Show Summary Details

Page of

PRINTED FROM the OXFORD RESEARCH ENCYCLOPEDIA, ECONOMICS AND FINANCE ( (c) Oxford University Press USA, 2019. All Rights Reserved. Personal use only; commercial use is strictly prohibited (for details see Privacy Policy and Legal Notice).

date: 20 November 2019

Contracts and Working Conditions in Medicine

Summary and Keywords

Contracts and working conditions are important influences on the medical workforce that must be carefully constructed and considered by policymakers. Contracts involve an enforceable agreement of the rights and responsibilities of both employer and employee. The principal-agent relationship and presence of asymmetric information in healthcare means that contracts must be incentive compatible and create sufficient incentive for doctors to act in the payer’s best interests. Within medicine, there are special characteristics that are believed to be particularly pertinent to doctors, who act as agents to both the patient and the payer. These include intrinsic motivation, professionalism, altruism, and multitasking, and they influence the success of these contracts. The three most popular methods of payment are fee-for-service, capitation, and salaries. In most contexts a blend of each of these three payment methods is used; however, guidance on the most appropriate blend is unclear and the evidence on the special nature of doctors is insubstantial. The role of skill mix and teamwork in a healthcare setting is an important consideration as it impacts the success of incentives and payment systems and the efficiency of workers. Additionally, with increasing demand for healthcare, changing skill mix is one response to problems with recruitment and retention in health services. Health systems in many settings depend on a large proportion of foreign-born workers and so migration is a key consideration in retention and recruitment of health workers. Finally, forms of external regulation such as accreditation, inspection, and revalidation are widely used in healthcare systems; however, robust evidence of their effectiveness is lacking.

Keywords: contracts, working conditions, blended payments, intrinsic motivation, multitasking, skill mix, teams, retention, external regulation, health economics


Contracts and working conditions for healthcare professionals are an important consideration for policymakers. Contracts involve an enforceable agreement of the rights and responsibilities of both employer and employee. Economic theory of contracts typically involves a principal-agent relationship where, in the presence of uncertainty, the principal must incentivize the agent to act in the principal’s interest (Bolton & Dewatripont, 2005). The principal must create a contract that provides agents not only with the same amount of utility that they could have by not signing the contract but also with enough incentive to not to shirk on their duties once they have accepted the contract, which is known as moral hazard (Hölmstrom, 1979). The nature of healthcare markets complicates this relationship. Due to asymmetry of information in healthcare (Arrow, 1963) patients have a lack of knowledge about the service being provided, which makes it more difficult to gauge whether they have received good-quality treatment (Klarman, 1963). Healthcare is also an experience good, where quality cannot be known until after consumption. Furthermore, illness has an element of randomness such that a good-quality service could have been provided but may still result in a bad outcome. As a result, a profit-maximizing healthcare provider could exploit these features and under- or overprovide services at the expense of a patient’s health.

One way to ensure a high-quality, efficient health service and tackle this moral hazard issue is through payment systems that produce incentives to providers to maintain or improve quality and/or reduce costs. Evidence has shown that payment mechanisms can impact expenditure, utilization, and physician behavior (Devlin & Sarma, 2008; Gosden et al., 2000; Moreno-Serra & Wagstaff, 2010; Wubulihasimu, Brouwer, & Van Baal, 2016). There is also a large body of evidence that evaluates pay-for-performance schemes on quality of care and patient outcomes. Much research has been carried out into the Quality and Outcomes Framework (QOF), the pay-for-performance scheme implemented in the United Kingdom, on patient outcomes and quality of service (Flodgren, Eccles, et al., 2011; Langdown & Peckham, 2013, Scott et al., 2011). However, the results are generally inconclusive due to a lack of studies with robust designs (Eijkenaar, Emmert, Scheppach, & Schöffski, 2013; Greene, 2013; Mendelson et al., 2017).

Regulation is also used to enforce quality of care and services. In previous years, the norm in regulation of the health services has been that performance improvement should be implemented through internal monitoring, for example of clinical standards or mortality rates. Historically there is resistance against imposing on professional autonomy in the medical profession. Furthermore, there is a view that incentivizing performance relies on voluntary take-up by organizations (Healy & Braithwaite, 2006). There is, however, no guarantee that the doctor given the privilege of self-regulation will not shirk on committing to his or her professional duties. Due in part to this, reliance on self-regulation in many health systems has been found inadequate, and more influence by governments to externally regulate care has been adopted. In the United Kingdom at least, the system of self-regulation is no longer seen (Dixon-Woods, Yeung, & Bosk, 2011). However, though widely accepted as necessary, the implications and success of forms of external regulation such as accreditation and inspection are unclear.

On the topic of working conditions in medicine, previous research has found pay rigidities have been linked to vacancies and recruitment and retention problems in the NHS (Elliott, Ma, Scott, Bell, & Roberts, 2007). There is also empirical evidence suggesting changes in wage levels influence workforce participation and number of hours worked for medical professionals (Antonazzo, Scott, Skatun, & Elliott, 2003; Baltagi, Bratberg, & Holmås, 2005; Saether, 2005; Shields, 2004). Contract issues are linked to working conditions of medical professionals, namely in areas such as retention, working hours, and pay levels. Evidence shows that working conditions such as understaffing and insufficient support for new doctors worsens patient experiences and outcomes (Kamau, 2016).

This article highlights five less explored research themes that are important for system efficiency and analyzes these in more detail, noting gaps in the literature where future research is needed. These include (a) salient characteristics that distinguish medical professionals from other workers; (b) the blending of fee-for-service, capitation, and salary payments; (c) teamwork and skill mix; (d) migration and retention; and (e) issues with external regulation. Failing to recognize or take advantage of both individual characteristics and team dynamics may lead to healthcare workers providing suboptimal levels of effort and could affect availability of services and patient outcomes. This article draws examples from health services in other countries, with particular attention to issues in the United Kingdom.

Salient Characteristics of Doctors

The principal-agent relationship in the context of medical workers is further complicated in a health setting by the “double-agent” role of a doctor (Blomqvist, 1991). The doctor acts on the agent’s behalf, interpreting and diagnosing the condition and skillfully implementing relevant treatment. In most countries, the costs of healthcare are covered by a third party, a public or private insurer. So, concurrently, a physician has a responsibility to act in the interests of the payer, taking into account the cost that the services he or she provides in treating a patient have on the health service.

Furthermore, the economics of health literature is filled with references to characteristics of doctors that set them apart from other workers. This manifests in characteristics such as intrinsic motivation, professionalism, altruism, and multitasking (Arrow, 1963; Ellis & McGuire, 1986; Hölmstrom & Milgrom, 1991; Roland et al., 2011). These suggest that the classical assumptions of labor economics may not be appropriate in a health setting. Although there is a strong theoretical basis for believing that these characteristics of healthcare workers diverge from the classical profit-maximizing worker, the empirical evidence is far from conclusive. Each of these characteristics is explored in more detail and the existing empirical research summarized; the question of how future research can be used to inform optimal incentives to elicit efficient levels of effort from workers is also addressed.

Intrinsic Motivation

Health workers are described as being influenced by intrinsic, nonmonetary, and organizational aspects of their work (Arrow, 1963; McPake, Scott, & Edoka, 2014). Intrinsic motivation involves a shift in focus away from an individual’s response to extrinsic or economic incentives toward internal forms of motivation. Economic theory in general does not make this distinction between whether an employee is responding to extrinsic or intrinsic motivation for either a task or a reward. This is in part due to the fact that it is difficult to distinguish which of the motivators an individual is responding to. As a result, constructing incentives for optimal behavior through more readily available extrinsic motivators proves a less complex task for policymakers (Frey & Jegen, 2001). Several countries have introduced pay-for-performance schemes involving financial incentives to improve quality of care, such as the QOF in the United Kingdom (NHS England, 2016a) and the CAPI in France (Saint-Lary & Sicsic, 2015).

