of satisfaction with specific health care services, with the questions: "How would you rate the following services:

Primary Care (general practice or paediatrics), Specialist Care; Hospital service; Emergency service?".

Opinions about general and specific health care services are rated by both actual and potential users of public health services, on a scale from 1 (very dissatisfied) to 10 (very satisfied).

The socioeconomic variables considered at the individual level include gender; age; and education and employment status as proxies for socio-economic status. Finally, a set of dummies for area of residence are included to account for rurality (areas with fewer than 10,000 inhabitants). We adjust for frequency of use by including a set of dummies for respondents who made one or two health visits and those who made three or more visits, to one or more health services, during the year immediately prior to the survey. For estimations based on specific health services, the self-assessed health (SAH) status of individuals is also included to take into account the possibility of reporting heterogeneity in terms of health status, following the procedure adopted previously by Fiorentini, Ragazzi and Robone (2015) .

Among the region-specific characteristics that might be considered, we focus in particular on public health expenditure, which is a major driver of health system performance and health care satisfaction (Malhotra & Do, 2017; Xesfingi & Vozikis, 2016) . The influence of private healthcare on patients' satisfaction with the health services received is measured by reference to regional expenditure on J o u r n a l P r e -p r o o f private health insurance (PHI) per capita. Previous studies have shown that there is a high level of interdependence between public and private provision of healthcare ( Jofre-Bonet, 2000; Costa-Font & García, 2003; Augurzky & Tauchmann, 2011; Chan et al., 2015; Wang et al., 2020) , with private insurance often revealing some deficiencies in publicly provided health care. Our study also controls for public health resources in terms of clinical staff (doctors and nurses) and hospital beds, which is in line with the approach adopted by Xesinfingis and Vozikis (2016). Detailed analyses of health service resources are based on the ratios of doctors and nurses in primary and in specialised care and (for hospital and emergency services), the ratio of hospital beds. The impact of regional economic development is addressed by a dummy variable 5 which equals one if income is below the average of the sample, which we expect to highlight income-related differences among Spanish regions.

The descriptive statistics considered and the definitions of the variables employed in our estimations are presented in Table 1 .

(insert table 1 here)

According to previous research , the variance of health care-related variables might be influenced not only by patients' individual characteristics or their own experience but also by regional attributes (Robone et al., 2011; Pérez-Romero et al., 2017; Valentine & Bonsel, 2016) . Some characteristics of regional health systems are under the direct influence of policy makers and managers, and thus constitute potential policy levers. In the highly decentralised Spanish NHS, the financing and management of the health system is controlled directly by regional governments, and therefore it is highly likely that individuals in the same region will report a more similar degree of satisfaction than individuals living in a different region. Accordingly, our analysis must take into account the fact that individuals are clustered hierarchically within regions. In view of these considerations, random intercepts are included to allow mean values to differ across regions. Two levels were analysed: individuals, as level 1, and region-year combinations, as level 2. On this basis, we consider the following equation:

Let , denote the reported health satisfaction with the Spanish public health system or with respect to the primary, specialist and hospital care received by an individual i living in region j. 0 is the overall intercept coefficient. X includes a set of individual variables (level 1) and Z reflects the regional characteristics (level 2).

is the random error at the individual level. The residuals, 2 and 2 , are assumed to have a normal distribution with zero mean and a variance of one. The STATA 15

(StataCorp, 2017) command mixed was used to perform the econometric analysis. The marginal effects of the explanatory variables are estimated via maximum likelihood.

