The impact of publicness on the performance of professional services: Do private sector organizations perform better?

Abstract

This research assesses the impact of the degree of publicness on hospital performance in a specific ’mixed market’ of public health. This market is characterized by patient choice, capitation financing for private hospitals, and funding through ‘soft’ budgets (public authorities partially cover deficits or appropriate profits) for public hospitals. Previous studies on ownership (economic theory), market logic (on choice), and welfare orientation (role of professionals) offer inconclusive results as to the differences of performance among hospitals with different degree of publicness. We contrast statistics related to several dimensions of efficiency and survey data on different aspects of patient satisfaction. Logistic regression models demonstrate that a higher degree of publicness is correlated with a lower degree of perceived quality. However, hospitals with a varying degree of publicness are similarly efficient. These results indicate that divergences of performance differ amongst performance dimensions and the theoretical expectations need to consider differently these dimensions. Comparisons of the performance of hospitals with a varying degree of publicness should consider the broader institutional (i.e. market mix) configuration and the specific constraints of political authority for all hospitals, and not just single organizations. Finally, professionalism may play a role in explaining variations or similarities of performance by levelling out the differences in the degree of publicness.

Keywords

Efficiency perceived quality performance management (PM)publicness

Introduction

The dimensional ‘publicness’ approach (Andrews et al., 2011; Bozeman, 2004; Bozeman and Bretschneider, 1994; Moulton, 2009) in which all organizations are “considered to be more or less public depending on the extent to which they are subject to political authority” (Merritt, 2019: 2) is increasingly used in public management research. Bozeman’s (1987) influential conceptualization that considers the dimensions of ownership, funding and the degree of exposure to government regulation to capture an organization´s degree of publicness has changed over time (Carter, 2016; Merritt, 2019). The degree of publicness, however conceptualized, is suggested to influence organizational performance (Andrews et al., 2011; Johansen and Zhu, 2014). Whether a high or low degree of publicness has a positive or negative effect on organizational performance is subject to academic debate (Merritt, 2019) and the results of empirical contributions are mixed (Bjorvatn, 2018; Garattini and Padula, 2019; Moulton, 2009).

Scholars have studied the relation between publicness and performance in, amongst others, the hospital sector. In this sector, mixed markets with public and private sector hospitals are increasingly common (Rechel et al., 2018; Siciliani et al., 2017), and there is limited consensus on the key performance distinction between public and private clinics (Andersen et al., 2016). Findings on the relation between publicness and hospital performance are difficult to compare because most studies define and operationalize both concepts differently. Whereas some focus on the impact of ownership on efficiency (Andersen and Blegvad, 2006; Bartel and Harrison, 2005; Herrera et al., 2014; Tiemann et al., 2012), others consider the relation between efficiency and cost containment (Bel and Esteve, 2020). A comparative assessment of performance that uses both objective and subjective measures among organizations with different degrees of publicness is missing.

Most empirical studies are conducted in the United States, the United Kingdom and Germany, that belong respectively to the private insurer, the national health service, and the private insurance health model (Böhm et al., 2013). The national health service model (regulated and financed by the public sector) has evolved into ‘mixed markets’ in which public funding is compatible with competition between providers for patients within a purchaser-provider split scheme (Siciliani et al., 2017) and different funding options for ‘money following choice’.

Spain, as a ‘quasi-federal’ system and part of the national health service model (Böhm et al., 2013), has devolved health management powers to regional governments. Each region displays a different blend of the health ’market’ and a diverging way to exert political authority, which shapes the degree of publicness of hospitals as a relevant factor to understand performance (see Bode, 2019). Political authority is exerted through public funding and individual performance contracts ruling the relationships between public authorities and (public and private) hospital managers, auditing, and inspections. The ‘mixed-market’ of the region of Madrid, the empirical focus of this research, has a considerable proportion of out-of-pocket spending in privately owned hospitals compared to other Spanish regions. In Madrid, 44 out of 81 hospitals are private, and they hold 28% of operating beds in the region, the fourth largest proportion in Spain (Ministerio de Sanidad, 2018). Some private hospitals offering partially private praxis are publicly funded too. They provide services to patients who are assigned to their catchment area or choose to attend these hospitals without having to pay for the services. These hospitals are reimbursed through a capitation financing formula, they must display the logos and the corporate image of the Madrid regional health authorities and are part of the public health system. Finally, hybrid hospitals offer a blend of public funding, a higher proportion of outsourced non-clinical services and greater managerial autonomy from political authority to shift resources when needed.

Within the public health system (the focus of this paper), patients may choose any hospital, whether public, private or hybrid. According to the annual Health Barometers from CIS (a governmental research and poll centre),¹ 63% of respondents would go to a public hospital (average from 2006 to 2018); 29.3% to a private one (without incurring additional costs) and 7.7% would go to any of them.