The relevance of making this distinction is that the effectiveness and design of remuneration schemes will have to take into account the importance that individuals place on various forms of motivation, as it will influence responsiveness (McPake et al., 2014). Motivation crowding theory suggests that monetary incentives may crowd out intrinsic motivation. The seminal example is that offering payment for blood donations would reduce voluntary blood donations as the internal justification and respected social values individuals have toward such a task is crowded out by the extrinsic incentive (Titmuss, 1987). The same could be argued for a general practitioner (GP) participating in a pay-for-performance incentive scheme. It could be the case that the reputational effects of accepting large bonuses when physicians feel intrinsically motivated to help patients could result in the opposite effect, as this would indicate a purely monetary relationship to patients (Burgess & Ratto, 2003). Evidence to support this includes increased importance of reputational rewards over time (Allen, Whittaker, Kontopantelis, & Sutton, 2018). In contrast, no effect has been found on GPs of the share of their income linked to performance (Allen, Whittaker, & Sutton, 2017).

The literature on the crowding effect is similarly contradictory, with some evidence that external interventions can foster the intrinsic motivation of healthcare workers (Pedersen, Andersen, Jensen, Waldorff, & Jacobsen, 2018; Qian & He, 2018). It has been found that financial incentives do not affect those who are intrinsically motivated, but for subjects without intrinsic motivation financial incentives are strong. (Lagarde & Blaauw, 2017; Tonin & Vlassopoulos, 2010). Given this, it is important for a policymaker to design remuneration schemes to account for the level of intrinsic motivation in the workforce. Offering strong financial incentives could be required, or could be a waste of resources, or could be harmful if physicians are intrinsically motivated toward their job. The challenge for policymakers is that this information is asymmetric.

Furthermore, what is the empirical evidence that an intrinsically motivated doctor produces better patient outcomes than a doctor motivated by extrinsic, monetary incentives? Brock, Lange, and Leonard (2013) conducted a laboratory experiment to gauge the generosity of clinicians and used this information to examine the correlation between generosity and quality of care in their practices. They found that generous physicians (who give away over half of their original endowment) provided 10% better quality care than those who did not. More studies of this nature are required.


Doctors across different countries and contexts abide by a number of codes of professional conduct. At the forefront of these values are honesty, integrity, the importance of patient welfare, and delivering high-quality care (Roland et al., 2011). These core beliefs can be viewed as the mission of this sector, which come from the underlying motivations of both principal and agent. Missions should be matched between principals and agents in order to achieve organizational efficiency (Besley & Ghatak, 2003). Besley and Ghatak (2005) propose that matching principals and agents on their intrinsic motivation or mission preferences can affect productivity and reduces the need to implement strong incentives. They argue that in sectors with social objectives, such as healthcare, there would be an inadequate level of provision by relying purely on market forces and so it is important to select workers committed to prosocial goals. Laying out clear objectives and goals through professional guidelines can attract workers who align with such values and instill in the preferences of those physicians a prosocial cause or mission.

But to what degree are these professional values actually internalized by workers? And can they be taught? Research has been conducted into professionalism, examining the extent to which workers adhere to the accepted principles of an organization in the health sector. Roland et al. (2011) in a study of doctors in the United Kingdom and the United States find that medical workers generally strongly support the codes of conduct laid out by their professional bodies, but there are contextual differences in how professional goals are portrayed and how far they are supported by workers’ stated values. This is supported by Lombarts et al. (2014), who developed an instrument to measure professionalism and found high levels of professionalism reported by European physicians and nurses overall. Results from China showed positive professional attitudes that are associated with reported behaviors but inconsistency between stated and revealed preferences (Chen, Xu, Zhang, & Fu, 2013). The pattern of strong agreement by physicians with standards of behavior and yet discrepancies in reported behavior is also supported by evidence from Campbell et al. (2007). While 96% of respondents agreed physicians should report incompetent coworkers, 45% of respondents who had come into contact with such coworkers had failed to report them.

Further research into professionalism in the medical workforce should be clear in what values this encompasses, as this will vary across health systems. In addition, research should consider whether professional codes of conduct set out by governing bodies and instilled into workers provide intrinsic motivation for them to perform tasks. Research is also needed in the matching missions approach of Besley and Ghatak (2003, 2005), whereby workers could be selected based on pre-existing values to increase efficiency.


One aspect of behavior of the medical profession often included in definitions of professionalism is altruism. Altruism is typically represented as doctors internalizing the patient’s welfare function in their own utility function. Ellis and McGuire (1986) represented altruism as a physician acting as agent to both the patient and the hospital. They define altruism as the marginal rate of substitution between patient health benefit and hospital profit. In setting optimal contracts, the degree of cost reimbursement required decreases in the level of physician altruism. For physicians who are not altruistic, and care only about profits, full cost reimbursement is recommended to encourage an efficient level of hospital provision. For physicians who place equal weight on hospital and patient benefits, the optimal payment would be to offer a flat payment (Galizzi et al., 2015).

Altruism is also thought to be beneficial in a healthcare setting where both public and private provision of healthcare is offered. Rich patients will receive high-quality treatment from private providers motivated by monetary gains, and poorer patients will be more likely to receive high-quality treatment from altruistic physicians who choose to select into the NHS, as it is where they feel their work will be most valued (Delfgaauw, 2007).

Observational evidence for the altruism of doctors is widespread, including the undertaking of voluntary work in local communities, abroad, or after natural disasters. A 2014 survey of NHS staff found that over 80% of doctors worked unpaid overtime (Rimmer, 2015). There is a large literature on the theoretical optimal design of incentive schemes for altruistic providers (Chalkley & Malcolmson, 1998; Chone & Ma, 2011; Jack, 2005; Makris & Siciliani, 2013); however, empirical analysis is lacking. Godager and Wiesen (2013) used a laboratory experiment to find evidence for physician altruism but with substantial heterogeneity. They thus recommend an optimal payment mechanism whereby physicians are paid according to how altruistic they are.

This is problematic in payment systems that are restricted to paying the same to different care providers. Although paying providers differentially according to their degree of altruism would give the efficient solution, practically, identifying the degree of altruism of every individual in the medical workforce is not easily achievable. Therefore, more empirical evidence into the altruism of physicians is warranted in order to provide policymakers with the relevant information to rectify this allocative inefficiency in contract design and to design contracts that would be suitable for people with different levels of altruism.


With the implementation of pay for performance schemes globally, there is concern over the risk that incentivizing effort for one aspect of performance might result in lower effort in other areas. Hölmstrom and Milgrom’s (1991) model of a multitask agency describes agents who solve multidimensional tasks that may be either substitutes or complements. If tasks are complements, then incentivizing one may result in positive spillovers with the related task. However, if tasks are substitutes, incentivizing one may lead to less focus on the unincentivized dimension.

Multitasking theory has been used to understand the optimal strength with which to enforce incentives within a pay-for-performance scheme. Kaarboe and Siciliani (2011) note that in the context of incentivizing quality, some dimensions of quality are nonverifiable or contractable and cannot be evaluated ex post. When interactions of dimensions of quality could be substitutes or complements, then when is it appropriate to introduce a pay-for-performance scheme and how strong should these incentives be? The impact of a performance scheme is affected by the extent to which the contractible quality element increases or decreases a provider’s marginal utility and how the marginal benefit of noncontractible elements are affected by changes in marginal benefit of contractible elements. The relative benefits of different quality dimensions must be assessed when these are substitutes, whereas high-powered incentives can be used when quality dimensions are complements. Multitasking also theoretically provides incentive for health systems to adopt mixed-payment systems such as partial capitation and fee-for-service to balance quality incentives across services (Eggleston, 2005).

Empirical evidence on multitasking is relatively scant due to the limited availability of data. Analysis of conflicting or harmonizing incentives on tasks performed by physicians requires information on multiple facets of physician behavior. Experimental evidence suggests that physicians respond by substituting effort between quantity and quality due to shifts in payment schemes (Dumont et al., 2008). Other analyses of pay-for-performance schemes have shown that their introduction improved both targeted and nontargeted tasks, without providing clear evidence of multitasking (Sherry, Bauhoff, & Mohanan, 2017; Sutton, Elder, Guthrie, & Watt, 2010). Analysis of the QOF finds substantial improvements for incentivized quality indicators at the expense of small adverse effects on not incentivized aspects of care (Doran et al., 2011). Other studies find limited evidence of positive spillover effects (Kristensen et al., 2014; Mullen, Frank, & Rosenthal, 2010) Existing research into spillover effects on nonincentivized activities largely analyzes incentive schemes ex post, looking for evidence of multitasking behavior. Conclusions from studies such as these are dependent on the specific structures and institutions in place, and further research is needed for more generalizable findings for policymakers.

