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date: 19 October 2019

Changes in Hospital Financing and Organization and Their Impact on Hospital Performance

Summary and Keywords

Since the 1980s policymakers have identified a wide range of policy interventions to improve hospital performance. Some of these have been initiated at the level of government, whereas others have taken the form of decisions made by individual hospitals but have been guided by regulatory or financial incentives. Studies investigating the impact that some of the most important of these interventions have had on hospital performance can be grouped into four different research streams. Among the research streams, the strongest evidence exists for the effects of privatization. Studies on this topic use longitudinal designs with control groups and have found robust increases in efficiency and financial performance. Evidence on the entry of hospitals into health systems and the effects of this on efficiency is similarly strong. Although the other three streams of research also contain well-conducted studies with valuable findings, they are predominantly cross-sectional in design and therefore cannot establish causation. While the effects of introducing DRG-based hospital payments and of specialization are largely unclear, vertical and horizontal cooperation probably have a positive effect on efficiency and financial performance. Lastly, the drivers of improved efficiency or financial performance are very different depending on the reform or intervention being investigated; however, reductions in the number of staff and improved bargaining power in purchasing stand out as being of particular importance.

Several promising avenues for future investigation are identified. One of these is situated within a new area of research examining the link between changes in the prices of treatments and hospitals’ responses. As there is evidence of unintended effects, future studies should attempt to distinguish between changes in hospitals’ responses at the intensive margin (e.g., upcoding) versus the extensive margin (e.g., increase in admissions). When looking at the effects of entering into a health system and of privatizations, there is still considerable need for research. With privatizations, in particular, the underlying processes are not yet fully understood, and the potential trade-offs between increases in performance and changes in the quality of care have not been sufficiently examined. Lastly, there is substantial need for further papers in the areas of multi-institutional arrangements and cooperation, as well as specialization. In both research streams, natural experiments carried out using program evaluation design are lacking. One of the main challenges here, however, is that cooperation and specialization cannot be directly observed but rather must be constructed based on survey or administrative data.

Keywords: reforms, hospitals, performance, efficiency, diagnosis-related groups, health systems, privatization, cooperation, specialization, health economics

Background of Changes in Hospital Financing and Organization

Rising health expenditure and tight public budgets have led policymakers in many countries to seek ways to improve the performance of healthcare organizations. In most countries, hospitals in particular are thought to have huge potential to improve their performance and are increasingly being held accountable for such improvements. Indeed, since the 1980s policymakers have identified a wide range of policy interventions to this effect.

Some of these interventions have been initiated at the government level, including: payment systems, such as those based on diagnosis-related groups; reforms in hospital planning, such as the centralized commissioning and decommissioning of hospital services for different regions; and the introduction of quality assurance systems. In health systems that are more market-oriented, such as in the United States, Germany, and Switzerland, measures to improve the performance of hospitals may take the form of individual decisions made by the hospitals themselves, albeit within regulatory and payment systems that may give hospital owners incentives to choose certain options over others. Examples include a hospital’s entry into a health system, privatization, cooperation with other hospitals or healthcare organizations, and specialization in certain services. While for instance in Sweden the regional government decides whether a specific hospital should specialize in a certain area, in Germany hospitals make this kind of decision themselves (at least within the framework of capacity planning undertaken at the level of each of Germany’s 16 states). The interventions presented in this article were chosen based on their policy relevance and the availability of empirical evidence, and are as follows: the introduction of Diagnosis-Related-Groups (DRG)-based hospital payments; the entry of hospitals into multi-institutional arrangements, privatization that can occur in these situations, and the entry of hospitals into looser cooperation arrangements; and, lastly, the specialization of hospitals.

The purpose of this article is to give an overview of studies investigating the impact on hospital performance of key reforms in the sector. In doing so, the article aims to group these studies into research streams, assess their validity, and synthesize their results. The article will also identify the drivers of the effects associated with, or resulting from, certain reforms. The policy implications of our findings and avenues for further research are subsequently presented and discussed.

Definition of Hospital Performance and Methodological Approaches

Definitions of hospital performance vary considerably depending on context. Those used by medical researchers often differ from those used by economists. In the medical literature, hospital performance is frequently understood to refer to quality of care, whether in terms of processes or outcomes. A measure of the former is the initiation of treatment within a specified time after arrival for certain emergency conditions. Some measures of the latter are in-hospital or post-hospitalization mortality rates, and the rate of readmission to hospital. In contrast, the economic literature frequently defines hospital performance in terms of financial performance and efficiency, although recently more and more economic papers have emerged that measure hospital performance as quality of care (Gaynor, Laudicella, & Propper, 2012). Efficiency can be defined as a measure of how well an organization produces output (i.e., treatments or cases) from a given amount of input, especially human and technological resources. It can be broken down into technical, cost, and profit efficiency. This article will focus primarily on studies that use parameters of financial performance, parameters of efficiency, or both.

Studies that analyze financial performance are usually undertaken in competitive hospital markets characterized by a large proportion of for-profit/nonprofit hospitals that have access to capital markets, as is the case for example in the United States and Germany (Shen, 2003; Büchner, Hinz, & Schreyögg, 2016; Ramamonjiarivelo, Weech-Maldonado, Hearld, Pradhan, & Davlyatov, 2018). By ownership, hospitals can generally be divided into private hospitals, which are invested in and owned by private entities (i.e., individual or several private owners), and public hospitals, which are invested in and owned mainly by public entities such as governments (Tiemann & Schreyögg, 2009). Private hospitals can be further classified as for-profit or nonprofit. Typical measures of financial performance across different ownership types are operative cash flow, equity ratio, profit before tax, and debt ratio. The assumption underlying studies of financial performance is that hospitals behave as profit-maximizing entities in competitive hospital markets even if they are forced to reinvest their surpluses, as is the case with nonprofit and many public hospitals. It can also be argued that in markets in which the state does not provide sufficient funding for capital costs, public and nonprofit hospitals are forced to generate surpluses to cover these costs and ensure survival of the organization (Shen, Eggleston, & Lau, 2007).