The number of studies on the specific relationship between publicness and performance in Spanish hospitals is limited to some performance areas that do not include perceived quality. Their findings are not conclusive. For example, no significant differences between public and hybrid hospitals were found in terms of safety, efficiency, and clinical effectiveness (Alonso et al., 2015; Comendeiro-Maaløe et al., 2019, 2020; Serra et al., 2017). Franco Miguel et al. (2019), however, observe that hybrid hospitals are more efficient than public hospitals.

Filling the identified gaps in the international and national literature, this research aims to assess the impact of the degree of publicness on hospital performance (in terms of efficiency as objective dimension and perceived quality) in the context of a specific hospital ‘mixed market’ in the region of Madrid.

Performance and organizational publicness

Performance defined

Organizational theorists have predominantly used the ‘goal attainment model’ to assess performance (Etzioni, 1964: 8). In this model, organizational effectiveness “is determined by the degree to which it realizes its goals” (Jung, 2011: 195). Goal refers to the desired outcomes and outputs and performance links to what is realized (Van der Hoek et al., 2018). Public managers aim to institutionalize and standardize the formulation of goals and its evaluation (Lee et al., 2009; Moynihan, 2006), trying to achieve formal specific objectives (Boyne, 2002). Moulton (2009) differentiates between performance as productivity and cost efficiency and public value-related outcomes, which include quality of care and perceived quality in the health sector (Anderson, 2014), as part of the extended goal attainment model (Radin, 2006).

Efficiency, that refers to the different forms of achieving outputs and outcomes with the minimum level of resources (Andrews and Entwistle, 2013), is customarily measured through objective performance indicators. Objectively verifiable performance is, according to Andrews et al. (2006), the ‘gold standard’ of performance management. However, measurement and assessment of performance are ultimately subjective (Brewer and Brewer, 2011) and can complement objective indicators to offer an overall view of organizational performance (Moynihan and Pandey, 2010).

Perceived quality by patients, as a subjective and second performance dimension considered in this study, refers to the strategies applied to satisfy patients, relying on judgmental evaluations on the influence of non-clinical factors like meals, rooms, and kindness in treatment by health staff (Conner-Spady et al., 2004). Subjective measures based on surveys that assess the perceived quality by users have the weaknesses of its reliance on recall and the comprehensive understanding of organizational issues (Amirkhanyan et al., 2014). Anderson et al. (1997) consider that customer satisfaction and operating efficiency are not compatible because any attention to inputs reduction will affect the (subjective) impact on clients. This is relevant in healthcare where a substantive amount of time is required to take care individually of patients (Cheon, 2016). This balance between efficiency and perceived quality is at the core of this research.

It has been suggested that the degree of publicness influences organizational performance (Andrews et al., 2011; Feeney and Welch, 2012; Johansen and Zhu, 2014). A definite answer to the question of the direction and magnitude of its impact is pending given the lack of conclusive empirical evidence and the different underlying theoretical perspectives. Literature clusters around three areas: ownership as a primary and more classical distinction of the public-private continuum, the regulatory environment in which entities with a different degree of publicness operate and are subject to political authority and the welfare orientation of professionals. These approaches will be discussed in turns.

Ownership

Some suggest that private ownership is associated with the adoption of more innovative, and performance-enhancing management practices (Hall et al., 2016). Following property rights theory, public ownership leads to lower efficiency because their managers are not rewarded for managing efficiently. In privately-owned organizations, however, efficiency gains are expected when managers are rewarded, and shareholders receive higher returns. Finally, transaction cost economics proposes that in the presence of asset specificity and measurable services, market mechanisms work better (Hefetz and Warner, 2011). In hospital care, if complex services like psychiatry and geriatrics are not considered, private providers should perform better given that asset specificity and measurability are high.

Private organizations operating in a public sector context are likely to search for economic success, focusing on a type of clients or processes that can be easily ‘manufactured’ (Rauh, 2015). The downside is that private hospitals are associated with cream-skimming (choosing profitable diagnosis-related groups and/or accepting low severity cases) and skimping (providing fewer services) (Bjorvatn, 2018).

Concerning efficiency, the results are not conclusive. Chang et al. (2004), for example, found that public Taiwanese hospitals were less efficient than private ones that do not have intensive-care units, which are a sign of higher complexity organization. However, Rosenau and Linder (2003) established that American public hospitals were more efficient than private ones; a similar result was obtained by Tiemann et al. (2012) for Germany. Bjorvatn (2018) found that private hospitals have lower waiting times and shorter stay for some procedures than public hospitals in Norway.

Meta-analyses do not offer conclusive results either. Eggleston et al. (2008) established that differences among hospitals depend on the institutional context, the influence of the market, the features of the regions, and they may differ over time. Herrera et al. (2014) did not find clear differences as regards efficiency in their meta-analysis of private for-profit, private not-for-profit, and public healthcare providers. The context and how political and economic authorities constrain the performance of hospitals may play a role (Tynkkynen and Vrangbaek, 2018). Finally, a meta-regression analysis (Bel and Esteve, 2020) concludes that studies on Germany, belonging to the social health insurance model dominated by mixed markets, and the United States, characterized by the private health insurance model (Böhm et al., 2013) found that private (including for-profit and not-for-profit) hospitals were more costly and less efficient than the public counterparts.