Payment Systems

Wages in labor markets are decided based on supply, demand, and market forces. In perfectly competitive markets, the wage rate is a direct reflection of the value of the output produced (McPake et al., 2014). Health markets, however, are not perfect. Asymmetric information and health as an experience good means that patients cannot be certain of the quality of the “good” or service they have received until after consumption. Even then they still cannot be sure, due to the random nature of illness. Asymmetric information in healthcare leads to issues such as supplier-induced demand. This is when, due to the imbalance of information between physician and patient, physicians are incentivized to influence demand for their care by placing an inflated emphasis on the supply of their services (Evans, 1974). Consequently, payment schemes in medicine have become more complicated than generally seen in other sectors.

Issues With the Most Popular Forms of Reimbursement Schemes

The three most commonly used forms of payment systems are fee-for-service, capitation, and salary. Each of these systems has different consequences for productivity and costs. A blended payment system, in which elements from each are used in order to alleviate their respective negative incentives, is suggested as a possible solution to this problem (Jones, 2012). However, evidence over the effectiveness of this as a solution or how blended the payment system should be is unclear.

Capitation payments are given based on the number of patients covered, for example, the number of patients registered with a health facility. As the amount of money awarded is fixed for a period of time, there is an incentive with capitation for physicians to reduce costs. This may mean reducing the amount of care, or “cream-skimming” by avoiding higher risk patients in favor of low-risk, less costly patients. However, the knock-on effect of this could mean patients are less likely to want to register with the lower quality GP practices, resulting in less payment provided (Jones, 2012).

With a fee-for-service payment system, physicians are paid separately for each unit of service. There is therefore an incentive for physicians to increase the number of services provided (assuming that the payment received for a service exceeds the cost). However, there is then no incentive to reduce costs if payment for services is reimbursed retrospectively. Increasing the number of services may be beneficial for patient outcomes but may not be cost-effective. More services do not guarantee better quality care and can even be harmful for patients (Lipitz-Snyderman & Bach, 2013), for example, providing too many x-rays or unnecessary invasive procedures.

A salary provides a fixed payment over a given time period. Though this does not provide an incentive to either overprovide services or cut costs, there are no performance incentives. At least capitation may create incentives to compete for patients. As there is no punishment for poor performance, physicians may provide suboptimal levels of effort, which could result in detrimental effects on patients.

How Blended Should Payments Be?

There is consensus on the recommendation that some blend of the different payment methods is needed in order to exploit the benefits and alleviate the problems with each incentive structure, supplemented by pay-for-performance targets (Robinson, 2001). In a simple model examining optimal consumer choice of provider reimbursement and insurance, based on the models of Ellis and McGuire (1986, 1990), Selden (1990) concludes that if capitation can be adjusted so that the risk level of patients is reflected, then a mixture of capitation and fee-for-service/cost-based payment is optimal. By introducing a mix of payments, the idea is to reduce skimping on quality while still providing some incentive for cost control (Ellis & McGuire, 1990; Ma, 1994; Ma & McGuire, 1997).

Robinson (2001) details different ways in which payment systems can be blended: (a) capitation combined with fee-for-service carve-outs for certain services, (b) bundled payments where a fixed amount is provided for a group of services for a certain condition, and (c) fee-for-service payments to provider organizations where savings made on healthcare budgets are shared. But how blended should the payment structure be? Seldon (1990) suggests the mixture reflects the concerns of the government over quality of care. In contexts where there is a shortage of services provided, introducing more of a fee-for-service element to the blended payment may provide a sufficient incentive to stimulate services offered. Where services are overprovided, more of a focus on capitation may incentivize physicians to control the number of services.

Though the theoretical intuition for shifts to mixed payment systems is clear, and most health systems are complex and do not solely adhere to a single form of payment method but use elements of each (Robinson, Shortell, Li, Casalino, & Rundall, 2004), the number of studies of sufficient quality on the response of physician behavior and patient outcomes to mixed payment models is limited. There is some evidence of the shift from fee-for-service to a mixed payment model showing there to be fewer but higher quality services provided (Brosig-Koch, Hennig-Schmidt, Kairies-Schwarz, & Wiesen, 2017; Dumont, Fortin, Jacquemet, & Shearer, 2008; Kralj & Kantarevic, 2013) whereas others find insignificant differences in hospital utilization (Hutchison et al., 1996). Zhang and Sweetman (2018) look at the effect of moving from a fee-for-service system in Canada to a blended payment where uncommon, expensive, and preventative services are protected from underallocation by being remunerated by fee-for-service while selected core services are capitated. They find that patients experience 9% to 14% reduction in services that are capitated and increases of 10% to 22% in fee-for-service services from rostering physicians. Studies that look into the effect of moving from capitation to a mixed payment system show more services are offered (Brosig-Koch et al., 2017; Krasnik et al., 1990).

There are no studies available that provide information regarding the optimal blend of these payment systems. There are clearly difficulties in producing high-quality, externally valid studies that can generalize findings on the most efficient blend of payment systems. The definition of the “blend” will vary greatly between health systems, and there will also be heterogeneity within definitions themselves such as those put forward by Robinson (2001). It is likely that there will be issues concerning causality in estimating the impact of a blended payment method. For example, systems with particularly low-quality or low volume of services offered may strengthen the fee-for-service element of their payment system to encourage physicians to increase services offered. The endogeneity of the design of mixed payment systems makes identification of causal effects on outcomes difficult. Future research on the optimal blend of payments would require clear definitions of the blended payment with particular attention paid to the system in place prior to the introduction of the mixed payment.

Skill Mix and Teams

Skill Mix

Due to rising pressures on expenditure and a need to organize the medical workforce efficiently, substantial attention has been given to the optimal mix of doctors and other healthcare professionals. This is especially important given the labor-intensive nature of health services. There are health workforce shortages globally (Liu et al., 2017). Doctors, in particular primary care doctors, are difficult to recruit (Marchand & Peckham, 2017). Several health systems are planning significant changes to the skill mix of the workers in primary care and looking to introduce more nonmedical roles to work alongside harder-to-recruit GPs (NHS England, 2016b).

“Skill mix” is generally defined as the mix of different professional roles and grades within an organization. It can also describe the range of skills or tasks required by a certain job (Buchan & Dal Poz, 2002). Skill mix change may be required within an organization for various reasons. Enhancing the workforce would allow the extension of roles without the need to be supervised. Substituting or delegating tasks would transfer responsibilities between, for example, GPs and existing or less expensive medical workers such as nurses or prescribing pharmacists. Skill mix change could also be considered for innovative reasons, encouraging new and enhanced care with increased collaboration (Nelson, Martindale, McBride, Checkland, & Hodgson, 2018).

Evaluating skill mix within an economic framework looks at the technical efficiency of the mix of workers. A technically efficient solution occurs where a given level of healthcare services is provided for the lowest cost, or given a set of inputs the output is maximized (Kernick & Scott, 2002). Substituting or delegating tasks between doctors and other medical staff is an appealing solution for policymakers in order to reduce costs while maintaining or improving the quality of care provided. There is a body of evidence that supports the idea that substituting the work of doctors with nurses or other health professionals can deliver the same or better health outcomes (Fulton et al., 2011; Kernick & Scott, 2002, Sibbald, Shen, & McBride, 2004). Having a richer nurse skill mix is found to be associated with lower mortality odds and lower odds of poor-quality care being reported (Aiken et al., 2017). Evidence also shows that countries that have undertaken major skill mix reforms have nurses who are more motivated to undertake new roles and feel they have the opportunity to do so (Köppen et al., 2018). However, many studies of the effects of skill mix are cross-sectional or based on differences between the new and the old workforce. There is a dearth of evidence providing the causal effect of skill mix change, comparing outcomes with the new workforce to a credible counterfactual.

Accepting the benefits of skill mix change, in practice, moving from a state of technical inefficiency to achieve technical efficiency, is not always straightforward. Organizational change is complicated by the fact that skill mix change is applied to pre-existing systems that often reflect historical precedent and problems (Pratt, Gordon, & Plamping, 2005, Freund et al., 2015). External factors such as status, gender, and unwillingness of health workers to change their roles limit the amount of flexibility in the system. Workforce shortages have been reported to be a major hindrance to skill mix change, while medical technology and professional and management support within an organization are reported as being conducive to role changes (Maier et al., 2018).