Various robustness tests are carried out in this study. The multilevel regressions detailed in Table 3 illustrate the lag assumed in public expenditure and resources to allow for the possibility of noncontemporary effects of these variables on health care-related outcomes. Furthermore, since the estimations based on overall health services are obtained using a very long time series dataset (2002) (2003) (2004) (2005) (2006) (2007) (2008) (2009) (2010) (2011) (2012) (2013) (2014) (2015) (2016) , we provide estimations based on first differences (see Table 4 ), which is an efficient means of dealing with the problems of omitted variables and of spurious correlations, and of addressing regional variations in quality over time. Lastly, in order to test whether any of the regions was driving the results, leaving-one-out tests were performed, by deleting in turn the observations for each of the Spanish regions included. Table 2 presents the linear multilevel estimations obtained for overall satisfaction with the Spanish NHS. Model 0 represents the empty model, and shows the extent to which the data on satisfaction with the Spanish NHS are nested. The intraclass correlation 6 (ICC) for level 2 (region-year) is 0.0577, implying that there is a 5.77% of variance between groups. Accordingly, the total variance for the dependent variable is explained not only by the variations among individuals but also by those among regions.

covariates, including health spending and other region-specific socioeconomic characteristics. These models show that female sex, higher-education qualifications and employed status are all negatively associated with the perceived quality of health services. Our detection of a negative gradient for the relationship between education background and health system satisfaction corroborates previous research in the field (e.g. Park et al., 2016) , which suggested that individuals with higher education qualifications have greater expectations of public health services. In contrast, in line with previous studies, age is found to be positively associated with health care quality. This finding may be explained by the fact that older people in Spain have had access to universal tax-funded healthcare since 1986, and they seem to value this provision 7 . Interestingly, low-frequency users (one or two visits per year) of public health services are more satisfied with the Spanish NHS than are non-users.

Our results show there are statistically significant differences among individuals according to their area of residence, with individuals from rural areas reporting a higher level of satisfaction than those living in urban ones. This finding might be explained by the fact that patients in rural areas are assigned a higher priority in waiting lists for specialist attention (Abásolo et al., 2014) .

A significant positive relationship was recorded between the level of regional health expenditure and patients' satisfaction with the Spanish NHS. Specifically, an increase of 10% in regional public health With respect to PHI, persons living in regions with a larger per capita expenditure on PHI are less satisfied with the Spanish NHS than those living where this expenditure is less, even after controlling for various levels of public health resources (in Model 5). This might be explained by the fact that those who opt out of public services tend to be generally less satisfied with publicly funded healthcare (e.g. see Costa-Font and García (2003)). However, as suggested by Robone et al. (2011) , choice and competition may also play an important role in explaining the higher level of responsiveness associated with private health care.

The level of satisfaction with the Spanish NHS in low-income regions is significantly lower than in richer regions, even after adjusting for other regional characteristics, such as aging, private healthcare expenditure and public health resources. According to the results obtained from model 5, persons living in low-income regions are likely to perceive 0.26 points lower health system quality than those in higher-income regions.

The Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) were calculated to compare the goodness-of-the-fit 8 of each model considered. According to these test results and the ICC values obtained, model 5 (which includes all regional characteristics) performs best. Regarding the sensitivity analysis, the results obtained from the first-differences models are generally in line with those of the baseline multilevel results (see Tables 4 ). However, with respect to private expenditure, although still negative and substantial in magnitude, the power of the estimations for the firstdifferences model is slightly reduced, especially for the estimations including other public healthrelated resources, probably due to the more limited time span corresponding to these variables (see Table 1 ). Finally, for our baseline model, the multilevel estimations, there seems to be a considerable non-contemporary effect of public resources (according to the AIC-BIC analyses, the model in which two lags are included performs best; see Table 3 ). Finally, as an alternative sensitivity analysis, we performed leaving-one-out tests in which we estimate all six models, deleting in turn the observations for each of the 17 regions considered, to address the possibility that one of the regions in particular may be driving the results. From these findings, we conclude that in general the effect of public expenditure is substantial across all regions, regardless of their income level (results of this sensitivity analysis not reported for brevity here but available upon request from authors).

(insert table 2 here) with public health services, by region and year (ICC), taking into account regional variables, ranges from 2.05% for primary care, 2.24% for specialist services, 3.57% for hospital services and 3.34% for emergency services in the empty model.

The associations between each of these variables and satisfaction with all public health services are mostly similar to those for overall satisfaction with the public health system. The estimations obtained for specific health services also include self-assessed health status 9 (SAH). In this respect, our analysis shows that persons with a lower self-reported health status report greater dissatisfaction with the quality of the services provided by the Spanish NHS, all else being equal. This result shows a pattern of reporting bias in terms of health status which is in line with Fiorentini et al. (2015) for health system responsiveness.