As regards to perceptions, the literature that focuses on the quality-shading hypothesis (Jensen and Stonecash, 2005) suggests that the perceived quality of services is at stake since private firms are expected to focus on productivity rather than on quality. A review of economic theory by Eggleston et al. (2008) shows that there is no clear-cut prediction of the impact of ownership on perceived quality. There are different arguments for performance comparisons between public and private provision because they depend on the institutional context of political authority and the competitive context. Concerning empirical research, Perotin et al. (2013) did not find statistical differences between public and private-owned hospitals.

Policy environment and market orientation

The degree of organizational publicness depends on their regulatory (Anderson, 2012; Bode, 2019) or policy environment (Miller and Moulton, 2014). This environment reflects the constraints of political authority on different providers. Merritt (2019) adds dimensions associated with a higher degree of publicness when considering the engagement with the public and external stakeholders, the latter also identified by Johnson and Dobni (2016). Governments exercise political authority even when they transfer responsibility to a contractor (Metzger, 2015) or when they use public funds to finance the treatment of patients through private providers.

Competition and choice of quasi-markets frame the regulatory environment. Quasi-markets have surfaced under different guises in healthcare (Hansen and Lindholst, 2016) and are expected to improve health quality if prices are regulated and quality is observable. However, positive, negative and zero effects are expected when the market determines prices (Barros et al., 2016). The health sector becomes a relevant area of study because many countries implement mixed markets.

In these markets, public and private hospitals compete for patients funded by taxes (Rechel et al., 2018; Siciliani et al., 2017) given that public authorities allocate extra resources to cost-efficient providers or to those who attract patients from other health districts (Bode et al., 2017). Financing varies from ‘soft’ budgets (i.e. public authorities partially cover deficits or appropriate profits) for public providers to different ways to fund private hospitals through Diagnosis Related Groups (DGR) with lump-sums or capitation formulas. These markets convey that private hospitals focus on efficiency and public hospitals on equity (Siciliani and Straume, 2019).

However, empirical research does not conclusively prove the higher performance of mixed markets (Levaggi and Levaggi, 2020; Tiemann et al., 2012). The basic idea, though, is that competition should ensure better individual performance. The features of the market depend on the way service providers are funded, their obligation upon universalistic services and the monitoring of the quality of services provided.

Regarding the perceived quality of treatment and facilities, Niskanen (1971) contended that public managers are less likely to prioritize customer satisfaction when their organizations are funded through taxes. However, organizations competing in the market are more likely to try to satisfy their customers (Fornell et al., 1996). Since non-clinical factors are not governed by professional norms, private clinics are expected to offer a higher quality of non-clinical services than public hospitals. In sum, in mixed-market environments with public sector providers funded through taxation and private providers financed by capitation or provided services, public organizations are likely to be less responsive to the demands of their clients (Cheon, 2016).

The welfare orientation

The welfare orientation underscores the ethos of professionals like doctors and nurses, who work with relative autonomy and enjoy “professional protection” (Noordegraaf, 2015: 1). This autonomy and ethos, in theory, make them less vulnerable to managerial decisions that often stress results and efficiency. Professionals are suggested to care for service quality, expertise, and ethical commitment (Noordegraaf, 2015), independent from the organizational context. In that sense, Frezza (2019) advocates that patient-centredness (entailing clinical effectiveness) is a core value of medicine for many physicians. The degree of publicness, then, is expected to be of little influence since doctors will act primarily as professionals and will do what is required to achieve clinical effectiveness even at the cost of efficiency. Professionalism has also implications for perceived quality since the autonomy of professionals make them to behave as ‘knights’, i.e. altruistic and putting the needs and wants of their patients (…) above their own; whereas ‘knavish’ professionals (…) prioritize (rather) their own immediate interests” (Le Grand, 2007: 31). As professionals are likely to enjoy more autonomy in public sector settings, they may organize the service according to their interest in terms of waiting times, surgery scheduled hours and the like. Highly autonomous professionals may care less about patient-perceived quality of professionals’ treatment.

However, the hybridity of the medical profession and their cross-cutting identities with the managerial profession (Ewert, 2020) might cause tension. The crowding-out effect of the business-like management approach might have an impact when organizations tilt towards valuing more economic issues (Bode, 2019). The hybridisation of the managerial arrangements depends on the impact of the national context on the competition of the business-like logic and medical professionalism (Bode and Dent, 2014). As a result, doctors may prefer economic issues over medical ones (Caronna, 2011) or vice versa (Bode, 2019) and these preferences will likely impact on perceived quality and efficiency.

