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Change in ownership among U.S. community hospitals has been frequent and, not surprisingly, remains an important issue for both researchers and public policy makers. In the past, investor-owned hospitals were long suspected of pursuing financial over other goals, culminating in several reviews that found few differences between for-profit and nonprofit forms (Gray, 1986; Sloan, 2000; Sloan, Picone, Taylor, & Chou, 2001). Nevertheless, continuing to the present day, several states prohibit investor-ownership of community hospitals. Conversions to investor-ownership are only one of six types of ownership change, however, with relatively less attention paid to the other types (e.g., for-profit to nonprofit, public to nonprofit). This study has two parts. We first review the literature on the various types of ownership conversion among community hospitals. This review includes the rate at which conversions occur over time, the relative frequency in conversions between specific ownership categories and the observed effects of conversion on hospital operations (e.g., strategic direction and decision-making processes) and performance (e.g., access, quality, and cost). Overall, we find that the impact of ownership conversion on the different measures is mixed, with slightly greater evidence for positive effects on hospital efficiency. As one explanation for these findings, we suggest that the impact of ownership conversion on hospital performance may be mediated by changes in the hospital's strategic content and process. Such a hypothesis has not been proposed or examined in the literature. To address this gap, we next study the role of strategic reorientation following hospital conversion in a field study. We conceptualize ownership conversion within a strategic adaptation framework, and then analyze the changes in strategy content and process across sixteen hospitals that have undergone ownership conversions from nonprofit to for-profit, public to for-profit, public to nonprofit, and for-profit to nonprofit. The field study findings delineate the strategic paths and processes implemented by new owners post-conversion. We find remarkable similarity in the content of strategies undertaken but differences in the process of strategic decision making associated with different types of ownership changes. We also find three main performance effects: hospitals change ownership for financial reasons, experience increases in revenues and capital investment post-conversion, and pursue labor force reductions post-conversion. Membership in a multi-hospital system, however, may be a major determinant of both strategy content and decision-making process that is confounded with ownership change. That is, ownership conversion may mask the impact of system membership on a hospital's strategic actions. These findings may explain the pattern of performance effects observed in the literature on ownership conversions.

In 2009 and 2010, the Financial Accounting Standards Board (FASB) adopted new accounting standards for nonprofit mergers and acquisitions. The new accounting standards are an example of the constitutive role accounting can play in how people think about economic events, since the FASB defined a new concept (the “inherent contribution”) and required valuation of intangible assets that were often previously unrecognized.

The FASB’s stated goals included minimizing “pooling” accounting and maximizing transparency regarding fair value information, acquired identifiable intangible assets, and the relation between consideration paid and the fair values of identifiable assets acquired. The FASB expected many combinations would involve little or no consideration. It also expressed concern that some organizations would undervalue assets acquired, especially intangible assets.

For a sample of 2012–2017 nonprofit hospital combinations, we find general agreement with the FASB’s expectations. Almost all combinations were accounted for as acquisitions, not mergers, even though there was frequently no consideration paid. More acquirers recorded “inherent contributions” than goodwill, because the net fair value of the acquired hospital’s identifiable assets exceeded the consideration paid. Acquirers ascribed value to assets, such as intangible assets, that would have gone unreported under the prior accounting rules, although lower levels of intangible assets were recognized in nonprofit business combinations, relative to total non-goodwill assets acquired, than in public companies’ acquisitions.

Hospitals are complex organisations accounting for most of total health expenditure. They play a critical role in providing care to patients with high levels of need. A key policy concern is that patients receive high quality care. Policymakers have attempted to influence hospital quality in different ways. This chapter focuses on three key policy levers: the extent to which hospital competition and higher hospital tariffs (of the DRG type) can stimulate quality, and whether non-profit hospitals provide higher or lower quality than for-profit ones. The chapter outlines key methodological challenges and selectively reviews the main findings from the literature. While several studies suggest that hospital competition reduces mortality rates for heart attack cases when hospital tariffs are fixed (under a DRG system), at this stage is unclear whether the effect holds across a range of quality indicators. Moreover, the limited literature on hospital mergers tends to suggest that hospital quality does not change following a merger. Finally, whether non-profit hospitals provide higher or lower quality varies across regions and institutional arrangements. The economic theory suggests several mechanisms with opposite effects on quality. To guide policy, future work needs to further unpack the various mechanisms through which these three key policy issues affect hospitals incentives.

Public hospitals have long been major players in the US health care delivery system. However, many public hospitals have privatized during the past few decades. The purpose of this chapter was to investigate the impact of public hospitals' privatization on community orientation (CO). This longitudinal study used a national sample of nonfederal acute-care public hospitals (1997–2010). Negative binomial regression models with hospital-level and year fixed effects were used to estimate the relationships. Our findings suggested that privatization was associated with a 14% increase in the number of CO activities, on average, compared with the number of CO activities prior to privatization. Public hospitals privatizing to for-profit status exhibited a 29% increase in the number of CO activities, relative to an insignificant 9% increase for public hospitals privatizing to not-for-profit status.

Purpose – This chapter examines how drug prescribing behavior in Taiwanese hospitals changed after the government changed reimbursement systems. In 2002, Taiwan instituted a system in which hospitals are reimbursed for drug expenditures at full price from a fixed global budget before the remaining budget is allocated to reimburse all other expenditures, often at discounted prices. Providers are thus given a financial incentive to increase prescriptions.

Methodology – We isolate the effect of this system from that of other confounding factors by estimating a difference-in-difference model to analyze monthly drug expenditures of hospital departments for outpatients during the years 1999–2006.

