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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. Governments are seeking to instruments to mitigate this cost rise. Liberalizing hospital markets, deregulation, changing budget systems and changing ownership are only a few examples of attempts to make hospitals more efficient.

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.

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.

There is a large body of literature on the efficiency and productivity of hospitals. Most studies focus on the effects of environmental pressures on hospital efficiency, such as payment systems (Dismuke & Sena, 1999; Sommersguter-Reichmann, 2000), competition (Rosko, 1999, 2004), Sari, 2003), and property rights (Gruca & Nath, 2001). Other studies pinpoint their attention to economic phenomena, such as economies of scale (Lindrooth, Lo Sasso, & Bazzoli, 2003; Dranove & Lindrooth, 2003), economies of scope (Prior & Sola, 2000; Grosskopf, Margaritis, & Valdmanis, 2001; Li & Rosenman, 2001), chain membership (Menke, 1997), economic behavior (Blank & Merkies, 2004), and expense preference (Rodriguez-Alvarez & Lovell, 2004).

Ila Semenick Alam is an associate professor. She received her Ph.D. in 1995 from Rice University in Houston, Texas. Her primary fields of specialization are applied econometrics and productivity in various sectors including the airlines, healthcare, and financial institutions. She has published in: Journal of Productivity Analysis, International Economic Review, World Bank Economic Review, Journal of Money, Credit and Banking, Singapore Economic Review, and Productivity and Economic Performance in the Asia-Pacific Region.

The purpose of this chapter is to suggest a general framework for assessing the efficiency of health care in general, and health care interventions specifically. We begin with a three-pronged overview of assessing performance in health care which begins with what we call the budget or cost side model relating budgets and costs to treatments. Next we proceed to describing an intermediate outputs specification which relates hospital resources to medical outcomes, and we conclude with a final outcomes model which relates the medical outcomes to patient health outcomes. The third model is illustrated with an application to data from Swedish cataract patients.

One common feature facing diverse health care organisations is a need to compare performance across geographical areas, institutions or individual practitioners. In all health care systems, comparative data help the central government formulate policies for distributing central grants, clinical education, public health, research and tackling disparities. Good comparative data also provides an important resource for decision-making by local managers and clinicians. Through the process usually known as benchmarking, institutions can explore which of their peers are performing best, and seek out detailed qualitative and quantitative information on the context and processes contributing to good performance. Benchmarking also helps local managers set targets and rewards, and permits local electorates pass judgment on their local governments. The central theme of this chapter is to describe how the national hospital benchmarking system (BMS) was implemented in Finland, focusing on the use of BMS for managerial purposes and its impact on hospital care.