According to empiric research, health professionals behave following the welfare orientation providing treatment to patients regardless of their economic implications in the mixed hospital care market in Germany (Bode et al., 2017). Qualitative work shows that the public service setting may favour the efficiency logic, but healthcare professionals cannot neglect the publicness of their organizations when abiding by their professional ethos (Bode, 2019). In this regard, any performance gain attributed to the economic efficiency argument might be balanced by a publicness motivational ethos in which this industry’s effectiveness might be sidestepped.

The previous discussion leads to formulating the hypotheses and subhypotheses to better understand the impact of the degree of publicness of hospitals on performance. Concerning efficiency, both theoretical approaches and the review of empirical research on ownership, regulation, and the welfare orientation are inconclusive. They, however, tend to emphasize a higher efficiency for hospitals with a lower degree of publicness. Therefore, the hypothesis reads as follows.

H1 The lower the degree of publicness, the higher the hospital efficiency

The subhypotheses allow for a more nuanced argumentation. Following the logic of the medical profession reasoning, efficiency arguments will be sidestepped if the welfare of patients is compromised. Therefore, private and public practitioners are likely to be impervious to managerial efficiency (regarding hospital stay, for instance) when issuing patient discharge decisions after surgery. Hence:

H1a: The degree of publicness does not influence the length of hospital stay after surgery

However, cost differences (i.e. use of generic prescriptions versus brand name drugs, which represent a considerable cost of hospital expenditure) without clear bearing on the clinical wellbeing of patients are likely to trigger different behaviours. Arguments derived from ownership and transaction cost theory suggest lower incentives for public servants to behave efficiently if other concerns are not considered. Hence:

H1b: The higher the degree of publicness, the higher the costs of prescriptions

Finally, there are trade-offs between efficiency and perceived quality in connection to patient ‘loyalty’ following the market logic. Panda et al. (2018), for instance, discovered in a meta-evaluation that a potential argument, among others, for the increasing use of caesarean sections vs natural births refers to the bond between the obstetrician and the patient. The possibility of organizing the birth might encourage the increase of caesarean sections, especially in private sector hospitals where ‘loyalty’ from patients may play a role in a market environment. Hence:

H1c: The lower the degree of publicness, the higher the number of low-risk caesarean sections

Performance as perceived quality refers to non-clinical aspects of the relationship between medical staff and patients. The previous discussion around ownership, blend of mixed health markets, and the welfare logic does not lead to a conclusive overall expectation. Theoretical arguments on ownership and empirically related research state that the degree of publicness does not affect perceived quality. In mixed markets, hospitals with a lower degree of publicness financed through patient choice will likely rely on enhancing the overall patient experience at their premises. We take this as the dominant logic for the overall hypothesis because following Bode (2019), the regulatory environment influences how other economic and profession-related explanations impact on hospital performance. Hence:

H2: The lower the degree of publicness, the higher the overall satisfaction of patients with non-clinical services

This overall hypothesis does not necessarily need to display homogeneous behaviour in the different components of perceived satisfaction. Following the market logic, satisfaction with infrastructure (i.e. the room), without any bearing on clinical effectiveness, is likely to be used by private hospitals as a competitive advantage. Hence:

H2a: The lower the degree of publicness, the higher the satisfaction of patients with the quality of the hospital infrastructure.

However, when clinical elements are at stake in the health staff-patient relationship, the welfare logic is expected to dominate over economic and market-related considerations. Clinical professionals from any sector are likely to show similar treatment to patients. Hence:

H2b: The degree of publicness does not influence the treatment of pain

H2c: The degree of publicness does not influence satisfaction with treatment by clinical staff

Research strategy: Case selection and methods

In Spain, the governance of the universal health system has been transferred to fully autonomous regional authorities. As part of the national health model (Böhm et al., 2013), the public sector provides and funds hospital care, operated by public officials.

The Madrid regional authority has increasingly used private sector providers for clinical and non-clinical services and adopted the international managerialist credo (see, for example, Ferlie et al., 2016; Veillard et al., 2005). Common to other European systems (Tynkkynen and Vrangbæk, 2018), hospital care is provided by hospitals with varied degree of publicness (public, private and hybrid) generating a ‘mixed market’ model found elsewhere (Barlow et al., 2013). Patients are free to choose the healthcare centre (whether publicly or privately owned) without making payments. All hospitals are within a 70-minute ride by public transport from the centre of Madrid. Free choice by patients has financial consequences only for privately owned hospitals that are financed on a capitation basis in a system of ‘fixed’ prices: the balance of patients coming in from other areas and patients going out of an area for hospital treatment matters financially. All hospitals must display the same corporate image (logos and stationery), regardless of whether they are publicly or privately owned. Privately owned hospitals cannot carry out individual marketing campaigns to attract patients.

Finally, since 2013, the regional authority has published comparative performance data on a website without ranking hospitals, although citizens can identify good from bad performers. Better performance results do not influence resource allocation for publicly owned hospitals, but they are the basis for assessing performance against a service level agreement between the hospital and the authorities. As in other countries, a ‘cadre’ of managerial hybrids head up hospitals (McGivern et al., 2015).