The assumption that hospitals of all ownership types behave as profit-maximizing entities is, however, highly controversial in the literature because different ownership types may be associated with different internal incentive structures. Indeed, there is a large body of literature on theoretical assumptions about differences in behavior between organizations with different ownership types. For instance, property-rights theory assumes that ownership of a firm involves two essential rights: (1) the right to control the firm and (2) the right to appropriate its profits (i.e., the financial surplus). Accordingly, the defining difference between hospitals that are for-profit and those that are public or nonprofit is that the latter two are precluded from distributing their surplus to those in control of the organization. This is known as the non-distribution constraint (Hansmann, 1988).

This being said, agency theory assumes that managers (or agents) seek to maximize their own utility rather than that of the organization or its owners (or principals). As a result, in hospitals of all three ownership types, hospital owners face a principal–agent problem. However, it is assumed that for-profit hospitals are able to address this more effectively, as their owners can use profits as their measure of the manager’s success, limiting any deviation from their interest by making the manager’s compensation a positive function of these (Newhouse, 1970; Fama & Jensen, 1983).

Another important point to consider is that private entities have access to capital markets and thus have an incentive to generate high profits to attract investors. In contrast, public and nonprofit hospitals are assumed to be generally averse to profit maximization. This is especially the case for public hospitals, which can have their profits taken away by public owners and spent on other public goods (Pestieau, 2009). It is therefore reasonable to assume that—depending on a country’s regulatory environment—using financial performance criteria to measure hospital performance may lead to bias if ownership types are not taken into account.

In some situations, the most meaningful measure of performance might be a combination of financial performance and efficiency. When an organization is privatized, for example, it is expected to increase its profitability. One of the measures that privatized organizations often take to do so is to reduce their number of staff, which for instance was found by Heimeshoff, Tiemann, and Schreyögg (2014) to be the case in Germany. Organizational changes such as this tend to be directly visible in efficiency measures (e.g., staff reduction as decreasing inputs), whereas the effect of organizational changes on financial performance often takes some time (e.g., Tiemann & Schreyögg, 2012).

With regard to their methods, studies assessing how changes in hospital financing and organization affect hospital performance can be divided roughly into two streams. The first is linked to program evaluation literature (Abadie & Cattaneo, 2018) and focuses on establishing a causal link between interventions and effects while considering selected performance indicators such as costs, revenues, length of stay, and measures of profitability. These studies use difference-in-difference regression models and occasionally also instrumental variable approaches or some kind of matching, for example with propensity scores (Shen, 2003; Gaynor et al., 2012; Clemens & Gottlieb, 2014). The other stream of literature measures changes in hospital efficiency while attempting to capture the production process of a hospital as comprehensively as possible through its inputs and outputs in contrast to selected performance indicators (Rosko, Proenca, Zinn, & Bazzoli, 2007; Büchner, Hinz, & Schreyögg, 2015). Often, studies in this category do not establish a causal link between interventions and effects. These studies measure technical, cost, and profit efficiency and use data envelopment analysis, stochastic frontier analysis, and, more recently, partial frontier analysis. While data envelopment analysis remains by far the most common approach to measuring the efficiency of hospitals (Kohl, Schoenfelder, Fügener, & Brunner, 2018), stochastic frontier and partial frontier analysis are gaining favor as they can be used to overcome certain weaknesses of data envelopment analysis, such as its treatment of outliers (Hollingsworth, 2008; Varabyova, Blankart, Torbica, & Schreyögg, 2017).

Effects of the Introduction of DRG-Based Hospital Payments on Hospital Performance

There is no doubt that case-based payment systems, such as those that use DRGs, have had a major impact on hospital markets. Previous systems were based predominantly on fee-for-service payments, per diem payments, global budgets, or some combination of these. The shift to DRG-based payments was radical and its impact can mainly be attributed to three factors (Street, O’Reilly, Ward, & Mason, 2011):

  1. 1. In DRG-based payment systems, provider revenue is related directly to their workload, leading to greater transparency in the reimbursement of hospital activity.

  2. 2. Payments are based mainly on patient characteristics and procedures performed by the hospital.

  3. 3. DRG-based hospital payments represents a form of yardstick competition, creating a quasi-market to encourage efficiency in the absence of market competition.

The third reason in particular leads to a different incentive structure for hospitals. The aim of yardstick competition is to provide a benchmark for providers, usually based on average market costs, giving them an incentive to reduce costs (Shleifer, 1985). For details on how DRGs are calculated in different health systems, refer to Schreyögg, Stargardt, Tiemann, and Busse (2006). If providers outperform others, they generate a surplus, whereas they generate a deficit if their costs per case are higher than the benchmark. This creates a continual incentive to reduce costs. To ensure an iterative process of cost reduction, all DRG systems have some kind of yearly or bi-yearly updating mechanism (Schreyögg et al., 2006; Street et al., 2011).

Given this radical change in incentive structures, one would expect hospitals to have improved their performance after DRG-based payments were introduced. Although several studies on this topic exist, only a few of them examine how the introduction of DRG-based hospital payments may have affected indicators of performance within the framework of a natural experiment. One reason for this may be the methodological challenge of establishing a causal link between such payment systems and hospital performance. Indeed, countries that have introduced DRG-based payment systems have usually done so nationwide and after a short phasing-in period. This means that there is no comparable control group of hospitals, unaffected by the intervention, that is available for analysis. Although psychiatric care hospitals might, at first glance, appear to be a suitable control group because these were usually excluded from such reforms, they have a completely different case-mix (i.e., patients are often discharged without being cured, in the narrow somatic sense of that word) and the optimal length of stay remains unclear for many psychiatric conditions. Another possible control group might be the hospitals that remained under the old payment system and did not opt into the new DRG-based payment schemes during the period in which the new payment system was gradually phased in. However, even if selection effects are considered, these phasing-in periods have to be regarded as transitions during which different rules apply and the incentives of the new system have not yet been fully implemented. Lastly, the considerable length of the phasing-in periods in most countries presents its own methodological challenges. Because these periods usually lasted a couple of years, other hospital reforms were often initiated in parallel, making it difficult, if not impossible, to distinguish between the effects of each.