Contracts must be conducive to this change. For example, in countries such as the United States where there is a prevalence of fee-for-service payments to doctors, this means that there is more monetary benefit of doctors doing the work, and doctors and nurses are in direct competition (Buchan & Calman, 2005). For doctors and nurses to be easily substituted, there must be no friction contractually. If there are transaction costs of substituting the work of doctors and nurses, this will hinder arriving at the efficient allocation. Group-based payment methods, however (capitation, pay-for-performance), encourage a higher proportion of nurses as long as the extra revenue from their services outweighs the cost (Delamaire & Lafortune, 2010).


There is clear agreement that teamwork is necessary and beneficial in a healthcare working environment. Recent years have seen a push toward more integrated, harmonized care, which includes increased coordination between various healthcare providers. New problems with incentives arise in a multiagent setting.

In his seminal paper, Hölmstrom (1982) highlighted the free rider problem created by moral hazard within teams. Moral hazard in teams takes place when there is asymmetric information; output is affected by the effort of each member of the team but is unobservable and cannot be contracted for, and so agents may be tempted to shirk and provide suboptimal levels of effort. Contrary to the single-agent model, it may be the case that moral hazard is a problem even with certain output as input by each individual cannot be observed—only joint output—so cheating is not observable.

Teams can be organized in different ways. One option is to design teams around a patient. This is common in the care of patients with chronic conditions and multimorbidity, with multidisciplinary teams of healthcare workers across different professions coordinating with a designated care plan. However, this can become complex organizationally, and when building a team of healthcare professionals around the care of each individual patient, overlapping teams become highly likely. Furthermore, the same condition will not manifest itself in each patient to require the same treatment, and clear guidelines are not always available in the case of complex conditions. Alternatively, Ratto, Propper, and Burgess (2002) suggest that using existing teams, smaller teams, and teams across professions and hierarchically within an organization are most effective. With smaller teams, each input is a larger contributor to total output, and so free-riding will affect output more. Furthermore, for teams across professions and hierarchical teams within an organization, benefits such as mutual monitoring and cooperation offset potential shirking and professional tensions.

The way teams are organized has an impact on how to reimburse workers to induce optimal effort. The difficulty with setting up contracts in a team-based environment is the problem of incentives. Monetary incentives applied at lower organizational levels, such as department level as opposed to hospital level, have been shown to improve effectiveness (Kristensen et al., 2016). However, incentives placed at too low a level, for example, aimed at the individual, could potentially undermine cooperation within teams (Robinson, 2001). The key to eliciting adequate levels of effort is through the dependency of the rewards. One way to achieve this is to ensure that individual contributions within a team are complements. When individual contributions in a team are complements, the marginal return of the effort of one worker depends on the effort of another. Therefore, moral hazard is avoided (Costa & Dutra, 2018). Another way health workers in teams are incentivized not to shirk is when the outcome of effort is influenced by common uncertainty. Thus, to encourage effort in teams where there are no complementarities in production, rewards should be connected to the input of individuals who experience the same risk (Ratto et al., 2002).

Recruitment, Retention, and Migration

Other than skill mix change, reliance on inward migration of health workers is a potential solution for issues with recruitment and retention. Many countries such as the United Kingdom, the United States, and Canada rely on a high proportion on foreign-born workers (Dumont & Zurn, 2007). The macroeconomic view of migration focuses on differences in wage levels between different geographical areas and their respective labor markets.

Neoclassical microeconomic theory portrays workers as weighing up the expected costs and benefits of migrating and doing so if their expected wage level in the new country is higher (Bauer & Zimmermann, 1999; Massey et al., 1993). The new economics of migration theory challenges the neoclassical focus on individual decision-making and proposes that migration is the result of mutually interdependent actors; families, or households, who are looking to maximize income and minimize risk in the context of other markets as well as the labor market, such as credit or insurance (Massey et al., 1993; Stark, 1991). Thus households do not only evaluate wage differentials but also take into account risk and uncertainty and consider their relative performance and relative deprivation in comparison to other households. In developing countries, there is increased risk in the absence of strong institutions or welfare and insurance systems. This, therefore, raises the incentive for migration from higher risk, developing countries to lower risk, developed countries even if wage differentials are nonexistent (Stark, 2003).

Research into the role of immigration within the healthcare workforce specifically has not received much attention, as generally there are wider economic goals in place by policymakers. With respect to immigration policy, issues specific to healthcare workers are not considered distinctly from these broader aims centered on economic growth (McPake et al., 2014). Antwi and Phillips (2013) find significant elasticities of attrition with respect to wages for potential migrants, but these elasticities are insignificant for other groups. They conclude, therefore, that migrants are the group who respond to differential wage rates and so changes in wage rates will impact retention through the migrant population. Vujicic, Zurn, Diallo, Adams, and Dal Poz (2004) find no relationship between wage differentials and intentions to migrate but do not break down their findings by age and skills.

Many high-income countries have historically been highly dependent on foreign-born healthcare workers and have implemented recruitment policies targeted at overseas healthcare workers on multiple occasions (Birrell, 2004; Organisation for Economic Co-operation and Development [OECD], 2017; Runnels, Labonte, & Packer, 2011; World Health Organization, 2019; Young, Weir, & Buchan, 2010). A recent U.K. study showed that the large proportion of non-UK qualified GPs working in the country work longer hours and are more likely to work in more socioeconomically deprived areas (Esmail, Panagioti, & Kontopantelis, 2017). A U.S. study found Medicare patients treated by international graduates had lower mortality rates compared with patients treated by U.S. graduates, and there were no differences between the two groups in readmission rates (Tsugawa, Jena, Orav, & Jha, 2017).

But reliance on international migration to fill health workforce shortages is not an ideal solution. First, there has been much attention given to the negative impact of recruitment of health workers by higher income countries. The “brain drain” of skills from these countries experiencing high volumes of outward migration can have exacerbating effects on their workforce shortages (Gross et al., 2011; O’Brien & Gostin, 2011). As a result, the Global Code of Practice on the International Recruitment of Health Personal was established in May 2010 by the World Health Assembly to encourage more ethical recruitment of health workers (OECD, 2017).

Reliance on international migration is also a risky solution. Large groups of workers migrating within a short period of time creates concerns for the age structure of the medical workforce, creating pockets of health workers retiring and leaving the workforce around the same time, and worries over how to replace them (Taylor & Esmail, 1999). Movement of international health workers is impacted by other factors that create irregularities in the supply of health workers such as war and civil unrest (Kingma, 2018, p. 63), as well as policy changes that dictate visas and work permits (Esmail et al., 2017). Sudden changes in levels of migrant workers such as those seen after the announcement of departure of the United Kingdom from the European Union should be exploited by future researchers to look at the economic impact of the reduction in migrants and decisions to migrate. Challenges to research are apparent in sourcing adequate data to explore motivations for migrating presented in the new economics of migration other than the wage differential.

External Regulation

Accreditation and Inspection

Accreditation is a form of external quality assessment that compares performance against desired and accepted objective standards. Adherence to these standards is regarded as a signpost of quality and is considered necessary for a safe and effective health service through systematic assessment of the competence of health systems (Lovern, 2000). These standards are developed and implemented by healthcare accreditation agencies. Further, bodies such as the International Society for Quality in Healthcare provide guidance on the development of the standards that agencies produce.

Although compliance with these standards is widely synonymized with attaining and improving quality and is adopted by most health systems (Academic Medical Center Working Group of the Institute for Healthcare Improvement, 2003), there is little robust evidence on their effectiveness. A report by the King’s Fund and the University of Manchester (2018) exploring the impact of the Care Quality Commission found audits to have little effect on quality. This is not only a U.K. phenomenon. Systematic reviews carried out by Greenfield, Pawsey, Hinchcliff, Moldovan, and Braithwaite (2012) and Brubakk, Vist, Bukholm, Barach, and Tjomsland (2015) into healthcare and hospital accreditation, respectively, found limited convincing evidence as to their impacts on clinical outcomes and quality of care. A U.S. study found hospital accreditation by independent organizations is not associated with lower mortality compared to those reviewed through state surveys and only slightly reduced readmission rates (Lam et al., 2018). Furthermore, Ho et al. (2014) identify potential unintended negative side effects of hospital accreditation in a qualitative study of its effects on medical students, such as reduced clinical learning opportunities, increased nonclinical workload, and violation of professional integrity in periods preceding and during the accreditation process. In the United Kingdom, revalidation is a form of external regulation introduced by the General Medical Council (GMC) in 2012. The GMC reassesses whether a doctor is fit to practice and, if so, confirms the continuation of his or her license (NHS England, 2019). Gutacker et al. (2019) find that revalidation appears to have resulted in higher numbers of doctors leaving clinical practice, with those ceasing clinical practice not appearing to have provided lower quality care.