Features of the selected hospitals

To study the impact of publicness of performance, we compare performance data of 34 public, hybrid, and private hospitals– the entire healthcare universe of the public system. A differentiated degree of publicness is based on the amount of political and economic authority that a hospital is exposed to (Carter, 2016). Public hospitals are those with the highest degree of publicness. The ownership is public, and they are financed with public money; they do not enjoy either financial nor managerial autonomy and are staffed with health care workers with civil service status.

Hybrid hospitals are publicly owned but have distinct features. A group of hybrid hospitals emerged under different juridical forms like state commercial enterprise, a public-private partnership for non-clinical services (such as cleaning, patient transport, and catering), an entity of public law and foundations. They were endowed in 2005 with some managerial and financial autonomy from political authority. Instead of relying on civil servants, health care professionals are subject to public law contracts. In the case of public-private partnerships, private investments on long-term infrastructure are earned back through an agreed-upon quota established in the contract. All hybrid hospitals experienced a process of corporatization which gives managers complete control over all inputs and issues related to the production of services (Busse et al., 2002) and have a non-negligible capacity to influence perceived quality since they enjoy greater managerial and financial power to deal with dimensions that affect the perceived quality (for instance, the information provided or room facilities).

Finally, the category private, with the lowest degree of publicness, includes private for-profit hospitals that provide public clinical and non-clinical services. Medical staff are contracted under private law and patients from the public health system do not pay fees. The hospitals are funded through a capitation formula explained above. All hospitals are subject to public control through inspections, audits, regulations, sanctions, and a performance contract.

Data, variables, and analysis

Several authors have provided a universal framework for analysis that includes reliable indicators in health (Copnell et al., 2009; Veillard et al., 2005). Although some indicators used in this article are the topic of continuous debate, there is a shared understanding of what indicators need to be considered when evaluating hospital care performance (Groene et al., 2008). We contrast the dimensions of efficiency and patient-perceived quality as objective and subjective variables.

The selection of dimension to account for perceived quality and efficiency for this article considers the available empirical data and the use of similar dimensions in international studies on hospital care performance (Veillard et al., 2005). These dimensions were the most common in the projects on hospital performance assessment reviewed by Groene et al. (2008: 165–166). For efficiency, (see the detail in Appendix 1), we grouped the indicators as follows: H1a on hospital stay (avoidable hospitalization, long stays after a stroke or hip fracture and cholecystectomies) H1b (cost per prescription), and H1c (number of low-risk caesarean section). For perceived quality, specifically measured by the satisfaction of patients with hospital facilities and treatment by professionals, the breakout of indicators is as follows: H2 on overall satisfaction (global satisfaction with the care received in the hospital, the number of complaints per 10,000 services and the percentage of patients who would recommend the hospital they stayed in), H2a (satisfaction with the treatment of pain), H2b (satisfaction with the room they stayed in during hospitalization) and H2c (satisfaction with the treatment by doctors, nurses, and with the information received).

The data used in this study were published by the health authorities² for the years 2014, 2015 and 2016. All 34 hospitals of the regional health care system are included and together they result in potentially 102 observations when the three years are combined. Each dependent variable has been converted into a dummy variable: high performance (coded as 1) vs. medium/low performance (coded as 0). Data related to the independent variables are derived from annual hospital activity reports. The key explanatory variable is the degree of publicness with three categories (0 = public, 1 = hybrid, 2 = private). Additional control variables are considered: Organizational age, degree of complexity, and location (see Table 1).

Table 1.

Descriptive statistics of the public, private and hybrid hospitals.

	Public	Hybrid	Private
Complexity
High	33.3%	10%	16.7%
Medium	33.3%	40%	50%
Low	5.6%	40%	16.7%
Other	27.8%	10%	0
Total	100%	100%	100%
Located in Madrid (the capital)	55.6%	20%	33.3%
Age (mean) in years	92.1	17.8	20.5
Total	18	10	6

First, the degree of complexity is coded in four categories 0 = low, 1 = high, 2 = medium, 3 = others, and for some analysis the category ‘others’ is suppressed. The performance of hospitals is expected to covariate with the complexity of services provided (Özcan, 1992, 2008), although with different impact on efficiency. Carr and Feldstein (1967) found lower efficiency following a U-curve pattern since marginal costs tend to decline when size increases but rise again with large size. We use the definition of complexity offered by the regional authority Web site.³ The complexity of a hospital is determined by the following factors: its activity, number of beds, technological equipment, human resources, treated cases, and service mix.

A second control variable is the location of the hospital (0 = Madrid capital, 1 = outside of the capital), to capture the real possibility of choice (Le Grand, 2007). The number of service providers is expected to be higher in densely versus less populated areas. It is expected that there are more opportunities for more market competition and better performance in densely populated areas with higher pressure on the service (Cooper et al., 2011).

Third, organizational age (years since the opening of the hospital and age squared to capture its potential non-linear effect) as a control variable is also used in comparative studies on organizational performance (Lawrence, 1988). Although seniority seems favourable in terms of organizational learning and survival in the private sector (Calantone et al., 2002), a negative impact is assumed on performance as older organizations are likely to have an older workforce and a more bureaucratic organizational culture in the public sector (Boyne and Walker, 2010: 185). Finally, a year dummy is included as part of the statistical specifications of the model.

For the analysis, we run multinomial logistic regressions (MLR) (Long and Freese, 2001), that include all the independent variables to assess the effect of publicness on performance.⁴ MLRs report the signs and statistical significance of the effects of each independent variable on each dependent variable, with different indicators for perceived quality and efficiency. As the dependent variables are binary, the magnitudes of the estimated coefficients do not report the relative strength of the effects of each independent variable. This is remedied through Average Marginal Effects (AMEs), calculated after the multinomial regression models, that work out the probability of experiencing higher perceived quality, and efficiency. The AMEs are calculated as follows: for each observation of the dataset, they first estimate the marginal effect of a given variable (holding all other independent variables constant) on our dependent variable (e.g. global satisfaction), and then they average the marginal effects for all the observations calculated in the previous step. Intuitively, the AMEs compare the probability of, following the example, being globally satisfied between two populations that only differ in one trait (i.e. being public or private), but share all the remaining characteristics (Williams, 2012). We display the results of AMEs in graphic format (see Figures 1 to 5). For the interpretation of the figures, we have to bear in mind that each horizontal line represents an independent variable of the model, the point standing for the best estimation of its effect upon the dependent variable, and the line, for its 95% confidence interval. If a confidence interval crosses the vertical line drawn at the origin (zero) of the horizontal axis (representing the absence of effects), the effect of the variable is not statistically significant. If it does not and is located to its right, the effect is positive and statistically significant, whereas if it is located to its left, the effect is negative and statistically significant (see Winter, 2014 for more details regarding the figures).

Findings

The different models of Figure 1 indicate that hybrid and private hospitals are less efficient than public hospitals in two out of four indicators related to the subhypothesis H1a (stay in hospital after intervention): in hip replacement +20 days of hospitalization (private hospitals are 34% less likely to be efficient than public hospitals), and cholecystectomy (private and hybrid hospitals are 21% and 35% less likely to be efficient than public hospitals, respectively).

Figure 1.

Average marginal effects, efficiency (H1a).^a

Differences in the likelihood of either public or private hospitals being more efficient are almost non-existent as regards to the subhypothesis H1b (cost per prescription paid by the hospital) since private hospitals are likely to be 0.4% less efficient than public hospitals (see Figure 2) and hybrid hospitals are 29% less likely to be efficient in this variable than public hospitals. Also (Figure 2), hybrid and private hospitals are less efficient than public ones since they perform more low-risk caesarean sections (56% and 86% respectively).

Figure 2.

Average marginal effects, efficiency (H1b – left panel and H1c – right panel).^a

Hence, as regards to efficiency, and including all control variables in the logistic models, both hybrid and private hospitals perform a bit worse than public hospitals in variables such as amount per prescription, low hip +20 and low-risk caesarean sections (see Table 2). Hybrid and private hospitals are similarly efficient (some of the variables are not statistically significant).

Table 2.

Reported values of AMEs for the grade of publicness, efficiency.^a

Efficiency	Hybrid	Private
H1a:
Low avoidable hospitalization	0.06 (n/s)	0.16 (n/s)
Low stroke +20	–0.17 (n/s)	0.08 (n/s)
Low hip +20	–0.16 (n/s)	–0.34*
High cholecystectomy	–0.35*	–0.21*
H1b:
Low amount per prescription	–0.29*	–0.004 (n/s)
H1c:
Low risk caesarean sections	0.56*	0.86*

^aNote: * Statistically significant; (n/s) statistically not significant.

Source: own calculations from the data of the Observatory of the Madrid Health Service

When controlling by complexity, highly complex hospitals are more efficient. The effects of location and age, however, depend on the indicator. The data suggest that a) the degree of publicness is linked to different dimensions of efficiency but with different results; b) in half of the processes we considered private hospitals are significatively less efficient than public hospitals; in the other half, results are not statistically significant (confirming partially subhypothesis 1a); c) concerning the cost of prescriptions there are no significant differences between private and public hospitals, different to what we expected (the subhypothesis b cannot be verified) and d) the lower the degree of publicness, the higher the number of low-risk caesarean sections, which confirms subhypothesis 1c.