The influence of regional variables on indicators of quality varies according to the health service considered. In this respect, the impact of public expenditure remains positive and is of considerable magnitude for primary health care. Although patients who live in poorer regions appear to be far less satisfied with public health services (in all cases), this effect only persists for primary care once we control for public health resources. As in the case of general services, the effect of public health resources is substantial and highly significant for all health services. However, for emergency care, spending has a weaker impact, but a larger (and positive) association is found with the patient-nurse ratio than that obtained for general health services. In this line, too, Kotzian (2009) argues that the lower the doctor-patient ratio, the greater the degree of satisfaction with the health system, since staff shortages can seriously impact on the quality of the service and ultimately on health-related outcomes.

In this respect, Jofre-Bonet (200) and Fernández and Sánchez (2020), among others, have suggested that the time spent waiting for health care attention is one of the most important responsiveness domains related to patients' satisfaction with the public health care system. Similarly, Irving et al.

(2017) recorded significant associations between national health care spending, the duration of consultations and the burnout that may be suffered by medical personnel. These authors argue that shorter consultations in primary care due to budget constraints are prejudicial to patients' health and to physicians' workloads and mental health.

Interestingly, while PHI per capita is negatively associated with satisfaction, for all services, the magnitude of this effect is only large and statistically significant for emergency services. Lastly, for hospital care, the ratio of public beds (per 1,000 inhabitants) is negatively associated with health system satisfaction. This finding is in line with Xesfingi and Vozikis (2016), and may reflect a problem of over-supply. The latter authors argue that the number of hospital beds is decreasing across Europe as a result of less invasive surgical procedures and more effective drugs, both of which reduce the length of hospital stays. However, as concerns Spain, this question requires further research. It could also be the case that despite increases in the number of hospital beds, levels of bed occupancy remain high. In fact, in a study conducted in the UK, lowering levels of bed occupancy below 90% was found to be positively associated with better hospital performance and with lower rates of mortality (Boden et al., 2016) .

(insert table 5 here)

This study explores the determinants of an increasingly employed patient-reported dimension of quality of care, as measured by satisfaction with health care and drawing on micro-data provided by the Spanish Health Barometer (SHB) together with macro-data related to regional characteristics.

We provide novel evidence on the role of regional factors in shaping the quality of a health system (proxied by health system satisfaction) drawing special attention to the effects of relevant supply-side factors which can be considered important policy levers and have been insufficiently addressed in previous research. According to our results, the most important drivers of satisfaction at an aggregate level seem to be the level of public resources available and, in particular, staffing levels in the health system (positively) and the amount of private spending on health care (negatively). Therefore, we tentatively suggest that policymakers seeking to enhance health system satisfaction may require higher spending levels in health care, most notably in the form of clinical staff. Indeed, the health sector already had insufficient human resources in many high and low-income countries even before the COVID-19 crisis, a shortcoming that has become even more evident today (ILOSTAT, 2020). Our results also indicate that a growing importance of the private health sector within a universal NHS may be a revealing indicator of inefficiencies in the public health system and/or the existence of features of private insurance which are deemed important by patients, such as shorter waiting lists or greater choice.

In addition, we find evidence of a considerable non-contemporary effect for some of the main policy levers, including expenditure in health care, which should be taken into consideration when analysing the impact of budgetary cuts (or increases) in health system satisfaction. Finally, our results suggest that a sector-specific analysis such as the one we present may detect important relationships among variables which a more aggregated analysis might not, like the role of specific sector-level supply characteristics.

The results of this study offer interesting and novel insights into the key drivers of a core dimension of healthcare quality which may be particularly relevant for tax-funded health systems heavily dependent on the economic cycle, especially those more willing to implement pro-cyclical fiscal policies as a response to economic downturns such as the one we examine (see e.g. Grigorakis et al., 2018) .