Findings – Our results suggest that hospital departments which use drugs more heavily as part of their regular medical care increased their drug prescription expenditures after the implementation of the global budget system. In addition, we find that the response was stronger among for-profit than not-for-profit and public hospitals.

Implications – Hospital doctors responded to the financial incentive created by the particular global budgeting system adopted in Taiwan by increasing expenditures on drug treatments for outpatients.

Purpose – Research on hospital system organization is dated and cross-sectional. We analyze trends in system structure during 2000–2010 to ascertain whether they have become more centralized or decentralized.

Design/Methodology/Approach – We test hypotheses drawn from organization theory and estimate empirical models to study the structural transitions that systems make between different “clusters” defined by the American Hospital Association.

Findings – There is a clear trend toward system fragmentation during most of this period, with a small recent shift to centralization in some systems. Systems decentralize as they increase their members and geographic dispersion. This is particularly true for systems that span multiple states; it is less true for smaller regional systems and local systems that adopt a hub-and-spoke configuration around a teaching hospital.

Research Limitations – Our time series ends in 2010 just as health care reform was implemented. We also rely on a single measure of system centralization.

Research Implications – Systems that appear to be able to centrally coordinate their services are those that operate in local or regional markets. Larger systems that span several states are likely to decentralize or fragment.

Practical Implications – System fragmentation may thwart policy aims pursued in health care reform. The potential of Accountable Care Organizations rests on their ability to coordinate multiple providers via centralized governance. Hospitals systems are likely to be central players in many ACOs, but may lack the necessary coherence to effectively play this governance role.

Originality/Value – Not all hospital systems act in a systemic manner. Those systems that are centralized (and presumably capable of acting in concerted fashion) are in the minority and have declined in prevalence over most of the past decade.

It is well recognized that hospitals do not operate in a competitive market typically observed in the economics literature, but rather alternative measures of performance must be developed. In other words, health policy analysts, managers, and decision-makers cannot rely on determining efficiency via the typical profit maximizing/cost minimizing firm but develop techniques that address the issues germane to hospital productivity. What has been presented in this book demonstrates the research in both productivity and policy that must attend to this anomaly. In this introductory section, we briefly summarize the theoretical underpinnings of this book.

Based on the Current Population Survey, 46.6 million Americans did not have health insurance in 2005 (Center on Budget and Policy Priorities, 2006). Lack of insurance is often associated with lower utilization rates, which may in turn adversely affect health status (Ayanian, Weissman, Schneider, Ginsburg, & Zaslavsky, 2000). Since universal health insurance is not provided for in the US, uninsured individuals must either self-pay or rely on charity care provided by hospitals and health clinics. The majority of charity care is produced in the public sector, either at the state, county, or local level (federal hospitals primarily serve a particular segment of the population – e.g., veterans in the case of Veterans Administration hospitals). Public hospital provision of “safety net” hospital services is particularly prevalent in large urban areas (Lipson & Naierman, 1996). These safety net hospitals are defined by the Institute of Medicine as having an “open door policy to serve all patients regardless of their ability to pay and provide substantial levels of care to Medicaid, the uninsured, and other vulnerable patients” (IOM, 2000). Private not-for-profit (NFP) hospitals also provide charity care but to a lesser extent than public providers, especially since the imposition of cost cutting measures both by Medicare and Medicaid (federal programs that fund health care for the elderly and indigent, respectively) and by managed care. Given that approximately 15% of US GDP is allocated to health care, cost cutting measures are laudable; however, care still needs to be provided for individuals who cannot afford it, and the burden of providing this care has to be borne somewhere in the health care system.

Micro hospitals are a new form of for-profit health-care facility with rapid expansion in some parts of the country. They continue to grow in Texas without in-depth public understanding or explicit policy guidance on their role in the health-care system. Our project aims to define socioeconomic and demographic characteristics of areas served by micro and regular hospitals, and by doing so help assess micro hospitals' impact in expanding health-care access for disadvantaged populations in Texas.

We (1) estimated hospital service areas (catchment areas) with a spatial model based on advanced Geographic Information System (GIS) methods using a proprietary ESRI traffic network; (2) assigned population socioeconomic measures to the catchment areas from the 2014–2018 American Community Survey 5-Year Estimates, weighted with an empirically tested Gaussian distribution; (3) used two-tailed t-tests to compare means of population characteristics between micro and regular hospital catchment areas; and (4) conducted logistic regressions to examine relationships between selected population variables and the associated odds of micro hospital presence.

We found micro hospitals in Texas tend to serve a population less stressed in health-care access compared to those who are more in need as measured by various dimensions of disadvantages.

Our analysis takes a cross sectional look at the population characteristics of micro hospital service areas. Even though the initial geographic choices of micro hospitals may not reflect the long-term population changes in specific neighborhoods, our analysis can provide policy makers a tool to examine health-care access for disadvantaged populations at given point in time. As the population socioeconomic characteristics have long been associated with health-care inequality, we hope our analysis will help foster structural policy considerations that balance growing health-care delivery innovations and their social accountability.

We used GIS based spatial modeling to dynamically capture the potential patient basis by travel time calculated with a street network dataset, rather than using the traditional static census tract to define hospital service areas. By integrating both spatial and nonspatial dimensions of healthcare access, we demonstrated that the policy considerations on the implications of equal opportunity for health-care access need to take into account the social realities and lived experiences of those experiencing the most vulnerability in our society, rather than a conceptual “equality” existing in the spatial and market abstraction.

Hospitals worldwide command the majority of any countries’ health care budget. Reasons for these higher costs include the aging of the population requiring more intensive health care treatments provided in hospitals, the relatively high costs of labor in this labor intensive industry and payment systems that may encourage inefficient behavior on the part of hospital managers and physicians, that have not been fully mitigated via reforms and regulations.