Figures 3 to 5 show the AMEs of each independent variable for the indicators of perceived quality that correspond to the general hypothesis 2 and the subhypotheses 2a to 2c. The breakout in different subhypotheses shows the following results. At a significant statistical level, the overall satisfaction of patients with hospital services (as predicted by hypothesis 2) decreases with a higher level of publicness, except for complaints from patients where hybrid hospitals display better performance than private hospitals. Patients from private hospitals are 80% more likely to be satisfied than patients from public hospitals and are 74% more likely to recommend the hospital to someone (these percentages are lower for the cases of patients from hybrid hospitals but are as well positive and statistically significant – see Table 3). The same can be said of H2a (higher satisfaction with the room in private and hybrid hospitals than in public hospitals displaying 89% and 56% of more likely satisfaction) (see the percentages of AMEs in Table 3). Unlike we expected, the degree of publicness seems to influence satisfaction with pain treatment and this improves with the degree of privateness (we reject therefore hypothesis 2 b). Furthermore, concerning the satisfaction of patients with the treatment of health staff and the information they provide, hypothesis 2c is rejected but only partially. Only private sector hospital patients (not the ones from the hybrid models) display higher satisfaction than public hospital patients with the treatment of doctors and nurses (except for the kindness of nurses, whose results are not statistically significant).

Figure 3.

Average marginal effects, quality (H2 general).^a

Figure 4.

Average marginal effects, quality (H2a – right panel and H2b – left panel).^a

Figure 5.

Average marginal effects, quality (H2c).^a

Table 3.

Reported values of AMEs for the grade of publicness, perceived quality.^a

Perceived quality	Hybrid	Private
H2 general:
Global satisfaction	0.23*	0.80*
Low complaints from patients	–0.49*	–017*
Recommendation to other patients	0.22*	0.74*
H2a:
Satisfaction with pain treatment	0.33*	0.42*
H2b:
Satisfaction with room	0.56*	0.89*
H2c:
Satisfaction with information	–0.05 (n/s)	0.43*
Positive treatment from doctors	0.08 (n/s)	0.46*
Positive nursing treatment	0.39*	0.41*
Positive nursing kindness	0.25 (n/s)	0.23 (n/s)

^aNote: * Statistically significant; (n/s) statistically not significant.

Source: own calculations from the data of the Observatory of the Madrid Health Service.

In general, the likelihood of positively evaluating any variable is higher in private than in hybrid hospitals and in these hospitals than in public hospitals.

The differences between the gross and net effect of publicness are explained by certain characteristics. High complexity has a negative effect on perceived quality and in older organizations patients are more satisfied. The effect of location is ambiguous and differs per variable. The fact that public hospitals tend to have higher complexity explains their worse performance compared to hybrid and private hospitals. However, as public hospitals also tend to be older, this disadvantage of higher complexity is partially compensated for by the better performance of older hospitals.

This research has at least two methodological shortcomings. A first limitation derives from the absence of a relevant indicator on the integration of services to respond to patients’ needs as advocated by Nuti et al. (2018). This indicator would give a relevant account of the performance differences, provided that private hospitals, devoted to the production function, are likely to be less eager to foster integration. A second limitation refers to the generalization of the results. Our selected hospitals constitute the whole universe and our analysis is restricted to this context that displays a particular ‘market mix’. Similar mixes are expected to show these results.

Discussion of results

The central aim of this article is to assess the impact of organizational publicness on hospital performance. Perceived quality by patients is higher in private and hybrid hospitals than in public hospitals concerning almost all variables, therefore we confirm the hypotheses related to overall patient satisfaction and satisfaction with the hospital infrastructure. However, we reject the subhypotheses linked to the treatment of pain and the treatment by health professionals. This, overall, might be explained by the funding schemes of private hospitals that depend on retaining their patients and attracting patients from other catchment areas. Given that private hospitals cannot marketize their services, service satisfaction and word of mouth may have an impact on these results. However, better-perceived quality in hybrid hospitals, whose financing formula is the same as public hospitals, cannot be explained similarly, but rather through the young age of this type of hospitals that might have affected this variable positively and has created virtuous practices in expectations/satisfaction management. These results disconfirm the quality-shading hypothesis (Jensen and Stonecash, 2005) by which private firms are expected to focus on productivity rather than on quality, and this is probably the effect of mixed-markets with considerable constraint from the political authority on the search for economic benefits. The results are not in line with the findings of Perotin et al. (2013) who did not find statistical differences between public and private-owned hospitals in reported quality levels. Also, the theoretical prediction that health care doctors (regardless whether they work in private or public hospitals) put perceived quality as a core value does not seem to hold as prescribed by Frezza (2019), at least as regards to public sector doctors. Perceived quality does not seem to be a fundamental part of the professional credo, and the professional autonomy in public sector hospitals is likely to make doctors care less for patient satisfaction (Le Grand, 2007).

The picture of efficiency is mixed. We could not find information for an index or overall index of efficiency as for perceived quality and the efficiency hypothesis was broken down into the dimensions related to avoidable hospitalization, the cost of prescriptions and caesarean sections. Public hospitals are significantly more efficient in avoidable hospitalization than private hospitals in two dimensions but only in one compared to hybrid hospitals There are no statistical differences as regards to the cost of prescriptions. These results are in line with the findings on technical efficiency of other scholars (Herr, 2008 for 1500 German Hospitals) using Stochastic Frontier Analysis, and Alonso et al. (2015), and Chang et al. (2004) employing bootstrapped Data Envelopment Model.