The few studies that do examine the impact of DRG-based payments on hospital performance have yielded mixed results. In Portugal (Dismuke & Sena, 1999; 2001), Sweden (Gerdtham et al., 1999a, 1999b), and Norway (Biørn et al., 2003; Hagen et al., 2006), the introduction of the new payment system appears to have led to increases in technical efficiency. In Switzerland, where the new payment system was introduced in a staggered fashion across different cantons, Widmer (2015) found increases in cost efficiency, albeit in a small sample of hospitals. In each of these studies, efficiency gains were realized through reduced inputs (fewer staff, shorter length of stay), increased outputs (more admissions), or both.

A number of other researchers, however, did not observe a positive impact on performance. Studies on hospitals in the United States (Borden, 1988; Chern & Wan, 2000) and Austria (Sommersguter-Reichmann, 2000) did not find any increase in technical efficiency. Herwartz and Strumann (2014) found a significant decline in technical efficiency in a sample of German hospitals. For Norway, Biørn et al. (2003) and Hagen et al. (2006) found mixed evidence on the impact of the new payment system on cost-efficiency.

While the heterogeneity of these results may be due in part to the different methods used in each study to estimate efficiency, it is probably also a function of very different health systems and contexts in the different countries. Each country has different reimbursement mechanisms; payment mechanisms, such as additional reimbursement components, that differ in their relevance; and, of course, a host of different and often simultaneous healthcare reforms. It should also be mentioned that none of the studies examined a possible trade-off between quality and efficiency after the introduction of DRG-based payments, even though some researchers have found such trade-offs in hospital care independent of DRGs (e.g., McKay & Deily, 2008).

Even if there is no convincing evidence that DRG-based payments have improved hospital performance, it is likely that yardstick competition has encouraged hospitals to adopt some of the organizational patterns seen in other markets. This may have facilitated other changes at the hospital level, such as cooperation, mergers (privatization), and specialization, all of which will be examined in later sections of this article.

Another, newer stream of research looks at how hospitals have responded to changes, especially changes in price, within existing DRG-based payment systems. Depending on the changes in question and context in which the sample of hospitals was located, studies in this stream have found causal links to the upcoding of patients into more profitable diagnoses and increases in the number of admissions, as well as to changes in treatment intensity, clinical pathways, and the range of services (Cutler, 1995; Duggan, 2000; Dafny, 2005; Acemoglu & Finkelstein, 2008; Clemens & Gottlieb, 2014). One of the main challenges in this stream of research is to find the best approach with which to distinguish between hospital responses at the intensive margin (e.g., upcoding) versus the extensive margin (e.g., increase in admissions). Although this stream of research is related only indirectly to hospital performance, it underscores how important it is to monitor how hospitals respond to changes within existing DRG-based payments systems and whether, and to what extent, such systems have unintended effects.

In summary, several studies have investigated how the introduction of DRG-based hospital payments may have affected efficiency in hospitals. Their results, however, are mixed, which may be explained by the different methods employed by the studies and, perhaps more importantly, the different national-policy contexts in which their samples of hospitals were situated. In cases where gains in efficiency were observed, these were realized through reduced inputs (fewer staff, shorter length of stay), increased outputs (more admissions), or both. This research stream suffers from two structural problems: (1) Usually there is no control group available for comparison because DRG-based systems are generally rolled out nationwide; and (2) the period during which most DRG-based payment systems are phased in is long, which means that other reform initiatives have generally been introduced in parallel, making it difficult if not impossible to distinguish between the effects of each. Another stream of research examines the causal link between price changes for given treatments and hospitals’ responses to these. The results of such studies suggest that price changes have had unintended effects and that careful monitoring of these is important. Future research should build upon these studies and disentangle effects at the intensive (e.g., upcoding) versus the extensive margin (e.g., increase in admissions).

Effects of Multi-Institutional Arrangements on Performance

Following the introduction of competitive market mechanisms to the hospital sector, it has become increasingly difficult for individual hospitals to survive. Hospitals have responded by cooperating with other healthcare organizations or by merging with other hospitals. Hospitals that enter into multi-institutional arrangements are assumed to be able to reduce costs and increase efficiency through economies of scale, as well as scope and synergy effects. Costs can be reduced primarily by consolidating or decreasing the number of redundant activities, including administrative (e.g., accounting) or support (e.g., pharmacy) functions, which are often centralized after entering into such arrangements. Moreover, within such arrangements, access to information in the form of clinical expertise may be enhanced, allowing hospitals to provide a greater range of health services, increase their output, or use their capacities more efficiently. Hospitals in multi-institutional arrangements can gain market power by achieving a competitive advantage over individual hospitals. Lastly, such arrangements are assumed to make it easier for hospitals to recruit staff, access capital and financial services, improve the skills of their workforce through the exchange of information and expertise, and increase their bargaining power (Oliver, 1990; Büchner et al., 2016).

There are at least three different forms of multi-institutional arrangement: health systems, health networks, and co-optation. The first two of these are particularly common and cover a range of complex multi-institutional relationships (Rosko et al., 2007). Health systems involve multiple hospitals that operate under the centralized ownership of a key organization (sometimes called a hospital corporation), whereas health networks are strategic alliances or contractual affiliations between hospitals and other health organizations that provide a diverse range of health services. The defining difference between the two arrangements is that a health system has a single owner, whereas a health network features diversified ownership by affiliated hospitals and other organizations (Shortell, Bazzoli, Dubbs, & Kravolec, 2000). A looser and less common form of multi-institutional arrangement is co-optation, which provides only a personal link between these organizations. For instance, a member of the board of one hospital may be member of the advisory board of another.

These arrangements differ according to the extent to which a hospital loses autonomy when entering into one of them and the need for coordination between the different organizations. While hospitals entering a health system through mergers lose some of their autonomy, the need for coordination among hospitals within such arrangements is lower than in other multi-institutional arrangements, at least after the initial adaptation phase. The opposite applies to co-optation. In the following we will focus on mergers and the joining of health networks as the most common types of entry into multi-institutional arrangements.

The Impact Entering Into a Health System on Hospital Performance

In terms of ownership type, health systems may be public, nonprofit, or for-profit. Thus, the only case in which the entry of an individual hospital into a health system can be defined as a privatization is that in which the health system is privately owned. There are two different streams of literature that look at how entering into a health system affects hospital performance. The first stream examines all entries into health systems regardless of health system ownership and focuses on specific organizational patterns (e.g., centralization vs. decentralization), whereas the second stream examines the impact of privatization specifically.