Our findings highlight that any worsening of the quality of public health care should be of great concern to policy makers since this could impel wealthier individuals towards the private sector, thus undermining one of the main pillars of social cohesion in the modern welfare state and possibly exacerbating health-related disparities (Costa-Font & García, 2003) . This consideration is of particular interest in view of the fact that health systems in many countries must address a growing public-sector deficit, respond to increasing pressures on the health care system (due to COVID-19) and coexist with a considerable increase in the take-up of private health care insurance.

Some limitations of this study should be mentioned. Firstly, since vignettes are not included in the SHB questionnaires, we cannot correct for possible reporting bias in the self-reported levels of satisfaction (Angelopoulou et al., 1998; Jones et al., 2012) with the NHS. However, as noted in our introduction, previous studies have corroborated the use of self-reported measures of perceived quality as credible indicators of how patients are treated by health care systems. Proxy measures for private healthcare were used in our estimations since no data were available on out-of-pocket spending in this respect at the regional level for the period under study. Moreover, due to the nature of the SBH survey, data for specific health services are only available since 2010 and so the time span covered is relatively short. Another significant consideration is that some public-sector workers in Spain can opt out of the public health system (Epstein & Jiménez-Rubio, 2019) , and so the amount of PHI obtained, in each of the regions considered, may be influenced by the number of public servants employed in each case.

As useful areas for future research, studies could be undertaken to explore in more detail the relationship between satisfaction and essential aspects of private healthcare such as waiting lists and J o u r n a l P r e -p r o o f choice. In addition, alternative supply side factors of satisfaction with the health services, such as the type of health provider could be examined in more depth.

In short, studies such as the present one may help policymakers and managers design and implement evidence-informed policy regarding key dimensions of health service quality which complements and enriches more traditional measures of health system performance and which may ultimately benefit health outcomes throughout the population.

Valentine, N. B., & Bonsel, G. J. (2016) . Exploring models for the roles of health systems' responsiveness and social determinants in explaining universal health coverage and health outcomes. Global Health Action, 9(1) Table 3 Multilevel estimations for satisfaction with the SNHS with lagged public expenditure and resources.

Lag of public health care resources 

Equity in specialist waiting times by socioeconomic groups: Evidence from Spain

Private and public medicine: a comparison of quality perceptions

Examining the role of patient experience surveys in measuring health care quality

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Lowering levels of bed occupancy is associated with decreased inhospital mortality and improved performance on the 4-hour target in a UK District General Hospital

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What does the decision to opt for private health insurance reveal about public provision?

Improving people's self-reported experience with the health services: The role of non-clinical factors

Are bad health and pain making us grumpy? An empirical evaluation of reporting heterogeneity in rating health system responsiveness

How do hospital-specialty characteristics influence health system responsiveness? An empirical evaluation of in-patient care in the Italian region of

Cuts drive health system reforms in Spain

Spanish health care cuts: Penny wise and pound foolish? Health Policy

Multilevel models with multivariate mixed response types

Macroeconomic and financing determinants of out of pocket payments in health care: Evidence from selected OECD countries

Understanding and measuring quality of care: Dealing with complexity

Patient satisfaction revisited: a multilevel approach

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International variations in primary care physician consultation time: a systematic review of 67 countries

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Population coverage for health care

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Social protection for happiness? The impact of social pension reform on subjective well-being of the Korean elderly

Public satisfaction with the healthcare system performance in South Korea: Universal healthcare system

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Relevancia del contexto socioeconómico y sanitario en la satisfacción del paciente

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StataCorp. 2017. Stata Statistical Software: Release 15. College Station

Model 0: empty model. M1: Variables at individual level + public spending. M2: M1 + socioeconomic characteristics+ private healthcare + public health resources

Note: Standard errors are shown in parentheses

Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) were calculated to compare the goodness-of-the-fit. A smaller AIC or BIC indicates a better-fitting model

Source: The authors, based on the Spanish National Health Barometer and the Health Ministry Data Base

Results for Individual-level variables not shown for simplicity but available upon request from authors

We are grateful for constructive comments and suggestions by the editor and anonymous referees, as