Public hospitals produce significatively fewer caesarean sections. A higher number of these sections in private hospitals might be related to the special bond between obstetricians and mothers as suggested by Panda et al. (2018) that fosters the pre-programming of caesareans so that the same doctor can deliver the birth.

The slight differences in efficiency between hospitals with different degree of publicness seem to suggest that the impact of ownership on this performance dimension does not offer conclusive results like suggested by the meta-analysis of Herrera et al. (2014), or they are tilted towards the public sector as in the meta-evaluation of Bel and Esteve (2020). In any case, the prediction of economic theory that private undertakings are more efficient (Hall et al., 2016; Hefetz and Warner, 2011; Rauh, 2015) seems to be disproven once more. As suggested by Borcherding et al. (1984), these results in efficiency might be caused by the particular arrangements of a ’mixed market’. When competition has no regulatory advantage for public sector providers, as in the region of Madrid, this does not entail significant differences in efficiency because only private hospitals compete for patients.

An alternative interpretation of the differences in efficiency might be related to hospital complexity. Private and hybrid hospitals under analysis belong to the category medium-low complexity while many public sector hospitals in the Madrid universe are of high complexity. In our analysis, higher organizational complexity entails lower performance for all both performance dimensions and most variables. Higher complexity entails, amongst other size-related features, the delivery of a more complex service mix and the treatment of more complicated patients. Therefore, a more efficient private sector hospital might be related to ‘mass-production’ surgery and treatment while complex cases, that require longer hospitalization and more expensive drug treatment, are left to public hospitals. This interpretation is in line with the research of Chang et al. (2004), who found that private hospitals without intensive-care units (i.e. medium or lower complexity according to this research) outperform public hospitals.

On the theoretical contribution, this study shows that several dimensions should be pondered to judge organizational performance (Andrews et al., 2011). Objective and subjective measures might offer contrasting views to have a fuller picture. Furthermore, unlike the theory that focuses on the impact of publicness on performance based on the economic logic, this paper suggests that the trade-offs among different performance dimensions and the impact of publicness on performance might be related to the regulatory environment and the specific constraint of public authority overall (Tynkkynen and Vrangbæk, 2018) and less to the degree of publicness of particular organizations. The policy environment may impact also the role of professionals. Agreeing with Bode and Dent (2014), health care professionals may react differently to different mixes of tensions derived from microeconomic steering and clinical leadership taking place in public and private hospitals alike. Therefore, a comparison of performance between private and public sector hospitals at the international level needs to consider the “structural impact of regulatory hybridization” (Bode et al., 2017: 503). Professionals seem to pay less importance to perceived quality in public hospitals preserving then their autonomy in a ‘knavish’ way (Le Grand, 2007) and private sector professionals offset the economic logic attached to efficiency by paying attention to clinical effectiveness and having similar results in this area than public hospital doctors. To expand the validity of these results, a meta-evaluation of hospital performance needs to consider the specific elements of the constraints exerted by the political authority and what is the relevant features of the ‘mixed-markets’ at play.

Conclusions

At a broad level, public hospitals are more efficient than private hospitals in some dimensions (in others, no significant differences) and the latter have more satisfied patients. In a closer look, each variable has a more nuanced behaviour.

The limited differences in efficiency and higher perceived quality when privateness of hospitals increases might be related to how the regulatory environment plays the market and the welfare orientation against each other in line with the suggestions by the literature. All chosen performance indicators to assess efficiency, but one, are closely linked to the clinical effectiveness of the treatment that aims at curing and avoiding recurring hospitalization or reducing stay in hospital after surgery. Here, the welfare orientation of the medical profession is at stake. In the welfare logic, health professionals treat patients without taking consideration economic implications and the market logic (Bode, Lange and Marker, 2017) or as nicely put by Andersen and Jakobsen (2011: 956) “ownership matters for highly professionalized services, but professionalism neutralizes some – but not all – ownership differences”.

For perceived quality, choice and competition are key provided that they are rewarded. The mixed market analysed only rewards private hospitals, hence no wonder that public hospitals are less inclined to attract patients, and this is not offset by a similar professional ethos of doctors in all types of hospitals. The market logic dominates over the welfare approach.

Footnotes

Acknowledgements

We are grateful to Jacobo Muñoz for his help in the early drafts of this manuscript. We also thank the anonymous reviewers for their professional work in guiding our research output.

Authors' note

José Rama is now affiliated with Department of Social Sciences, Universidad Carlos III de Madrid, Spain.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research has been funded by the Spanish Ministry of Science and Innovation thanks to grant CSO2016-77493-P – ‘Public values, professionals and public-private partnerships in the area of health’.

ORCID iD

Salvador Parrado

Notes

Appendix 1. Dimensions and explanation of efficiency indicators

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