Entering Into Health Systems of Any Ownership Type

Most studies in the first stream look at hospitals located in the US market and are cross-sectional. These studies can be divided into two categories: The first examines hospitals in health systems and their association with hospital efficiency. Two of these studies focused on the effect of hospital membership in health systems. Carey (2003) found weak evidence for a positive association between health-system membership and cost-efficiency. Rosko et al. (2007) investigated different types of health systems, particularly centralized and decentralized ones. They concluded that membership of these can be positively or negatively related to cost inefficiency. Two other studies focused on the effects on hospital efficiency of providing hospital services at the health-system level. Rosko and Proenca (2005) found that hospitals that provide a moderate to high proportion of their services at the system level are more efficient than hospitals that do not. Proenca, Rosko, and Dismuke (2005) analyzed this effect on cost-efficiency and revealed that the proportion of hospital services provided at the system level was negatively related to hospital costs. But while these four studies found a positive relationship between system membership and hospital efficiency, their findings are based on study designs that do not allow us to establish causation. The only longitudinal study on this topic was undertaken by Büchner et al. (2015) using a difference-in-difference framework in a sample of German hospitals. It found that the technical efficiency of the hospitals that entered into the health system increased in the fourth year after entry. The results were robust, and technical efficiency increased over time and was realized mainly through (1) synergies in the purchasing of supplies, such as drugs and medical devices, and (2) reductions in the number of administrative and nonclinical staff after entry into the health system.

The second category of studies looks at the impact of health-system membership on hospital financial performance. Bazzoli et al. (2000) examined US data using a comprehensive set of nine indicators of financial performance, including measures of profitability such as total margin and return on total assets, as well as hospital costs, liquidity, department structure, and asset efficiency. They found that hospitals in moderately centralized health systems showed better financial performance than those in other types of systems. In particular, they found that hospitals in health systems perform better than those in networks. Another study, by Tennyson and Fottler (2000), analyzed the impact of health-system membership on financial performance using data on US hospitals from 1986 and 1992. Financial performance was measured in two different years as operating margin, total margin, and return on assets. The authors found that system membership was associated with a decrease in financial performance in 1986 but had no significant impact in 1992. Büchner et al. (2016) use a difference-in-difference framework examining operating margins, return on investment, earnings after taxes, and earnings before interest and taxes in a sample of German hospitals. They found that entering into a health system had a positive effect on financial performance one year after entry. However, this effect appeared to be transitory, disappearing in the second year. Thus, there is no clear evidence that entering into a health system has an impact on a hospital’s financial performance. Connor, Feldman, and Dowd (1998) and Dranove and Lindrooth (2003) both use a difference‐in‐difference approach, while Dranove and Lindrooth (2003) additionally uses a matching approach. Both studies are based on US data and find that significant cost reductions result from mergers. Gaynor et al. (2012) use an event study design similar to a difference-in-difference approach and examine hospital mergers among public hospitals in the UK between 1997 and 2006. They include parameters for financial performance, productivity, waiting times, and quality of care. While admissions and staff numbers decreased, which was desirable if the intention was to remove spare capacity, labor productivity did not rise and financial deficits even increased. Most measures for quality remained unchanged. Thus, the authors conclude that apart from reductions in capacities, no positive effects of mergers could be found.

In summary, the evidence on the effect of entering into a health system, regardless of a health system’s ownership type, suggests that there is likely to be an increase in efficiency. The effects on financial performance, however, are not clear, although mergers seem to be followed by cost reductions. The most important limitations of many of these studies are their cross-sectional nature and their failure to differentiate between health system ownership types, which may increase variance and therefore lead to imprecise estimates. The main drivers of increased efficiency were found to be synergies in the purchasing of supplies, such as drugs and medical devices, and reductions in the number of administrative and non-clinical staff.

Entering Into Health Systems That Are Privately Owned

The second stream of literature focuses on single hospitals that enter into health systems that are privately owned, that is, privatizations. These privately owned health systems may operate under a for-profit or a nonprofit regime. The literature distinguishes between two main forms of privatization: formal and material. Formal privatization, also known as corporatization, involves a change in legal form but not in ownership. Using a difference-in-difference framework, Lindlbauer, Winter, & Schreyögg (2016) found that this change in legal form was associated with increased technical efficiency. However, we will focus in the following on material privatization, which involves both a change in legal form and a change in ownership. Typically, in such cases, a public hospital is sold to a privately owned health system, but some studies also define the change from nonprofit to for-profit ownership as a privatization event.

In the 1980s and 1990s, several countries created incentives for the material privatization of hospitals. The United States and Germany, in particular, underwent several strong waves of privatization. Between 1975 and 2015, the number of for-profit hospitals in the United States increased from 775 to 1,035, while the number of nonprofit hospitals decreased from 3,339 to 2,849 (American Hospital Association, 1976–2018). Sloan, Ostermann, & Conover (2003) showed that, in the United States, the likelihood of privatization was higher for hospitals with low margins and high debt-to-asset ratios. Between 1991 and 2017, the number of for-profit hospitals in Germany increased from 358 to 707, while the number of nonprofit hospitals decreased from 943 to 674 (Statistisches Bundesamt, 1993–2018). However, in both countries, the pace of privatization has slowed dramatically in recent years. In the United States, the number of for-profit hospitals peaked in 2012 at 1068 and has steadily decreased since then. In Germany, only 10 hospital privatizations have taken place since 2002. While the reasons for this in both countries are not entirely clear, it may be due to diminished confidence in private entities after the financial crisis of 2007–2008. In Germany, the number of formal privatizations has increased instead, enabling the owners (i.e., communities, counties, or regions) to continue to influence hospitals’ development (Lindlbauer et al., 2016).