External inspections are used in health systems to assess adherence to and reinforce evidence-based standards, assuming that the process is carried out by an organization external to the one being reviewed. Again, despite external inspection processes being widely used, there is little evidence regarding the benefits in terms of quality of care and patient outcomes and therefore little information regarding optimal design of inspection processes. A systematic review of the effectiveness of external inspection systems by Flodgren, Pomey, Taber, and Eccles (2011) identified only two studies that meet the inclusion criteria. Questions are also raised over the reliability and validity of the inspectors. Boyd, Addicott, Robertson,Ross, and Walshe (2017) find that having inspectors in groups rather than individual inspectors alleviates some of these concerns and produces more reliable assessments.

Why is there such a gap in convincing evidence for the impact of accreditation globally, and what are the challenges to research? First, intervention studies are hindered due to the heterogeneous and multifaceted nature of implementing accreditation. There is great variation in how interventions are implemented, which makes it difficult to gauge the overarching impact of accreditation across different contexts (Shepperd et al., 2009). Inability to properly control for unobserved confounding factors in observational studies will also impact the validity of these studies and the ability to reliably comment on the true effect of accreditation. Furthermore, in assessing the value of accreditation from a policy perspective, thought must be given to alternative methods of quality improvement that could take place in its stead (Cross, 2003; Øvretveit, 2009) However, an absence of reliable evidence does not necessarily imply absence of any positive effects of accreditation and inspections but should encourage further research with stronger study designs. There is a gap in the literature of studies analyzing best practice for the development of standards, the processes involved, and which types of standards are most likely to have the greatest impact (Greenfield et al., 2012). The system must develop from learned experience to a more reliable, evidence-based method of developing and creating standards.

Where Is the Best Level to Implement Interventions to Regulate Care Quality?

When regulating quality in healthcare, policymakers must consider the best level at which to target interventions. Previous work looking into how to target pay for performance schemes finds that financial incentives for quality improvement targeted at the lower organizational level (department as opposed to hospital) are more effective in encouraging performance (Kristensen et al., 2016). There are calls to make the system of medical revaluation less “one size fits all” (Walshe et al., 2017). This means that revalidation must be more responsive to individual and organizational contexts and allow appropriate variation in applying policy. Again, systems that are put into place to check and regulate quality must make sense at a more granular level if they are to ensure smooth running of a system so heavily reliant on its workforce.

Gutacker et al. (2018) find more variation in clinical outcomes is associated with individual doctors rather than hospitals. This would all suggest that interventions that regulate quality would be better targeted at doctors as opposed to larger organizations. While the authors found doctor variation to surpass hospital variation by a factor of 1.2 or more, doctors and organizations only attributed at most 11% of variation in case mix adjusted performance indicators. Most of the variation is explained by random chance and unobserved patient factors. The caveat to targeting interventions for performance specifically at doctors as opposed to a wider level is that there is not generally enough data and number of cases per doctor to be able to robustly gauge individual performance. This is supported by other studies that find that using individual-level indicators may not provide trustworthy information on true performance (Dimick, Staiger, & Birkmeyer, 2010; Eijkenaar & van Vliet, 2013). Interventions made at a lower level must be reliably done with enough evidence on doctor performance to observe their “effort” and skill and not outcomes due to chance or unobserved patient factors.


Contracts and the settings in which healthcare professionals work are complex, with multiple conflicting factors to consider. Often the efficient solution is hindered by a bias toward entrenched systems in place and political agendas. As many health systems implement payment schemes that include a mix of fee-for-service, capitation, and salary, there is a need to explore not only how effective mixed payments are but also what blend proves most effective. It is also important for policymakers to account for heterogeneity in individuals when designing contracts. Future research is needed not only into how the distinct characteristics of doctors might impact extrinsic monetary incentives already in place but also how best to utilize intrinsic motivators to motivate the medical workforce. As well as at the individual level, there needs to be more research on how to implement successful contracts and incentives in a team-based environment and what skill mix within those teams is the most efficient and cost-effective. With the medical workforce in many countries so heavily reliant on migrants, the existing research on the impact of wage differentials on migration should be expanded to explore other motivators such as risk and relative deprivation. Mechanisms used to externally regulate health systems must be responsive to individual and organizational contexts.

Further Reading

Buchan, J., & Dal Poz, M. R. (2002). Skill mix in the healthcare workforce: Reviewing the evidence. Bulletin of the World Health Organization, 80, 575–580.Find this resource:

Chalkley, M. (2018, August 28). Incentives and performance of health care professionals. In J. H. Hamilton (Ed.), Oxford Research Encyclopedia of Economics and Finance. Oxford, U.K.: Oxford University Press.Find this resource:

Ellis, R. P., & McGuire, T. G. (1990). Optimal payment systems for health services. Journal of Health Economics, 9(4), 375–396.Find this resource:

Frey, B. S., & Jegen, R. (2001). Motivation crowding theory. Journal of Economic Surveys, 15(5), 589–611.Find this resource:

Greenfield, D., Pawsey, M., Hinchcliff, R., Moldovan, M., & Braithwaite, J. (2012). The standard of healthcare accreditation standards: A review of empirical research underpinning their development and impact. BMC Health Services Research, 12(1), 329.Find this resource:

Jones, A. M. (Ed.). (2012). The Elgar companion to health economics. Cheltenham, U.K.: Edward Elgar.Find this resource:

Kaarboe, O., & Siciliani, L. (2011). Multi-tasking, quality and pay for performance. Health Economics, 20(2), 225–238.Find this resource:

McPake, B., Scott, A., & Edoka, I. (2014). Analyzing markets for health workers: Insights from labor and health economics. Washington, DC: World Bank.Find this resource:

Ratto, M., Propper, C., & Burgess, S. (2002). Using financial incentives to promote teamwork in healthcare. Journal of Health Services Research & Policy, 7(2), 69–70.Find this resource:

Robinson, J. C. (2001). Theory and practice in the design of physician payment incentives. The Milbank Quarterly, 79(2), 149–177.Find this resource:

Roland, M., Rao, S. R., Sibbald, B., Hann, M., Harrison, S., Walter, A., . . . Campbell, E. G. (2011). Professional values and reported behaviours of doctors in the USA and UK: Quantitative survey. BMJ Quality & Safety, 20, 512–521.Find this resource:


Academic Medical Center Working Group of the Institute for Healthcare Improvement. (2003). The imperative for quality: A call for action to medical schools and teaching hospitals. Academic Medicine, 78(11), 1085–1089.Find this resource:

Aiken, L. H., Sloane, D., Griffiths, P., Rafferty, A. M., Bruyneel, L., McHugh, M., . . . Sermeus, W. (2017). Nursing skill mix in European hospitals: Cross-sectional study of the association with mortality, patient ratings, and quality of care. BMJ Quality & Safety, 26(7), 559–568.Find this resource:

Allen, T., Whittaker, W., Kontopantelis, E., & Sutton, M. (2018). Influence of financial and reputational incentives on primary care performance: a longitudinal study. Br J Gen Pract, 68(677), e811–e818.Find this resource:

Allen, T., Whittaker, W., & Sutton, M. (2017). Does the proportion of pay linked to performance affect the job satisfaction of general practitioners? Social Science & Medicine, 173, 9–17.Find this resource:

Antonazzo, E., Scott, A., Skatun, D., & Elliott, R. F. (2003). The labour market for nursing: A review of the labour supply literature. Health Economics, 12(6), 465–478.Find this resource:

Antwi, J., & Phillips, D. C. (2013). Wages and health worker retention: Evidence from public sector wage reforms in Ghana. Journal of Development Economics, 102, 101–115.Find this resource:

Arrow, K. J. (1963). Uncertainty and the welfare economics of medical care. The American Economic Review, 53(5), 941–973.Find this resource:

Baltagi, B. H., Bratberg, E., & Holmås, T. H. (2005). A panel data study of physicians’ labor supply: The case of Norway. Health Economics, 14(10), 1035–1045.Find this resource:

Bauer, T. K., & Zimmermann, K. F. (1999). Assessment of possible migration pressure and its labour market impact following EU enlargement to central and eastern Europe (Vol. 3). Bonn, Germany: IZA.Find this resource:

Besley, T., & Ghatak, M. (2003). Incentives, choice, and accountability in the provision of public services. Oxford Review of Economic Policy, 19(2), 235–249.Find this resource:

Besley, T., & Ghatak, M. (2005). Competition and incentives with motivated agents. The American Economic Review, 95(3), 616–636.Find this resource:

Birrell, R. J. (2004). Australian policy on overseas-trained doctors. Medical Journal of Australia, 181(11–12), 635–639.Find this resource:

Blomqvist, Å. (1991). The doctor as double agent: Information asymmetry, health insurance, and medical care. Journal of Health Economics, 10(4), 411–432.Find this resource:

Bolton, P., & Dewatripont, M. (2005). Contract theory. MIT press, edition 1, Vol. 1.Find this resource:

Boyd, A., Addicott, R., Robertson, R., Ross, S., & Walshe, K. (2017). Are inspectors’ assessments reliable? Ratings of NHS acute hospital trust services in England. Journal of Health Services Research & Policy, 22(1), 28–36.Find this resource:

Brock, M. J., Lange, A., & Leonard, K. L. (2013). Generosity norms and intrinsic motivation in healthcare provision: Evidence from the laboratory and field. Working Paper 147. London, U.K.: European Bank for Reconstruction and Development.Find this resource:

Brosig-Koch, J., Hennig-Schmidt, H., Kairies-Schwarz, N., & Wiesen, D. (2017). The effects of introducing mixed payment systems for physicians: Experimental evidence. Health Economics, 26(2), 243–262.Find this resource:

Brubakk, K., Vist, G. E., Bukholm, G., Barach, P., & Tjomsland, O. (2015). A systematic review of hospital accreditation: The challenges of measuring complex intervention effects. BMC Health Services Research, 15(1), 280.Find this resource:

Buchan, J., & Calman, L. (2005). Skill-mix and policy change in the health workforce: Nurses in advanced roles. OECD Health Working Paper No. 17. Paris, France: OECD Publishing.Find this resource:

Buchan, J., & Dal Poz, M. R. (2002). Skill mix in the healthcare workforce: Reviewing the evidence. Bulletin of the World Health Organization, 80, 575–580.Find this resource:

Burgess, S., & Ratto, M. (2003). The role of incentives in the public sector: Issues and evidence. Oxford Review of Economic Policy, 19(2), 285–300.Find this resource:

Campbell, E. G., Regan, S., Gruen, R. L., Ferris, T. G., Rao, S. R., Cleary, P. D., & Blumenthal, D. (2007). Professionalism in medicine: Results of a national survey of physicians. Annals of Internal Medicine, 147(11), 795–802.Find this resource:

Chalkley, M., & Malcomson, J. M. (1998). Contracting for health services when patient demand does not reflect quality. Journal of Health Economics, 17(1), 1–19.Find this resource:

Chen, J., Xu, J., Zhang, C., & Fu, X. (2013). Medical professionalism among clinical physicians in two tertiary hospitals, China. Social Science & Medicine, 96, 290–296.Find this resource:

Choné, P., & Ma, C. T. A. (2011). Optimal healthcare contract under physician agency. Annals of Economics and Statistics/Annales d’Économie et de Statistique, 101–102, 229–256.Find this resource:

Costa, F. J., & Dutra, J. (2018). Effort complementarity and team size, an experimental analysis of moral hazard in teams. Economics Bulletin, 38(1), 20–29.Find this resource:

Cross, M. (2003). Money pit: Is accreditation always worth the cost? Managed Care, 12(7), 26.Find this resource:

Delamaire, M. L., & Lafortune, G. (2010). Nurses in advanced roles. OECD Health Working Paper No. 54. Paris, France: OECD Publishing.Find this resource:

Delfgaauw, J. (2007). Dedicated doctors: Public and private provision of healthcare with altruistic physicians. Tinbergen Institute Discussion Paper No. 2007-010/1. Rotterdam, The Netherlands: Erasmus University.Find this resource:

Devlin, R. A., & Sarma, S. (2008). Do physician remuneration schemes matter? The case of Canadian family physicians. Journal of Health Economics, 27(5), 1168–1181.Find this resource:

Dimick, J. B., Staiger, D. O., & Birkmeyer, J. D. (2010). Ranking hospitals on surgical mortality: The importance of reliability adjustment. Health Services Research, 45(6), 1614–1629.Find this resource:

Dixon-Woods, M., Yeung, K., & Bosk, C. L. (2011). Why is UK medicine no longer a self-regulating profession? The role of scandals involving “bad apple” doctors. Social Science & Medicine, 73(10), 1452–1459.Find this resource:

Doran, T., Kontopantelis, E., Valderas, J. M., Campbell, S., Roland, M., Salisbury, C., & Reeves, D. (2011). Effect of financial incentives on incentivised and non-incentivised clinical activities: longitudinal analysis of data from the UK Quality and Outcomes Framework. Bmj, 342, d3590.Find this resource:

Dumont, E., Fortin, B., Jacquemet, N., & Shearer, B. (2008). Physicians’ multitasking and incentives: Empirical evidence from a natural experiment. Journal of Health Economics, 27(6), 1436–1450.Find this resource:

Dumont, J. C., & Zurn, P. (2007). Immigrant health workers in OECD countries in the broader context of highly skilled migration. International Migration Outlook, 2007, 162–228.Find this resource:

Eggleston, K. (2005). Multitasking and mixed systems for provider payment. Journal of health economics, 24(1), 211–223.Find this resource:

Eijkenaar, F., Emmert, M., Scheppach, M., & Schöffski, O. (2013). Effects of pay for performance in healthcare: A systematic review of systematic reviews. Health Policy, 110(2–3), 115–130.Find this resource:

Eijkenaar, F., & van Vliet, R. C. (2013). Profiling individual physicians using administrative data from a single insurer: Variance components, reliability, and implications for performance improvement efforts. Medical Care, 51(8), 731–739.Find this resource:

Elliott, R. F., Ma, A., Scott, A., Bell, D., & Roberts, E. (2007). Geographically differentiated pay in the labour market for nurses. Journal of Health Economics, 26, 190–212.Find this resource:

Ellis, R. P., & McGuire, T. G. (1986). Provider behavior under prospective reimbursement: Cost sharing and supply. Journal of Health Economics, 5(2), 129–151.Find this resource:

Ellis, R. P., & McGuire, T. G. (1990). Optimal payment systems for health services. Journal of Health Economics, 9(4), 375–396.Find this resource:

Esmail, A., Panagioti, M., & Kontopantelis, E. (2017). The potential impact of Brexit and immigration policies on the GP workforce in England: A cross-sectional observational study of GP qualification region and the characteristics of the areas and population they served in September 2016. BMC Medicine, 15(1), 191.Find this resource:

Evans, R. G. (1974). Supplier-induced demand: Some empirical evidence and implications. In H. H. Jaszi (Ed.), The economics of health and medical care (pp. 162–173). London, U.K.: Palgrave Macmillan.Find this resource:

Flodgren, G., Eccles, M. P., Shepperd, S., Scott, A., Parmelli, E., & Beyer, F. R. (2011). An overview of reviews evaluating the effectiveness of financial incentives in changing healthcare professional behaviours and patient outcomes. Cochrane Database of Systematic Reviews, 7, CD009255.Find this resource:

Flodgren, G., Pomey, M. P., Taber, S. A., & Eccles, M. P. (2011). Effectiveness of external inspection of compliance with standards in improving healthcare organisation behaviour, healthcare professional behaviour or patient outcomes. Cochrane Database of Systematic Reviews, 11, CD008992.Find this resource:

Freund, T., Everett, C., Griffiths, P., Hudon, C., Naccarella, L., & Laurant, M. (2015). Skill mix, roles and remuneration in the primary care workforce: Who are the healthcare professionals in the primary care teams across the world? International Journal of Nursing Studies, 52(3), 727–743.Find this resource:

Frey, B. S., & Jegen, R. (2001). Motivation crowding theory. Journal of Economic Surveys, 15(5), 589–611.Find this resource:

Fulton, B. D., Scheffler, R. M., Sparkes, S. P., Auh, E. Y., Vujicic, M., & Soucat A. (2011). Health workforce skill mix and task shifting in low income countries: A review of recent evidence. Human Resources for Health, 9(1), 1.Find this resource:

Galizzi, M. M., Tammi, T., Godager, G., Linnosmaa, I., & Wiesen, D. (2015). Provider altruism in health economics.Find this resource:

Godager, G., & Wiesen, D. (2013). Profit or patients’ health benefit? Exploring the heterogeneity in physician altruism. Journal of Health Economics, 32(6), 1105–1116.Find this resource:

Gosden, T., Forland, F., Kristiansen, I. S., Sutton, M., Leese, B., Giuffrida, A., . . . Pedersen, L. (2000). Capitation, salary, fee-for-service and mixed systems of payment: Effects on the behaviour of primary care physicians. Cochrane Database of Systematic Reviews, 3(3), CD002215.Find this resource:

Greene, J. (2013). An examination of pay-for-performance in general practice in Australia. Health Services Research, 48(4), 1415–1432.Find this resource:

Greenfield, D., Pawsey, M., Hinchcliff, R., Moldovan, M., & Braithwaite, J. (2012). The standard of healthcare accreditation standards: A review of empirical research underpinning their development and impact. BMC Health Services Research, 12(1), 329.Find this resource:

Gross, J. M., Rogers, M. F., Teplinskiy, I., Oywer, E., Wambua, D., Kamenju, A., . . . Kiriinya, R. (2011). The impact of out-migration on the nursing workforce in Kenya. Health Services Research, 46(4), 1300–1318.Find this resource:

Gutacker, N., Bloor, K., Bojke, C., Archer, J., & Walshe, K. (2019). Does regulation increase the rate at which doctors leave practice? Analysis of routine hospital data in the English NHS following the introduction of medical revalidation. BMC Medicine, 17(1), 33.Find this resource:

Gutacker, N., Bloor, K., Bojke, C., & Walshe, K. (2018). Should interventions to reduce variation in care quality target doctors or hospitals? Health Policy, 122, 660–666.Find this resource:

Healy, J., & Braithwaite, J. (2006). Designing safer healthcare through responsive regulation. Medical Journal of Australia, 184(10), S56.Find this resource:

Ho, M. J., Chang, H. H., Chiu, Y. T., & Norris, J. L. (2014). Effects of hospital accreditation on medical students: A national qualitative study in Taiwan. Academic Medicine, 89(11), 1533–1539.Find this resource:

Hölmstrom, B. (1979). Moral hazard and observability. The Bell Journal of Economics, 10(1), 74–91.Find this resource:

Hölmstrom, B. (1982). Moral hazard in teams. The Bell Journal of Economics, 13(2), 324–340.Find this resource:

Hölmstrom, B., & Milgrom, P. (1991). Multitask principal-agent analyses: Incentive contracts. Asset Ownership and Job De-sign, 7.Find this resource:

Hutchison, B., Birch, S., Hurley, J., Lomas, J., & Stratford-Devai, F. (1996). Do physician-payment mechanisms affect hospital utilization? A study of health service organizations in Ontario. CMAJ: Canadian Medical Association Journal, 154(5), 653.Find this resource:

Jack, W. (2005). Purchasing healthcare services from providers with unknown altruism. Journal of Health Economics, 24(1), 73–93.Find this resource:

Jones, A. M. (Ed.). (2012). The Elgar companion to health economics. Cheltenham, U.K.: Edward Elgar.Find this resource:

Kaarboe, O., & Siciliani, L. (2011). Multi-tasking, quality and pay for performance. Health Economics, 20(2), 225–238.Find this resource:

Kamau, C. (2016). Vulnerability of emergency surgery to the working conditions of new doctors. The Bulletin of the Royal College of Surgeons of England, 98(8), 354–357.Find this resource:

Kernick, D., & Scott, A. (2002). Economic approaches to doctor/nurse skill mix: Problems, pitfalls, and partial solutions. British Journal of General Practice, 52(474), 42–46.Find this resource:

Kingma, M. (2018). Nurses on the move: Migration and the global healthcare economy. Ithaca, NY: Cornell University Press.Find this resource:

Klarman, H. (1963). The distinctive economic characteristics of health services. Journal of Health and Human Behavior, 4(1), 44–49.Find this resource:

Köppen, J., Maier, C. B., Busse, R., Bond, C., Elliott, R., Bruhn, H., . . . & Svobodová, H. (2018). What are the motivating and hindering factors for health professionals to undertake new roles in hospitals? A study among physicians, nurses and managers looking at breast cancer and acute myocardial infarction care in nine countries. Health Policy, 122, 1118–1125.Find this resource:

Kralj, B., & Kantarevic, J. (2013). Quality and quantity in primary care mixed-payment models: Evidence from family health organizations in Ontario. Canadian Journal of Economics/Revue canadienne d’économique, 46(1), 208–238.Find this resource:

Krasnik, A., Groenewegen, P. P., Pedersen, P. A., von Scholten, P., Mooney, G., Gottschau, A., . . . Damsgaard, M. T. (1990). Changing remuneration systems: Effects on activity in general practice. BMJ, 300(6741), 1698–1701.Find this resource:

Kristensen, S. R., Bech, M., & Lauridsen, J. T. (2016). Who to pay for performance? The choice of organisational level for hospital performance incentives. The European Journal of Health Economics, 17(4), 435–442.Find this resource:

Kristensen, S. R., Meacock, R., Turner, A. J., Boaden, R., McDonald, R., Roland, M., & Sutton, M. (2014). Long-term effect of hospital pay for performance on mortality in England. The New England Journal of Medicine, 371(6), 540–548.Find this resource:

Lagarde, M., & Blaauw, D. (2017). Physicians’ responses to financial and social incentives: A medically framed real effort experiment. Social Science & Medicine, 179, 147–159.Find this resource:

Lipitz-Snyderman, A., & Bach, P. B. (2013). Overuse of healthcare services: When less is more . . . more or less. JAMA Internal Medicine, 173(14), 1277–1278.Find this resource:

Lam, M. B., Figueroa, J. F., Feyman, Y., Reimold, K. E., Orav, E. J., & Jha, A. K. (2018). Association between patient outcomes and accreditation in US hospitals: Observational study. BMJ, 363, k4011.Find this resource:

Langdown, C., & Peckham, S. (2013). The use of financial incentives to help improve health outcomes: Is the quality and outcomes framework fit for purpose? A systematic review. Journal of Public Health, 36(2), 251–258.Find this resource:

Lombarts, K. M., Plochg, T., Thompson, C. A., Arah, O. A., & DUQuE Project Consortium. (2014). Measuring professionalism in medicine and nursing: Results of a European survey. PLoS One, 9(5), e97069.Find this resource:

Lovern, E. (2000). Accreditation gains attention. Modern Healthcare, 30(47), 46.Find this resource:

Liu, J. X., Goryakin, Y., Maeda, A., Bruckner, T., & Scheffler, R. (2017). Global health workforce labor market projections for 2030. Human Resources for Health, 15(1), 11.Find this resource:

Ma, C. T. A. (1994). Healthcare payment systems: Cost and quality incentives. Journal of Economics & Management Strategy, 3(1), 93–112.Find this resource:

Ma, C. T. A., & McGuire, T. G. (1997). Optimal health insurance and provider payment. The American Economic Review, 87, 685–704.Find this resource:

Maier, C. B., Köppen, J., & Busse, R. (2018). Task shifting between physicians and nurses in acute care hospitals: Cross-sectional study in nine countries. Human Resources for Health, 16(1), 24.Find this resource:

Makris, M., & Siciliani, L. (2013). Optimal incentive schemes for altruistic providers. Journal of Public Economic Theory, 15(5), 675–699.Find this resource:

Marchand, C., & Peckham, S. (2017). Addressing the crisis of GP recruitment and retention: A systematic review. British Journal of General Practice, 67(657), e227–e237.Find this resource:

Massey, D. S., Arango, J., Hugo, G., Kouaouci, A., Pellegrino, A., & Taylor, J. E. (1993). Theories of international migration: A review and appraisal. Population and Development Review, 19, 431–466.Find this resource:

McPake, B., Scott, A., & Edoka, I. (2014). Analyzing markets for health workers: Insights from labor and health economics. Washington, DC: World Bank.Find this resource:

Mendelson, A., Kondo, K., Damberg, C., Low, A., Motúapuaka, M., Freeman, M. & Kansagara, D. (2017). The effects of pay-for-performance programs on health, healthcare use, and processes of care: A systematic review. Annals of Internal Medicine, 166(5), 341–353.Find this resource:

Moreno-Serra, R., & Wagstaff, A. (2010). System-wide impacts of hospital payment reforms: Evidence from central and eastern Europe and central Asia. Journal of Health Economics, 29(4), 585–602.Find this resource:

Mullen, K. J., Frank, R. G., & Rosenthal, M. B. (2010). Can you get what you pay for? Pay-for-performance and the quality of healthcare providers. The Rand Journal of Economics, 41(1), 64–91.Find this resource:

Nelson, P., Martindale, A. M., McBride, A., Checkland, K., & Hodgson, D. (2018). Skill-mix change and the general practice workforce challenge. British Journal of General Practice, 68, 66–67.Find this resource:

NHS England. (2016a). 2016/17 General Medical Services (GMS) Contract Quality and Outcomes Framework (QOF) Guidance for GMS contract 2016/17. Leeds, U.K.: Author.Find this resource:

NHS England (2016b). General practice forward view. Leeds, U.K.: Author.Find this resource:

NHS England. (2019). What is revalidation? Leeds, U.K.: Author.Find this resource:

Nuffield Trust. (2017). The NHS workforce in numbers. London, U.K.: Author.Find this resource:

O’Brien, P., & Gostin, L. O. (2011). Health worker shortages and global justice. Millbank Memorial Fund Report. Global Health Workforce Alliance.Find this resource:

Organisation for Economic Co-operation and Development. (2017). Health at a glance 2017: OECD indicators. Paris, France: OECD Publishing.Find this resource:

Øvretveit, J. (2009). Does improving quality save money? A review of evidence of which improvements to quality reduce costs to health service providers. London, U.K.: The Health Foundation.Find this resource:

Pedersen, L. B., Andersen, M. K. K., Jensen, U. T., Waldorff, F. B., & Jacobsen, C. B. (2018). Can external interventions crowd in intrinsic motivation? A cluster randomised field experiment on mandatory accreditation of general practice in Denmark. Social Science & Medicine, 211, 224–233.Find this resource:

Pratt, J., Gordon, P., & Plamping, D. (2005). Working whole systems: Putting theory into practice in organisations. Oxford, U.K.: Radcliffe.Find this resource:

Qian, J., & He, A. J. (2018). The bonus scheme, motivation crowding-out and quality of the doctor-patient encounters in Chinese public hospitals. Public Organization Review, 18(2), 143–158.Find this resource:

Ratto, M., Propper, C., & Burgess, S. (2002). Using financial incentives to promote teamwork in healthcare. Journal of Health Services Research & Policy, 7(2), 69–70.Find this resource:

Rimmer, A. (2015). Over 80% of doctors work unpaid overtime, NHS survey shows. BMJ, 2015, 350.Find this resource:

Robinson, J. C. (2001). Theory and practice in the design of physician payment incentives. The Milbank Quarterly, 79(2), 149–177.Find this resource:

Robinson, J. C., Shortell, S. M., Li, R., Casalino, L. P., & Rundall, T. (2004). The alignment and blending of payment incentives within physician organizations. Health Services Research, 39(5), 1589–1606.Find this resource:

Roland, M., Rao, S. R., Sibbald, B., Hann, M., Harrison, S., Walter, A., . . . Campbell, E. G. (2011). Professional values and reported behaviours of doctors in the USA and UK: Quantitative survey. BMJ Quality & Safety, 20, 512–521.Find this resource:

Runnels, V., Labonté, R., & Packer, C. (2011). Reflections on the ethics of recruiting foreign-trained human resources for health. Human Resources for Health, 9(1), 2.Find this resource:

Sæther, E. M. (2005). Physicians’ labour supply: The wage impact on hours and practice combinations. Labour, 19(4), 673–703.Find this resource:

Saint-Lary, O., & Sicsic, J. (2015). Impact of a pay for performance programme on French GPs’ consultation length. Health Policy, 119(4), 417–426.Find this resource:

Scott, A., Sivey, P., Ait Ouakrim, D., Willenberg, L., Naccarella, L., & Furler, J. (2011). The effect of financial incentives on the quality of healthcare provided by primary care physicians. Cochrane Database of Systematic Reviews, 9, CD008451.Find this resource:

Selden, T. M. (1990). A model of capitation. Journal of Health Economics, 9(4), 397–409.Find this resource:

Shepperd, S., Lewin, S., Straus, S., Clarke, M., Eccles, M. P., Fitzpatrick, R., . . . Sheikh, A. (2009). Can we systematically review studies that evaluate complex interventions? PLoS Medicine, 6(8), e1000086.Find this resource:

Sherry, T. B., Bauhoff, S., & Mohanan, M. (2017). Multitasking and heterogeneous treatment effects in pay-for-performance in healthcare: Evidence from Rwanda. American Journal of Health Economics, 3(2), 192–226.Find this resource:

Shields, M. A. (2004). Addressing nurse shortages: What can policy makers learn from the econometric evidence on nurse labour supply? The Economic Journal, 114(499), F464–F498.Find this resource:

Sibbald, B., Shen, J., & McBride, A. (2004). Changing the skill-mix of the healthcare workforce. Journal of Health Services Research & Policy, 9(Suppl. 1), 28–38.Find this resource:

Stark, O. (1991). The migration of labor. Oxford, U.K.: Blackwell.Find this resource:

Stark, O. (2003). Tales of migration without wage differentials: Individual, family, and community contexts. Discussion Paper 18743. Bonn, Germany: University of Bonn.Find this resource:

Sutton, M., Elder, R., Guthrie, B., & Watt, G. C. M. (2010). Record rewards: The effects of targeted quality incentives on the recording of risk factors by primary care providers. Health Economics, 19(1), 1–13.Find this resource:

Taylor, D. H., Jr., & Esmail, A. (1999). Retrospective analysis of census data on general practitioners who qualified in South Asia: who will replace them as they retire?. Bmj, 318(7179), 306–310.Find this resource:

Titmuss, R. M. (1987). Developing social policy in conditions of rapid change: The role of social welfare. In Brian Abel-Smith & Kay Titmuss (Eds.), The Philosophy of Welfare: Selected Writings of Richard M. Titmuss (pp. 254–268). London: Allen and Unwin. (Originally published in 1972.)Find this resource:

Tonin, M., & Vlassopoulos, M. (2010). Disentangling the sources of pro-socially motivated effort: A field experiment. Journal of Public Economics, 94(11–12), 1086–1092.Find this resource:

Tsugawa, Y., Jena, A. B., Orav, E. J., & Jha, A. K. (2017). Quality of care delivered by general internists in US hospitals who graduated from foreign versus US medical schools: Observational study. BMJ, 356, j273.Find this resource:

Vujicic, M., Zurn, P., Diallo, K., Adams, O., & Dal Poz, M. R. (2004). The role of wages in the migration of healthcare professionals from developing countries. Human Resources for Health, 2(1), 3.Find this resource:

Walshe, K., Boyd, A., Bryce, M., Luscombe, K., Tazzyman, A., Tredinnick-Rowe, J., & Archer, J. (2017). Implementing medical revalidation in the United Kingdom: Findings about organisational changes and impacts from a survey of Responsible Officers. Journal of the Royal Society of Medicine, 110(1), 23–30.Find this resource:

World Health Organization. (2019). Health workforce—migration. Geneva, Switzerland: Author.Find this resource:

Wubulihasimu, P., Brouwer, W., & Van Baal, P. (2016). The impact of hospital payment schemes on healthcare and mortality: Evidence from hospital payment reforms in OECD countries. Health Economics, 25(8), 1005–1019.Find this resource:

Young, R., Weir, H., & Buchan, J. (2010). Health professional mobility in Europe and the UK: A scoping study of issues and evidence. London, U.K.: National Coordinating Centre for the Service Delivery and Organisation.Find this resource:

Zhang, X., & Sweetman, A. (2018). Blended capitation and incentives: Fee codes inside and outside the capitated basket. Journal of Health Economics, 60, 16–29.Find this resource: