In September 2015, the United Nations General Assembly adopted the resolution titled “Transforming our world: the 2030 Agenda for Sustainable Development” that consists of 17 goals covering the three aspects of sustainable development—economic, social and environmental. Sustainable Development Goal (SDG) 3 aims to ensure healthy lives and promote well-being for all at all ages. One of the targets of SDG 3 (Target 3.8) is focused on achieving universal health coverage (UHC), including financial risk protection, access to quality essential health care services and access to safe, effective, quality and affordable essential medicines and vaccines for all [1].
Achieving UHC calls for increasing the fiscal space for health. One of the means to achieve this is improving efficiency of health systems and is currently gaining more attention due to rapid growth in health expenditure driven by various factors including demographic and epidemiological changes, growth in health technology and rising expectations of the population [2]. The 2018 Declaration of Astana on primary Health Care aptly states that the global community cannot afford waste in health care spending due to inefficiency if universal health coverage and other health and health-related targets of the Sustainable Development Goals are to be achieved [3].
Inefficiency is a pervasive problem in health systems. The World Health Organization (WHO) estimates that, on average, 20–40% of global total health spending is wasted [4]. In 2011, the annual cost of waste to the US health care system was estimated between a low of 21% and a high of 47% of the total health expenditure [5].
Hospitals consume a large proportion of the total health expenditure. In 2016, in the OECD member states, hospitals, on average absorbed about 38% of the total health expenditure. Figures for some of the high-income OECD countries during the same period include Germany (29.1%), USA (34%), Canada (29.3%), the UK (41.7%), Italy (45.5%), France (38.4%) and Denmark (44.3%) [6]. In low and middle-income countries, the proportion of total health expenditure attributed to hospitals is even higher—51% in South Africa in 2013/2014 [7] and 53% in Malaysia in 2015 [8]. For this reason, assessment of efficiency of hospitals has gained the utmost attention of policy makers and managers, as efficient hospitals imply better health systems [9, 10].
A hospital may be defined as an institution, which provides beds, meals, and constant nursing care for its patients while they undergo medical therapy at the hands of a physician with the objective of restoring the patient to health [11]. This definition covers the main attributes of a hospital. However, hospitals are diverse entities in terms of their structure and organization. They range from a small rural hospital in a low-income country, which provides basic services to a large specialized urban hospital in a high-income country endowed with the latest technology and highly skilled workforce.
The core functions of hospitals include patient care, teaching, research and health system support [12]. However, the extent to which hospitals execute some of these functions depends on how they are organized and classified. These will expectedly have an effect on the efficiency of hospitals and the factors that influence efficiency. Hospitals can be divided into different categories based on various criteria [13] including:
- Ownership—public and private hospitals;
- Financial objective—for profit (FP) and not for profit (NFP) hospitals;
- Educational responsibilities—teaching hospital (TH) and non-teaching hospital (NTH);
- Administration or catchment area—primary, secondary and tertiary hospitals;
- Degree of service specification: general and specialized hospitals; and
- Employee status of their doctors: staff model and non-staff model hospitals.
A combination of the above criteria may be used in classifying hospitals. For example, private hospitals may be classified as private for profit or private not for profit.
Many studies have indicated that technical inefficiency in hospitals is widespread in countries at all stages of economic development. Globally about US$ 300 billion is lost annually to hospital-related inefficiency [14]. It is therefore imperative to look for the factors influencing hospital efficiency and propose interventions to address these factors and improve hospital efficiency and enhance performance of the entire health system. As such, this paper has dual objectives. First, information on major determinants of hospital efficiency will be synthesized using a literature search. Second, a framework for addressing hospital inefficiency will be proposed based on the synthesis of the problems.
Hospital inefficiencies may exist in different forms including technical, allocative, scale, scope and cost inefficiency [15]. Technical inefficiency occurs when a hospital fails to maximize outputs for a given level of inputs or resources, or conversely, when a hospital fails to minimize inputs for a given level and choice of outputs. Allocative efficiency occurs when a hospital allocates and uses the least costly combination of inputs in producing its outputs or when hospital resources are committed to produce outputs that are not priorities for society. As for scale efficiency, it is when the size of hospital operations is optimal so that any modifications of its size will render the hospital less efficient. Scope efficiency occurs when a hospital reduces its average cost through the benefit of producing several outputs. Cost efficiencies measure the average cost used in producing outputs compared to a standard or the cost used by other providers.
The efficiency of hospitals is measured using rates/ratios and frontier techniques. The most common frontier techniques of hospital efficiency measurement are data envelopment analysis and stochastic frontier models that include production and cost functions. To identify the factors that influence (in)efficiency some studies use a second-stage regression analysis, in which case, the efficiency or inefficiency scores estimated using the above techniques are regressed against hypothesized influencing factors. Others use non-regression techniques to identify simple associations between the efficiency or inefficiency scores and identified influencing factors.