There are numerous studies comparing the performance of public and private (for-profit/nonprofit) hospitals in countries in which both types of ownership coexist (e.g., Farsi & Filippini, 2008; Herr, 2008; Herr, Schmitz, & Augurzky, 2011; Siciliani, Sivey, & Street, 2013). In a meta-review of these, Shen et al. (2007) concluded that there was little evidence to support the standard assumption that private for-profit hospitals outperform hospitals with other types of ownership. Kruse, Stadhouders, Adang, Groenewoud, and Jeurissen (2018) confirmed this finding in a recently published review of studies conducted in European countries. The majority of these studies compare the efficiency of hospitals using data envelopment analysis or stochastic frontier analysis. Some of them also focused on measures of accessibility (e.g., waiting times) or quality of care (e.g., mortality and readmission rates), with mixed results. All of these studies, however, are limited by their cross-sectional perspective. Only a few go beyond this approach and examine privatization as a natural experiment using a longitudinal data set.

Using measures of financial performance such as profit margins, capacity, staffing ratios, salaries, patient mix, and the amount of unprofitable care, Shen (2003) and Picone Chou, and Sloan (2002) examined the impact of changes in ownership on hospital performance in the United States. Both studies found that hospitals that had converted from public or nonprofit status to for-profit status increased their profit margins and reduced staffing ratios. In addition, Shen (2003) found that such hospitals reduced cost and increased revenue. She also found that a change from public or for-profit status to nonprofit status resulted in slight reductions in cost and in the number of nursing staff, but did not lead to increased profit margins. The results of a recently published study by Ramamonjiarivelo et al. (2018), which included privatizations from 1997 to 2013, confirmed that privatization is associated with gains in financial performance. In particular, the authors found that increases in operating margin and total margin were substantially larger for for-profit privatizations than for nonprofit ones.

Two studies have assessed changes in efficiency after hospital privatization. Tiemann and Schreyögg (2012) use a difference-in-difference matching approach based on data envelopment analysis efficiency scores in a sample of German hospitals. They examined privatizations from public to for-profit and from public to nonprofit ownership and found strong gains in technical efficiency of around 2.9 to 4.9%, depending on the year, after privatization. Efficiency gains were of similar magnitude for for-profit and nonprofit conversions. The efficiency gains seen in hospitals converted to for-profit status were substantially lower in the DRG era than before it. Another study found that the employment-reducing effect of for-profit privatization, especially among nursing and other clinical staff, was larger than that of nonprofit privatization (Heimeshoff et al., 2014). These findings are similar to those of Picone et al. (2002) and Shen (2003) and raise the question of whether reductions in staff affected the quality of care.

In the US context, Ramamonjiarivelo, Epané, Hearld, McRoy, and Weech-Maldonado (2016) investigated efficiency after hospital privatization using occupancy rate, total full-time equivalent employees per occupied bed, working hours per adjusted patient day, and case-mix-adjusted admissions per full-time equivalent employees as measures of efficiency. They confirmed the finding of Tiemann and Schreyögg (2012) that efficiency generally increases after hospital privatization. Ramamonjiarivelo et al. (2016) did not detect clear advantages for either for-profit or nonprofit privatizations.

Some studies have also examined the quality of care after a change in ownership and found that conversions from nonprofit to for-profit status had a significant negative impact (Picone et al., 2002; Shen, 2002; Shen, 2003) In addition, Farsi (2004) found that a change from for-profit to nonprofit status also had a negative effect on the quality of care. Although studies on the effect of conversions from public to nonprofit or for-profit ownership are lacking, the negative effect observed with other conversions suggests that the resulting restructuring activity may disrupt organizational routines (e.g., in surgical units) or lead to other organizational problems that affect the quality of care. It is therefore crucial to control for the quality of care when examining gains in efficiency and financial performance after hospital privatization (Tiemann & Schreyögg, 2012).

In summary, several studies examine the effects of privatization on hospital performance. Most of these use longitudinal designs. While their results suggest that hospital privatization is likely to increase efficiency and financial performance, there were no consistent differences in effect sizes between for-profit and nonprofit privatizations. Reductions in the number of staff were determined to be the major drivers of gains in performance. In both the United States and Germany, reductions in nursing and other clinical staff were observed. As some studies have reported a decrease in quality of care after privatization, it is crucial for future research to control for quality of care when examining efficiency and financial performance after hospital privatization.

The Impact of Cooperation on Hospital Performance

Almost all countries have policy initiatives that seek to generate synergies, reduce costs, and improve the quality of care by enhancing cooperation between actors in the healthcare sector. At the same time, DRG-based payment systems and other competitive arrangements have made it increasingly difficult for individual hospitals to remain viable. One way for a hospital to escape this situation is to cooperate with other players in the healthcare sector, establishing or joining networks of hospitals and other actors. This can help the hospital in question gain or sustain a competitive advantage over its competitors. It is important in this context to distinguish between formalized and loose cooperation, as well as between horizontal and vertical cooperation arrangements (Mascia, Vincenzo, & Cicchetti, 2012).

Horizontal cooperation involves making arrangements with competing hospitals. It enables hospitals to share administrative or medical resources, such as consolidated purchasing systems or radiology facilities. Vertical cooperation involves inter-organizational partnerships, with partners acting at different levels along the value chain. Vertical cooperation can be forward, which consists of cooperation with long-term care facilities or rehabilitation institutions, or backward, which consists of cooperation with physician groups and outpatient services (Wang, Wan, Clement, & Begun, 2001). However, vertical cooperation and vertical integration have traditionally raised concerns among policymakers that these arrangements might be used strategically to achieve anticompetitive effects (Williamson, 1971). In addition to horizontal and vertical forms of cooperation, there is also diagonal cooperation, such as between a hospital and the pharmaceutical industry.

Although hospital cooperation is widespread and has received great attention in hospital markets in recent years, literature on its impact on performance is scarce. The few studies available tend to focus on formalized cooperation arrangements as opposed to loose ones and cover the impact of horizontal and vertical cooperation. Horizontal cooperation has been found to be associated with increased efficiency (Rosko & Proenca, 2005; Granderson, 2011; Mascia et al., 2012) and financial performance (Vera, 2006; Büchner et al., 2015). For the US hospital market, Rosko showed that moderate or high-intensity use of network resources, in particular, was associated with increased cost-efficiency. Granderson (2011) confirmed this finding. Moreover, the size of the cooperation network of hospitals was found to be positively associated with increased cost-efficiency, a result which was driven by the ability to obtain materials and supplies at lower prices. Mascia et al. (2012) found that, in Italy, efficiency gains were realized mainly through resource complementarities between hospitals. They also found that competition between hospitals in a given region, fostered by new market regulations, did not prevent hospitals from intensifying their cooperation activities. In terms of financial performance, Büchner et al. (2015), in a sample of German hospitals, found a positive effect of horizontal administrative cooperation on operating margins while no significant effect was found for horizontal medical cooperation. They argue that sharing administrative resources creates economies of scale and scope and helps optimize internal processes. Finally, Vera (2006) found that horizontal cooperation increases bargaining power in supplier relationships and improves competitive position.

Regarding vertical cooperation, the majority of the studies go beyond cooperation and focus on vertical integration, in which the cooperation partners along the supply chain no longer have legal autonomy. In general, these studies find a positive association between vertical integration and hospital financial performance (e.g., Kim et al., 2004). However, literature only on vertical cooperation is much scarcer. Distinguishing between cooperation depth (intensity) and breadth (number of cooperation activities), Büchner et al. (2015) found that the latter was significantly related to financial performance but that the former was not. This seems plausible given, for example, the dependence of many hospitals on referrals from primary care physicians. Vera (2006) also found that vertical cooperation was associated with improved financial performance, particularly in terms of increased market share. Furthermore, he compared the effects of horizontal and vertical cooperation and found that the latter was more effective at increasing financial performance than the former. In contrast, Büchner et al. (2015) found that horizontal cooperation (in particular, administrative cooperation) was more effective than vertical cooperation at increasing financial performance. However, interaction effects between vertical and horizontal cooperation arrangements must be considered, because hospitals that maintain strong vertical and horizontal cooperation networks tend to have poorer financial performance. It is likely that a large number of network partners becomes unmanageable at a certain point and transaction costs rise sharply. Generally, it is striking in this stream of research that none of the studies address the question of whether vertical cooperation can generate a similar gain in financial performance and efficiency to that attained by vertical integration.

In summary, studies on the effects of hospital cooperation on financial performance and efficiency generally focus on horizontal rather than vertical cooperation. They have found that horizontal cooperation increases efficiency and financial performance. The size of the cooperation network and whether or not there is a focus on administrative cooperation seem to play an important role in this regard. An improved bargaining power in supplier relationships may be an important driver of this enhanced performance. Fewer studies investigate the impact of vertical integration. They also find positive effects on performance. A broader cooperation network seems to be more important in this respect than the depth of cooperation activities. Patient referrals would appear to be an important driver of improved performance. From a policy perspective, these results suggest that the overall number of cooperation activities should be carefully considered, as they greatly increase transaction costs. Finally, research on the relationship between the cooperation behavior of hospitals and hospital performance is still scarce, and all of the studies that have been published on this topic to date have measured associations rather than establishing causation. Future research should look at changes in cooperation behavior within the framework of a natural experiment, although the designs would be complex due to the different forms and dynamic nature of cooperation.

Effects of Specialization on Performance

Specialization is one of the most discussed topics in health policy, and many decision makers expect specialization to improve performance and increase quality of care at the same time. It is therefore not surprising that a number of difference incentives have been devised to encourage the specialization of hospitals. For instance, the introduction of DRG-based payments has been a major driver of specialization. These payments encourage hospitals to specialize in DRGs, particularly involving elective procedures, that entail low production costs. Doing so may ultimately reduce aggregate hospitalization costs if the specialized hospitals are efficient (Dranove, 1987).

The general idea that specialization can improve performance dates back to Adam Smith and his work on the division of labor (Smith, 1776). Taylor also proposed enhancing organizational performance by deploying workers based on their individual skills (Taylor, 1911). While Smith and Taylor focused on individual specialization, March and Simon proposed distinguishing between individual and higher-level (i.e., organizational) specialization (March & Simon, 1958). For the hospital market, Clark and Huckman (2012) pointed out the potential of linking both approaches in order to measure and operationalize specialization at the level of the operating unit, such as departments, units, or other suitable structures in hospitals.

Investigating the impact of specialization on hospital performance is challenging, however, because it is not a directly observable variable and must therefore be operationalized using administrative data. There are several approaches to doing so, all of which construct a measure based on information about hospital patients grouped into different categories according to their diagnoses (Lindlbauer & Schreyögg, 2014). The most common of these measures in the hospital context is the Information Theory Index (Farley, 1989; Farley & Hogan, 1990), which can also be understood as a measure of diversification (Kim et al., 2015). The Information Theory Index compares the proportions of patients in different diagnosis categories in a hospital with the average proportions for these categories in all hospitals in a country or region. Based on the Information Theory Index, Zwanziger, Melnick, and Simonson (1996) developed a similar measure based on the distance between a hospital’s patient case-mix and a predetermined baseline. Others have used the Herfindahl–Hirschman Index to operationalize specialization as the concentration of diagnoses within hospitals or operational units, such as departments (Baumgardner & Marder, 1991). Another concept was put forward by Daidone and D’Amico (2009), who used an index similar to the Gini coefficient to measure how the proportion of patients in each diagnosis category in a hospital deviated from a uniform distribution.

Lindlbauer and Schreyögg (2014) made two observations about specialization measures like these, which were based on proportions. First, increasing the number of patients in only one category increases its proportion but also decreases the proportions of other diagnosis categories, although there may have been no change in treatment behavior in the latter. Second, relying solely on a proportion-based measure can make it appear that only small hospitals are highly specialized, whereas large hospitals, such as academic medical centers, may be highly specialized as well. To address these limitations, they developed an alternative measure of specialization known as “category medical specialization,” which considers information on the volume of patients in each diagnosis category in addition to concentration. Using this measure, they were able to identify both small and large hospitals that offered specialized hospital services.

Several studies have investigated the relationship between hospital specialization and hospital performance. These use primarily cross-sectional data and do not treat specialization as an event (e.g., one that takes place after new regulation). The majority of these studies focus on efficiency. Among the studies that investigated the relationship between hospital specialization and efficiency, data envelopment analysis or stochastic frontier analysis have been the approaches of choice. As a measure of specialization, these studies use the Information Theory Index (Linna & Häkkinen, 1999; Lee, Chun, & Lee, 2008; Herwartz & Strumann, 2012), the Gini coefficient (Daidone & D’Amico, 2009; Atella et al., 2012) or category medical specialization (Lindlbauer & Schreyögg, 2014). Carey, Burgess, & Young (2008) examined individual specialty hospitals to reduce complexity. These studies used data from hospitals in the United States, Finland, Italy, Korea, and Germany. Lee et al. (2008) and Daidone and D’Amico (2009) found specialization to be positively associated with technical efficiency, whereas Atella et al. (2012) found the relationship to be negative, and Herwartz and Strumann (2012) found that the relationship changed over time. Linna and Häkkinen (1999) found a positive relationship between specialization and cost-efficiency, while Carey et al. (2008) found that individual specialty hospitals were not associated with superior cost-efficiency compared to full-service hospitals. Lindlbauer and Schreyögg (2014) found different results depending on the definition of specialization. When measured using the Information Theory Index and the Gini coefficient, specialization was found to be negatively associated with technical efficiency, whereas it was found to be positively associated with technical efficiency when measured using category medical specialization. The standardization of processes is suggested in the papers to be the primary driver of improved efficiency.

A few papers also investigated the impact of specialization on financial performance. Eastaugh (2011) found that increased specialization among hospitals in the United States was associated with a 10% decline in unit cost per admission. Kim et al. (2015) found that, when identified using the Information Theory Index, specialization had a positive effect on income per bed, whereas it had a significant positive effect on income per specialist, but a negative effect on income per bed when identified using the Herfindahl–Hirschman Index. Finally, Schneider et al. (2007) investigated whether the presence of more specialized hospitals in regional markets had an effect on the costs and profitability of general hospitals. They found that the presence of such hospitals reduced the costs and increased the operating margin of general hospitals and concluded that specialization in the hospital market seems to have important competition effects. Gonçalves and Barros (2013) investigated economies of scope in the provision of auxiliary clinical services that are typically carried out within in-patient facilities in Portuguese hospitals, by estimating a flexible cost function. They found economies of scope for some of the examined services, but not for all.

In summary, while a number of studies have looked at the impact of specialization on performance, the effects remain largely unclear. The main reason for this may be the complexity of measuring specialization. As ITI, HHI, Gini, and category medical specialization all measure different forms of specialization, more research is needed, such as simulation studies, to compare the different concepts and to disentangle the differences between them. These various concepts of specialization and the heterogeneity of samples used in different countries may explain why the studies published to date have yielded such mixed results. Finally, future studies should attempt to investigate specialization as an event using program evaluation techniques, even though self-selection is a limitation in this context.

Discussion of Studies and Promising Avenues for Future Investigation

This article presents an overview of studies that have investigated both the major interventions that have taken place since the 1980s in the financing and organization of hospital services, and their impact on hospital performance. The validity of the studies and their results are highly heterogeneous. Table 1 provides an overview of our key findings for each of the research streams, covering the main effects, drivers, and validity of methods. The table also highlights the challenges in each research stream and the scope for further research.

Table 1. Overview of Key Findings in Different Research Streams

Main Effects on Performance

Drivers Behind Effects

Validity of Methods Used

Challenges of and Scope for Further Research

DRG-based hospital payments

  • Several studies on efficiency

  • Studies find mixed results

  • In studies where there seem to be positive effects, drivers appear to be: staff reduction, shorter length of stay, and increased admissions

  • Two structural problems in this research stream:

  • Usually no control group available as DRGs are usually rolled out nationwide

  • Long time frame for introduction of DRGs

  • New stream of research has emerged examining the link between price changes for given treatments and hospitals’ responses to this

  • Future research should disentangle changes in hospitals’ response at the intensive margin (e.g., upcoding) from the extensive margin (e.g., increase in admissions)

Entry of hospitals into health systems

  • Only a few studies on efficiency and financial performance

  • Studies show increase in efficiency

  • Effects on financial performance are not clear, although some cost reductions found

  • Synergies in purchasing of supplies (e.g., drugs and medical devices)

  • Reduction in numbers of administrative and nonclinical staff

  • Two longitudinal studies/others cross-sectional

  • Sometimes imprecise estimates because of not distinguishing between ownership types

  • More studies are needed on financial performance in particular

  • Future studies should look at hospitals’ entry into health systems as an intervention and consider ownership type in doing so

Privatization

  • Several studies on efficiency and financial performance (United States and Germany)

  • Studies predominantly use longitudinal designs

  • No consistent difference in effect size between for-profit and nonprofit privatizations

  • Staff reduction (all kinds of staff)

  • Reductions in number of nursing staff may affect quality of care

  • Studies on the actual process of privatization are needed (e.g., different strategies)

  • Well-designed studies including control groups

  • Studies show increase in efficiency and financial performance

  • As some studies found decreasing quality of care after privatization, analyzing the trade-off between quality and performance is crucial for future studies

Cooperation

  • Several studies, mainly on efficiency

  • These focus more on horizontal than vertical cooperation

  • Horizontal cooperation increases efficiency and financial performance

  • The few studies on vertical cooperation find positive effects

  • Horizontal cooperation: bargaining power in supplier relationships

  • Vertical cooperation: patient referrals

  • Often small samples

  • All cross-sectional studies

  • Complex measurement due to different forms of cooperation

  • More studies are needed on the effect of vertical cooperation, in particular

  • Future studies should investigate cooperation within the framework of natural experiments

Specialization

  • Several studies mainly on efficiency

  • Contradictory results mainly due to different measures of specialization used

  • In studies where there appear to be positive effects: standardization of processes

  • Large samples

  • Well-developed efficiency measures

  • Mainly cross-sectional

  • Need to compare different specialization concepts and to disentangle differences between them (e.g., through simulation studies)

  • Future studies should attempt to investigate specialization using program evaluation techniques

Table 1 shows that, overall, surprisingly few studies have examined the impact of policy reforms on hospital performance. None of the research streams has a rich body of literature comparable to that seen in other fields of health economics. Chief among the numerous reasons for this are a lack of data—for example the absence of control groups of non-DRG hospitals—and the complexity of the research designs that would be required to investigate, say, the different forms of multi-institutional arrangements that are prevalent in the hospital sector. Of all the evidence, that on the effects of privatization is the strongest. Studies in this research stream use longitudinal designs with control groups and have found robust increases in efficiency and financial performance. Evidence on the entry of hospitals into health systems and the effects of this on efficiency is similarly strong. Although the other three streams of research also contain well-conducted studies with valuable findings, they are predominantly cross-sectional in design and therefore cannot establish causation. Whereas the effects of introducing DRG-based hospital payments and of specialization remain largely unclear, we can conclude that vertical and horizontal cooperation are likely to have a positive effect on efficiency and financial performance. The drivers of improved efficiency or financial performance are very different depending on the reform or intervention being investigated, but reductions in the number of staff and improved bargaining power in purchasing stand out as being of particular importance.

We identified several promising avenues for future investigation. One of these is situated within a new area of research examining the link between changes in the prices of treatments and hospitals’ responses to these. As there is evidence of unintended effects of DRG payments, future studies should attempt to distinguish between changes in hospitals’ responses at the intensive margin (e.g., upcoding) versus the extensive margin (e.g., increase in admissions). When looking at the effects of entering into a health system and of privatizations, there is still considerable need for research. With privatizations, in particular, the underlying processes are not yet fully understood, and the potential trade-offs between increases in performance and changes in the quality of care have not been sufficiently examined. For instance, studies such as that by Bloom et al. (2015), who found a positive impact of competition on management quality, are needed for privatizations to understand the underlying processes. The main challenge for research on privatization is small sample sizes. It is therefore hardly surprising that the few studies that do exist in this area focus on the very large hospital markets in the United States and Germany. It would be useful, however, to widen the scope of this research and pursue the same research questions in studies examining the effects of entering into health systems in general rather than focusing exclusively on privatizations. Lastly, there is substantial need for further papers in the areas of multi-institutional arrangements and cooperation, as well as specialization. In both research streams, natural experiments investigated using program evaluation design are lacking. One of the main challenges here, however, is that cooperation and specialization cannot be directly observed but rather must be constructed based on survey or administrative data. Moreover, there are multiple definitions of specialization, and each of these measures a different form of specialization. More research is clearly needed to disentangle these.

This review has some important limitations. First, the interventions presented in this article were chosen purposively based on a subjective assessment of their policy relevance, real-world impact, and the availability of empirical data. There are, of course, many other interventions that have been undertaken by governments and hospitals in recent years that have also had an impact on hospital performance. Examples include changes in hospital capacity planning (e.g., Karmann & Rösel, 2016), the introduction of selective contracting and other competitive models, for instance in California (e.g., Mobley, 1998), and the introduction of quality assurance and quality certification systems (e.g., Lindlbauer et al., 2016). Second, this review is a narrative one and is not based on a systematic review of the literature. Although we searched for literature in a structured manner in the most common databases, further studies may be available for the different research streams.

Policy Implications

The findings of this review have important implications for health policy. It is often assumed that the major reforms in the hospital sector since the 1980s have led to improved hospital performance. This review suggests, however, that the evidence in this regard is rather mixed, and is strong only for the effects of a hospital entering into a health system, and of privatization. This may come as a surprise to policymakers. DRG-based hospital payments are, however, an important case in point. Almost all high-income and many other countries followed the example of the United States and introduced DRG systems, naturally with certain country-specific adaptions in calculation and payment mechanisms. Yet it has rarely been questioned whether DRG-based hospital payments actually lead to superior performance. Studies showing the unintended effects of these systems have emerged only recently, long after most DRG-systems were fully implemented. While there is no evidence that these unintended effects are severe, it has become clear that setting the right incentives and carefully monitoring each step are much more crucial than had been thought. Policymakers would therefore be well advised to tread more carefully with future policy reforms, and when changing incentives in the hospital sector. Policy interventions would benefit greatly from the running of pilot trials that use control groups and defined evaluation periods before such interventions are implemented across the hospital sector as a whole.

Further Reading

Acemoglu, D., & Finkelstein, A. (2008). Input and technology choices in regulated industries: Evidence from the health care sector. Journal of Political Economy, 116(5), 837–880.Find this resource:

Büchner, A., Hinz, V., & Schreyögg, J. (2015). Cooperation for a competitive position: The impact of hospitals’ cooperation behavior on organizational performance. Health Care Management Review, 40(3), 214–224.Find this resource:

Dranove, D., & Lindrooth, R. (2003). Hospital consolidation and costs: Another look at the evidence. Journal of Health Economics, 22(6), 983–997.Find this resource:

Gaynor, M., Laudicella, M., & Propper, C. (2012). Can governments do it better? Merger mania and hospital outcomes in the English NHS. Journal of Health Economics, 31(3), 528–543.Find this resource:

Herrera, C. A., Rada, G., Kuhn-Barrientos, L., & Barrios, X. (2014). Does ownership matter? An overview of systematic reviews of the performance of private for-profit, private not-for-profit and public healthcare providers. PLoS ONE, 9(12), e93456.Find this resource:

Lindlbauer, I., & Schreyögg, J. (2014). The relationship between hospital specialization and hospital efficiency: Do various measures of specialization lead to different results? Health Care Management Science, 17(4), 365–378.Find this resource:

Shen, Y. C. (2002). The effect of hospital ownership choice on patient outcomes after treatment for acute myocardial infarction. Journal of Health Economics, 21, 901–922.Find this resource:

Shen, Y. C., Eggleston, K., & Lau, J. (2007). Hospital ownership and financial performance: What explains the different findings in the empirical literature? Inquiry, 44, 41–68.Find this resource:

Street, A., O’Reilly, J., Ward, P., & Mason, A. (2011). DRG-based hospital payment and efficiency: Theory, evidence and challenges. In R. Busse, A. Geissler, W. Quentin, & M. Wiley (Eds.), Diagnosis-related groups in Europe: Moving towards transparency, efficiency and quality in hospitals (pp. 93–114). Maidenhead, U.K.: Open University Press.Find this resource:

Tiemann, O., Schreyögg, J. (2012). Changes in efficiency after hospital privatization. Health Care Management Science, 15(4), 310–326.Find this resource:

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