Using financing to strengthen the health workforce: What has worked

and why?

Barbara McPake1 and Ijeoma Edoka1 1 Institute for International Health and Development, Queen

Margaret University, Edinburgh

1st September, 2013

Abstract

To achieve universal access to health care, a range of health financing reforms including user fee reforms and health insurance schemes have been implemented across different countries. While the focus of much research and discussions on universal health coverage has been on the impact of health financing reforms on population coverage, health service utilization and out-of-pocket payments, the implications for human resources for health have often been overlooked. Shortages and

1 Queen Margaret University, Queen Margaret Drive, Musselburgh, Edinburgh EH21 6UU

geographical imbalances in the distribution of skilled health workers persist in many LMICs, posing a threat to achieving universal access to health care. This paper highlights the implications of health financing reforms for the distribution of financial resources as well as their unintended negative consequences on geographical distribution of the health workforce.

Introduction

Over the past decade, there has been a growing momentum towards achieving universal health coverage (UHC) in low and middle income countries (LMICs). With this aim, a range of health financing reforms including user fee reforms, tax-based funding and health insurance schemes, have been designed and implemented across different countries with varying degrees of success. The main objectives of these reforms have been to increase efficiency and equity in the utilization of health care services by widening population coverage, particularly to the poor and vulnerable while offering financial protection from unexpected out-of–pocket payments. The focus of much research and discussion has been on the impact of health financing reforms on population coverage, health service utilization and out-of-pocket payments. The implications for human resources for health (HRH) have often been overlooked. Although financial barriers represent an important barrier to universal access to health care services, availability of an appropriate mix of the health workforce is equally fundamental given that the health workforce is a crucial component of the health care system and an important determinant of population health. However, shortage of skilled health workers and geographical imbalances in the distribution of skilled workers persist in many LMICs, posing an important threat to achieving universal access to health care services.

Several LMICs fall short of the Joint Learning Initiative (JLI)-WHO benchmark of 2.28 health workers (doctors, nurses and midwives) per 1,000 population (World Health Organization, 2006). For example, 6 out of the 11 countries in South-East Asia experience shortages in health

1

workforce (World Health Organization, 2006). National levels or averages often mask geographical imbalances that exist even amongst countries that are not classified as experiencing critical shortages. For example, Thailand in 2010 reported a national level of 2.55 doctors and nurses/midwives per 1,000 population (World Health Organization, 2010). However, the density of doctors and nurses/midwives in Bangkok, the capital, was 7 times and 2 times higher, respectively, than the density in the Northeast, the poorest region. In Timor-Leste, 64% of the doctors are concentrated in urban areas while 34% are concentrated in rural areas (World Health Organization, 2011). In Indonesia in 2006, 50% of health centres located in remote and underdeveloped areas had no doctors while only 5% of health centres in more developed regions were without doctors. In addition, in urban Java there is 1 doctor per 3,000 population but 1 doctor per 22,000 population in rural Java (Dawson et al., 2011).

Similar geographical imbalances have been reported in other LMICs including countries in Sub-Saharan Africa where 36 out of 47 countries experience critical shortages in the health workforce (World Health Organization, 2006, Lemiere et al., 2011). For example, in Ghana, the density of doctors, nurses and midwives per 1,000 population is over 2.28 in the capital city, Accra, while the corresponding density in rural areas was only 0.67 (Appiah-Denkyira et al., 2013).

Several factors may explain geographical imbalances in the distribution of health workforce. Lower demand for health workers (due to lower ability to pay), lower health care infrastructure, unavailability of equipment and supplies, unfavourable job characteristics (such as longer working hours, higher workload and working in professional isolation) as well as lower standard of living in rural areas all affect the supply of health workers to rural areas. An understanding of how these factors interact to affect health workers’ location choices is important to aid policy decisions aimed at effectively addressing geographical imbalances in the distribution of health workers.

2

Regional (rural-urban) disparities resulting from the higher concentration of skilled health workers in wealthier urban areas and lower in remote and rural areas, means that, increasing financial protection for the poor, who are often located in remote and rural areas without a concurrent strengthening of the health workforce will undermine efforts to improve health outcomes in these areas. Therefore in designing health financing reforms, more attention need to be directed towards understanding their implications for the health workforce and how incentive structures can be explicitly incorporated within these reforms to address geographical imbalances in the distribution of health workers. The purpose of this report is to provide an overview of the factors that influence the supply of health workers to rural and remote areas and the extent to which financing policies can influence these factors, thereby stimulating further discussions on how health financing reforms can be designed to effectively address geographical imbalances in the distribution of health workforce. A literature review was carried out to assess the evidence on factors that affect the supply of health workers and on how these factors interact to influence location choices of health workers. In addition, this paper reviews evidence of the impact of financing policies on the supply and distribution of health workers in LMICs. Various databases where searched, restricting the range of publication dates to between 2000 and 2013. Databases searched include PubMed, Google Scholar, Science Direct and HRH Global Resource Centre.

Geographical imbalance in the distribution of the health workforce: A labour market perspective

Labour market theory provides a good basis for understanding the economic determinants of geographical imbalances in the distribution of health workers. In a perfect market, demand and supply tend towards an

3

equilibrium, driven by market forces which move both prices (or wage rate) and quantities to an equilibrium. For example, in a well-functioning market, high demand for health workers (captured by higher willingness and ability to pay for health workers) will result in an increase in wage rate. This will in turn induce an increase in the supply of labour by health workers until a new equilibrium is reached where demand matches supply. This presupposes that wage rates and quantities can readjust freely to achieve market equilibrium. However, the peculiar features of the health labour market (such as barriers to entry, asymmetry of information between buyers (patient/government) and sellers (health care providers/health workers) and inflexible wage rates) means that market forces cannot be relied on to achieve this equilibrium.

Disequilibrium occurs when the market fails to ‘clear’ resulting in shortages (in which case demand exceeds supply) or surpluses/unemployment (in which case supply exceeds demand). For example barriers to entry into the health labour market due to training and regulatory requirements could result in long delays in the response of labour supply to changes in demand. Bilateral pay negotiations between health worker unions and employers impose restrictions on employers’ ability to adjust wage rates downwards in response to high supply. In addition, the centralization of wage setting, as is the case in many countries, results in local shortages and surpluses when wage rates fail to capture regional differences in job attributes and environmental conditions. Therefore inflexibility of wage rates could result in persistent shortages in rural regions when wage rates fail to adjust upwards in response to low supply in order to attract health workers into these regions. On the other hand, surpluses may persist in urban regions when wage rates fail to adjust downwards in response to high supply of labour within these regions.

Empirical evidence

Empirical evidence supports labour market theory on the positive relationship between wage rate/salary levels and the supply of labour by

4

health workers (Baltagi et al., 2005, Qin et al., 2013, Sæther, 2005, Shields, 2004). Higher wages increases the supply of labour, either by increasing the number of hours worked by health workers already participating in the labour market or by encouraging those not already in the labour market to choose to work2.

The ability to pay for health workers in the public sector depends on a country’s fiscal space for health. In LMICs, the wages of public sector health workers are financed largely through budgetary allocations to the Federal Ministry of Health, as part of an overall wage bill. The size of the health wage bill depends on how the overall wage bill is allocated across different sectors. Therefore restrictions to expansions of the overall wage bill, for example to meet macroeconomic targets, are likely to result in wage rigidities and restrictions in the recruitment of health workers. The recognition of the impact wage bill ceilings could potentially have on the health workforce and thus the implications for reaching the Millennium Development Goals, has led to the exemption of the health sector from wage bill ceilings in several LMICs (Center for Global Development, 2007, Vujicic et al., 2009).

Although much debate and discussion has focused on the impact wage bill policies could have on the expansion, distribution and performance of the health workforce, there is still limited empirical evidence on the effectiveness of these policies. Available evidence suggests that prioritization of health within an overall wage bill and an increase in budgetary allocations to the health sector does not always translate to an expansion of health workforce, thus highlighting the complexities of the relationship between overall wage bill and stock of health workers in the public sector (Vujicic et al., 2009). Various factors have been highlighted as possible reasons for why policies designed to increase the health sector wage bill do not always result in an expansion of the health workforce. Inefficiencies in government administrative processes and 2 In high income countries, there is weak evidence of a fall in the number of hours worked by doctors as wage rate increase. This could occur when doctors on relatively high wage rates choose to substitute longer working hours for more leisure time (Scott, 2006, Whalley et al., 2008).

5

management functions impose limitations on the strategic use of resources which in turn result in the delays in hiring new staff, higher attrition rates and inefficiencies in the deployment of health workers to locations where they are most needed such as in rural areas (Vujicic et al., 2009).

Since many LMICs already face huge constraints in the overall fiscal space, increasing allocations to the health sector is not likely to be sustainable. Bossert and Ono (2010) estimated that for some low income countries to achieve the JLI/WHO recommended density of health workers, a huge and unrealistic proportion of their GDP will have to be allocated to health. For example, Ethiopia will have to allocate 53% of its GDP to health in order to reach the JLI/ WHO target (Bossert and Ono, 2010).

Taken together, these suggest that more emphasis needs to be placed on improving efficiencies in the utilization of available resources and current budgetary allocations to health rather than on a potentially unsustainable ‘scaling up’ of the health sector wage bill. Several policy strategies have been promoted in order to achieve greater efficiencies in the use of the health wage bill. These include the decentralization of human resource management and removing health workers from the national civil service. While these policy reforms have been shown to have some positive effects by enhancing administrative efficiencies, as in the case of decentralization, challenges still remain with the extent to which these reforms can positively address geographical imbalances in the distribution of health workforce (Haji et al., 2010, Vujicic et al., 2009, Heywood and Harahap, 2009, Lutwama et al., 2012). For example decentralization of wage setting from central authorities to local level is expected to allow greater flexibility in wage rates which reflects regional differences in job characteristics and living conditions. In addition, decentralization of human resource management is expected to result in timely and targeted recruitment of health workers in a manner that is responsive to local needs thereby reducing attrition of health workers

6

from rural posts. However, decentralization has often failed to achieve these objectives and negative experiences have been widely reported due to limited institutional capacity at local level and inadequate monitoring, resulting in nepotism and corruption (for example see Vujicic et al., 2009 ). In addition, geographical imbalances may be heightened due to wage inflation resulting from decentralization of pay setting. Wealthier regions are able to offer higher wages to attract health workers into these regions, to the detriment of poorer regions that are unable to match these higher wages (Dussault and Franceschini, 2006).

The scenario described in the preceding paragraphs applies mainly to the public health sector. In LMICs, geographical imbalance in the distribution of health workers is further exacerbated by a higher concentration of the private health sector in urban areas. Given that urban areas and cities comprise of a wealthier population with higher income, the demand (or ability to pay) for health services and thus the demand for health workers, is higher in these regions. Flexible wage rates in the private sector means that private sector employers can freely adjust wages upwards to attract health workers, resulting in an ‘internal brain-drain’ whereby health workers move from the public to private sector. A higher concentration of the private health sector in urban areas also provides greater opportunities for health workers in the public sector to engage in dual practice, thus providing further incentives for health workers to remain in urban areas (Gruen et al., 2002, Ndetei et al., 2008).

Studies on the impact of wage rates on the supply and retention of health workers to rural and under-served areas in LMICs are limited. This may partly be due to the unavailability of reliable data (McCoy et al., 2008). However, given the evidence on the impact of changes in salaries or wage rates on the supply of labour, offering higher wage rates for rural posts is likely to provide an incentive for health workers to relocate to rural areas. In the absence of reliable data which can be used to observe changes in health worker behaviours in response to policy changes,

7

stated preference methods (discrete choice experiments and contingent valuation) are now increasingly been used to predict health worker behaviours. Serra et al. (2010) showed using contingent valuation, that increasing salaries by 30-40% of current salary level will induce 5% of nurses and 3-4% of doctors to remain in Ethiopia.

Evidence from discrete choice experiments suggests that non-financial factors equally play an important role. Using hypothetical scenarios, discrete choice experiments have been used to investigate the extent to which non-financial (and financial) factors can attract health workers to rural areas and the importance these factors have in influencing location choices. These experiments have demonstrated the importance of a wide range of factors including job attributes, the importance of which vary across different health worker cadres and (demographic) characteristics of health workers. For example in Liberia, higher salaries were the most important job attributes for nurses while in Vietnam, greater opportunities for further studies proved to be more important for doctors (Vujicic et al., 2010) . Health workers who had a rural background (i.e. who had previously lived in rural areas before commencing medical training) and who had parents with lower educational qualifications were more likely to place a lower value on urban job locations (Vujicic et al., 2011). Similar findings were reported in South Africa, where the most cost-effective policy intervention was the recruitment of students from rural backgrounds because they are more likely to remain in a rural post, followed by preferential access to specialist training for nurses currently working in rural areas (Lagarde et al., 2012).

In Ghana, a combination of three job attributes- availability of supplies and equipment, supportive management and a 100% salary bonus, is likely to persuade 90% of medical students to accept a rural post after graduation (Kruk et al., 2010). For nursing students, a two-year fixed term contract followed by study leave was the most important determinant in accepting a rural post (Appiah-Denkyira et al., 2013), while opportunities for further training dominated for midwifery students

8

(Lori et al., 2012). Similar results were observed in India, where a guaranteed position on a post-graduate training course was the most important incentive for under-graduate nursing students to accept a 2-3 year post at a rural location (Raha et al., 2009).

A range of policies have been designed and implemented in many countries to encourage skilled health workers to relocate to rural and underserved areas. These include mandatory practice in rural areas through bonded training schemes; restriction of recruitment in over-served areas; the use of short-term contracts accompanied by high remuneration packages; strengthening opportunities for financial top-ups in rural areas through the legalization of dual practice; training and targeted recruitment of health workers from rural and lower-income background. However, there is limited robust evidence on the effectiveness of these incentive schemes in increasing the supply of skilled health workers in rural and remote areas as well as limited evidence on the long-term impact of these schemes (Barnighausen and Bloom, 2009, Buykx et al., 2010, Grobler et al., 2009). Although some studies have demonstrated some evidence of a positive impact in increasing the supply of skilled workers to rural areas, poor study design limits the reliability of these results (Dolea et al., 2010), thus raising important questions about the scope for these incentive schemes to achieve set objectives.

Health financing policies: Implications for geographical distribution of the health workforce

As highlighted in the preceding section, several factors affect geographical imbalances in the distribution of the health workforce. On the supply-side, health worker preferences and job characteristics are important factors. On the demand side, wage rates and opportunities for salary top-ups are important factors, suggesting that health workers will

9

be attracted to areas with higher financial resources. Therefore health financing policies that affect the redistribution of financial resources are likely to have an impact on the distribution of the health workforce. This sub-section discusses recent financing reforms and their impact on both the distribution of financial resources and HRH.

User fee reforms

User fees were promoted in the 1980s against the backdrop of failing health care systems in LMICs. They were, and still are viewed by their proponents as a means of generating extra resources that could be used to improve the quality of health care services. While available evidence suggests that user fees may have been successful in increasing cost recovery and in generating revenue (for example see McPake, 1993), they are regressive and impact negatively on health care service utilization particularly amongst the poorer population (Witter, 2005, James et al., 2006, World Health Organization, 2008). In addition, user fees policies are likely to exacerbate geographical imbalances in the distribution of the health workforce if higher demand for health services in urban areas due to a higher ability to pay provides strong incentives for health workers to remain in urban areas (Ndetei et al., 2008).

Following years of debate and discussion on user fee policies, there now appears to be a general consensus on the abolition of user fees and a shift to fairer means of financing health care services. The focus of much research has been on the impact of abolishing user fees on the utilization of health services and on population health outcomes, while the implication for the distribution and performance of the health workforce has received less attention. Out-of-pocket payments represent an important barrier to accessing health care services. Therefore, the removal of user fees is likely to result in an increase in the demand and utilization of health care services, a trend that has now been reported widely across a range of LMICs following changes in user fee policies (Yates, 2009, Meessen et al., 2009, Penfold et al., 2007). Higher utilization of health care services imposes an extra burden on the health

10

workforce, particularly in rural and remote areas where higher gains in the utilization of health services have been reported (Masiye et al., 2008, Witter et al., 2011).

In several LMICs, health care workers have reported an increase in their workload and as a consequence, a decline in motivation and an increase in the desire to resign from their current positions (Burnham et al., 2004, Cheelo et al., 2010 , McIntyre et al., 2005, Nimpagaritse and Bertone, 2011). The decline in health workers’ motivation is further exacerbated by the loss of supplementary income or bonuses previously provided by user fee revenues.

Revenue generated through user fees contribute a significant proportion to total revenue of lower level health facilities, and allows greater flexibility in the recruitment and remuneration of local support staff (Cheelo et al., 2010 , Nabyonga-Orem et al., 2008, Steinhardt et al., 2011, Witter et al., 2010). Therefore compared to the impact on higher level health facilities, the abolition of user fees is likely to have a greater impact on lower level health facilities due to their greater reliance on user fee revenues to cover both salary and non-salary costs.

To the best of our knowledge, no studies have directly evaluated the impact of the abolition of user fees on the geographical distribution of the health workforce. However, the implication of removing user fees for the distribution of HRH can be inferred from evidence on pro-poor increases in the utilization of health care services (Masiye et al., 2008, Witter et al., 2011), the disproportionate loss of locally generated revenues in rural areas compared to urban areas (Witter et al., 2010) and the resulting redundancies of support workers (Nabyonga-Orem et al., 2008). In addition, lack of planning and preparations for adequate reimbursement mechanisms (Meessen et al., 2011) and lack of clear guidance on how user fee replacement funds are to be utilized (Cheelo et al., 2010 ) further compounds difficulties in rural allocation and retention of health workers.

11

To compensate health facilities for loss of user fee revenue as well as to cover costs for providing free health care services, various reimbursement mechanisms have been used in different countries (for example see Meessen et al., 2011). These reimbursement mechanisms provide different incentives that influence the behaviour of health workers, and may in turn influence the geographical distribution of health workers. For example in Senegal, following the removal of user fees for deliveries and caesarean sections in 2005, lower level facilities were compensated on an ‘input-based’ system which meant that health centres were provided with kits and supplies for normal child birth deliveries and caesarean sections but no cash transfers. Conversely, higher level health care facilities were reimbursed prospectively to cover costs for caesarean sections, with lump sums that were set much higher than the actual cost of providing the service and in some cases, much higher than amount previously charged as user fees for caesarean sections (Witter et al., 2010). The marked difference between the costs per additional caesarean section (US$467) and the cost per additional supervised normal delivery (US$21), could provide a financial incentive to perform more caesarean sections in higher level facilities (Witter et al., 2010). Imbalances in the distribution of financial resources is thus reinforced, which may in turn reinforce imbalances in the distribution of health workers

Universal health coverage reforms

Pooling funds through voluntary or compulsory health insurance schemes represents an equitable means of financing health services. This is because the criteria used for determining contribution levels or premiums (whereby the criteria are based on ability to pay such as level of income, consumption, occupation or area of residence) differ from the criteria used in paying out (whereby the criteria are based on the need for health care). This means that health care is subsidized for the sick by those who are healthy and as the pool of funds grows to include individuals from a wider range of socioeconomic status, health care

12

services for the poorer can be effectively subsidized by the richer. Health insurance schemes are now widespread across many LMICs with varying degrees of success in expanding the pool of funds and in reducing out-of-pocket payments. For example, while in some countries such as Thailand, the pooled share of total health expenditure has been accompanied by a fall in the out-of-pocket payment share, in other countries such as the Philippines, the out-of-pocket payment share of total health expenditure grew faster than the pooled share over a 14 year period (Fan and Savedoff, 2012).

A common feature of most UHC schemes is the separation of the provider function from the purchaser function. This means that providers are reimbursed for providing health care services to the population through a pre-determined reimbursement mechanism. As highlighted in the previous sub-section, variations in reimbursement mechanisms across different levels of health care facilities can accentuate geographical imbalances in the distribution of the health workforce. However even when uniform reimbursement rules are applied, facilities with more sophisticated infrastructures are likely to attract higher reimbursements for providing more sophisticated health care services compared to lower level facilities. (Witter and Garshong, 2009). As a consequence, financial resources are distributed disproportionately, favouring regions or areas with a higher concentration of high level facilities and infrastructures.

For example, in Ghana, under the National Health Insurance Scheme (NHIS) health care providers are reimbursed on a pay-by-episode-of-care basis, according to disease groups (Diagnosis-Related Groups or DRGs). Although revenue generated by health facilities through NHIS reimbursements have grown significantly since the inception of the NHIS in 2005, evidence suggests that this growth is unevenly distributed across different locations (urban vs. rural ) and different levels of health facilities with hospitals attracting a larger proportion of NHIS reimbursements compared to lower level health care facilities (Witter and Garshong, 2009). This heightening of pro-urban bias in the

13

distribution of financial resources, as an unintended consequence of the NHIS, may leave rural areas with less financial leverage to compete with higher level facilities in attracting and retaining health workers.

Furthermore, reimbursements to rural health facilities can be further compromised when members from rural areas withdraw their membership from the scheme. Difficulties in accessing health care facilities in remote areas due to barriers imposed by physical distances to health facilities may deter rural members from renewing their membership. For example, in Ghana, willingness to renew membership varied significantly by location but not by economic status, suggesting that the unwillingness to renew membership with the scheme was not driven by an inability to pay renewal premiums (Bjerrum and Asante, 2009).

Although no studies have directly investigated the impact of UHC reforms on the geographical distribution of health workers, geographical imbalances in the distribution of financial resources, as an unintended consequence of UHC reforms, is likely to exacerbate historical imbalances in the distribution of health workforce. The example of the Ghanaian NHIS highlights the need to integrate measures within UHC reforms that induce the redistribution of both financial and human resources in favour of rural areas.

Few examples can be cited of UHC schemes that have incorporated within their design features, measures that are aimed at explicitly addressing rural-urban imbalances in the distribution of health workers. Thailand’s attempt to address this through its UHC reform illustrates the difficulties. Under the reform, the provider/purchasing function was separated with a central agency managing the purchasing of health services and provincial health authorities overseeing the provision of health care services. Global budgetary allocations to provincial health authorities from the central Ministry of Health were replaced by capitation payment adjusted for population-age structure. To address rural-urban imbalance in the distribution of health workers, capitation

14

payments were kept lower than the recommended level, resulting in financial deficits in some health facilities and surpluses in others. As a consequence, ‘capitation-losing’ health facilities and regions-mostly large public hospitals in urban areas, were unable to cover health workers salaries and it was anticipated that this would induce the redistribution of health workers from over-served areas (mostly urban areas) to under-served and rural areas (Hughes et al., 2010). However, the redistribution of health workers did not occur as planned and the policy objective was compromised by pressures from professional groups which led to the reinstatement of pre-reform budgetary allocations from the central Ministry of Health.

Conclusion

As the momentum towards achieving UHC grows in LMICs, reducing geographical imbalances in the distribution of the health workforce remains crucial to achieving this objective. Rural-urban imbalances in the distribution of higher level health care facilities can result in an unequal distribution of financial resources. This in turn provides a greater incentive for health workers to remain in urban areas or, conversely, provides less incentive for health workers to relocate to rural areas. This link between financial resources and the supply of health workers suggest that health financing reforms that affect the redistribution of financial resources is likely to have an effect on the distribution of health workers. Therefore, inducing an appropriate redistribution of financial resources should be an objective of reforms aimed at achieving UHC.

Other initiatives such as improving health care infrastructure in rural areas could also serve as an important policy tool for addressing geographical imbalances in the distribution of the health workforce. Not only will this provide non-financial incentives for health worker to remain in rural areas through providing better working conditions and opportunities for better professional practices, better health care

15

infrastructures in rural areas will attract higher reimbursement and provide a financial incentive for health workers to remain in these areas.

It is worth noting however, that the hierarchical structure of the health care systems in most countries is designed to have a lower concentration of higher level facilities compared to lower level facilities. Thus, the few high level facilities, often located in urban areas and cities, which provide specialist and more sophisticated health care services are bound to attract more financial resources as well as a larger stock of highly skilled health workers. Thus, geographical imbalances in the distribution of health workers may be a ‘natural’ consequence of the hierarchical structure of the health care system and it may be ambitious to expect to achieve relative equality in the distribution of the health workforce. However, ignoring the implications of health financing reforms for rural distribution of the health workforce, as most reforms to date have done, can result in unintended negative consequences.

16

References

APPIAH-DENKYIRA, E., HERBST, C. H., SOUCAT, A., LEMIERE, C. & SALEH, K. 2013. Towards interventions on human resources for health in Ghana: Evidence for health workforce planning and results, The World Bank, Washington, DC.

BALTAGI, B. H., BRATBERG, E. & HOLMÅS, T. H. 2005. A panel data study of physicians' labor supply: the case of Norway. Health Economics, 14, 1035-1045.

BARNIGHAUSEN, T. & BLOOM, D. 2009. Financial incentives for return of service in underserved areas: a systematic review. BMC health services research, 9, 86-86.

BJERRUM, A. & ASANTE, F. 2009. Determinants of health insurance membership in Ghana. . Accra, Ghana: Accra Coalition Health.

BOSSERT, T. J. & ONO, T. 2010. Finding Affordable Health Workforce Targets In Low-Income Nations. Health Affairs, 29, 1376-1382.

BURNHAM, G. M., PARIYO, G., GALIWANGO, E. & WABWIRE-MANGE, F. 2004. Discontinuation of cost sharing in Uganda. Bulletin of the World Health Organization 82, 187-195.

BUYKX, P., HUMPHREYS, J., WAKERMAN, J. & PASHEN, D. 2010. Systematic review of effective retention incentives for health workers in rural and remote areas: towards evidence-based policy. The Australian Journal Of Rural Health, 18, 102-109.

CENTER FOR GLOBAL DEVELOPMENT 2007. Does the IMF Constrain Health Spending in Poor Countries? Evidence and an Agenda for Action. Washington, DC: Center for Global Development. Available at http://www.cgdev.org/doc/IMF/IMF_Report.pdf.

CHEELO, C., CHAMA, C., POLLEN, G., CARASSO, B., PALMER, N., JONSSON, D., LAGARDE, M. & CHANSA, C. 2010 Do User Fee Revenues Matter? Assessing the Influences of the Removal of User Fees on Health Financial Resources in Zambia. Department of Economics, Working Paper No. 2010/1. University of Zambia Lusaka.

DAWSON, A., HOWES, T., GRAY, N. & KENNEDY, E. 2011. Human resources for health in maternal, neonatal and reproductive health at community level: A profile of Indonesia. Human Resources for Health Knowledge Hub and Burnet Institute, Sydney, Australia.

17

DOLEA, C., STORMONT, L. & BRAICHET, J.-M. 2010. Evaluated strategies to increase attraction and retention of health workers in remote and rural areas. Bulletin of the World Health Organization 88, 379-385.

DUSSAULT, G. & FRANCESCHINI, M. 2006. Not enough there, too many here: understanding geographical imbalances in the distribution of the health workforce. Human Resources for Health, 4, 12.

FAN, V. Y. & SAVEDOFF, W. D. 2012. The Health Financing Transition: A Conceptual Framework and Empirical Evidence Working Paper. . Washington, DC: Center for Global Development

GROBLER, L., MARAIS, B., MABUNDA, S., MARINDI, P., REUTER, H. & VOLMINK, J. 2009. Interventions for increasingthe proportion of health professionals practising in rural and other underserved areas. Cochrane Database of Systematic Reviews [Online], Issue 1.

GRUEN, R., ANWAR, R., BEGUM, T., KILLINGSWORTH, J. R. & NORMAND, C. 2002. Dual job holding practitioners in Bangladesh: an exploration. Soc Sci Med, 54, 267-279.

HAJI, M., DURAIRAJ, V., ZURN, P., STORMONT, L. & MAPUNDAC, M. 2010. Emerging opportunities for recruiting and retaining a rural health workforce through decentralized health financing systems. Bulletin of the World Health Organization 88, 397-399.

HEYWOOD, P. & HARAHAP, N. 2009. Human resources for health at the district level in Indonesia: the smoke and mirrors of decentralization. Human Resources for Health, 7, 6.

HUGHES, D., LEETHONGDEE, S. & OSIRI, S. 2010. Using economic levers to change behaviour: The case of Thailand's universal coverage health care reforms. Social Science & Medicine, 70, 447-454.

JAMES, C., HANSON, K., MCPAKE, B., BALABANOVA, D., GWATKIN, D., HOPWOOD, I., KIRUNGA, C., KNIPPENBERG, R., MEESSEN, B., MORRIS, S., PREKER, A., SOUCAT, A., SOUTEYRAND, Y., TIBOUTI, A., VILLENEUVED, P. & XUH, K. 2006. To Retain or Remove User Fees?: Reflections on the Current Debate in Low- and Middle-Income Countries. Applied Health Economics and Health Policy, 5, 137-153.

KRUK, M. E., JOHNSON, J. C., GYAKOBO, M., AGYEI-BAFFOUR, P., ASABIR, K., KOTHA, S. R., KWANSAH, J., NAKUA, E., SNOW, R. C. & DZODZOMENYO, M. 2010. Rural practice preferences among

18

medical students in Ghana: a discrete choice experiment. Bulletin of the World Health Organization, 88, 333-41.

LAGARDE, M., BLAAUW, D. & CAIRNS, J. 2012. Cost-effectiveness analysis of human resources policy interventions to address the shortage of nurses in rural South Africa. Social Science & Medicine, 75, 801-6.

LEMIERE, C., HERBST, C. H., JAHANSHAHI, N., SMITH, E. & SOUCAT, A. 2011. Reducing geographical imbalances of health workers in sub-saharan Africa: A labor market perspective on what works, what does not, and why. Africa Human Development Series. The World Bank Washington, DC.

LORI, J. R., ROMINSKI, S., RICHARDSON, J., AGYEI-BAFFOUR, P., KWEKU, N. E. & GYAKOBO, M. 2012. Factors influencing Ghanaian midwifery students' willingness to work in rural areas: a computerized survey. International Journal of Nursing Studies, 49, 834-41.

LUTWAMA, G., ROOS, J. & DOLAMO, B. 2012. A descriptive study on health workforce performance after decentralisation of health services in Uganda. Human Resources for Health, 10, 41.

MASIYE, F., CHITAH, B. M., CHANDA, P. & SIMEO, F. 2008. Removal of user fees at Primary Health Care facilities in Zambia: A study of the effects on utilisation and quality of care. Equinet discussion paper number 27 Regional Network for Equity in Health in Southern Africa (EQUINET).

MCCOY, D., BENNETT, S., WITTER, S., POND, B., BAKER, B., GOW, J., CHAND, S., ENSOR, T. & MCPAKE, B. 2008. Salaries and incomes of health workers in sub-Saharan Africa. The Lancet, 371, 675-681.

MCINTYRE, D., GILSON, L. & MUTYAMBIZI, V. 2005. Promoting equitable health care financing in the AFrican context: current challenges and future prospects. Equinet discussion paper number 27. Regional Network for Equity in Health in Southern Africa (EQUINET).

MCPAKE, B. 1993. User charges for health services in developing countries: A review of the economic literature. Social Science & Medicine, 36, 1397-1405.

MEESSEN, B., HERCOT, D., NOIRHOMME, M., RIDDE, V., TIBOUTI, A., BICABA, A., KIRUNGA TASHOBYA, C. & GILSON, L. 2009.

19

Removing User Fees in the Health Sector in Low-Income Countries – A Multi-Country Review. New York: UNICEF.

MEESSEN, B., HERCOT, D., NOIRHOMME, M., RIDDE, V., TIBOUTI, A., TASHOBYA, C. K. & GILSON, L. 2011. Removing user fees in the health sector: a review of policy processes in six sub-Saharan African countries. Health Policy and Planning, 26, ii16-ii29.

NABYONGA-OREM, J., KARAMAGI, H., ATUYAMBE, L., BAGENDA, F., OKUONZI, S. & WALKER, O. 2008. Maintaining quality of health services after abolition of user fees: A Uganda case study. BMC Health Services Research, 8, 102.

NDETEI, D. M., KHASAKHALA, L. & OMOLO, J. O. 2008. Incentives for health worker retention in Kenya: An assessment of current practice EQUINET Discussion Paper Series. EQUINET with African Mental Health Foundation, University of Namibia, Training and Research Support Centre, University of Limpopo and ECSA-Regional Health Community, EQUINET, Harare.

NIMPAGARITSE, M. & BERTONE, M. P. 2011. The sudden removal of user fees: the perspective of a frontline manager in Burundi. Health Policy and Planning, 26, ii63-ii71.

PENFOLD, S., HARRISON, E., BELL, J. & FITZMAURICE, A. 2007. Evaluation of the delivery fee exemption policy in ghana: population estimates of changes in delivery service utilization in two regions Ghana Medical Journal, 41, 100-109.

QIN, X., LI, L. & HSIEH, C.-R. 2013. Too few doctors or too low wages? Labor supply of health care professionals in China. China Economic Review, 24, 150-164.

RAHA, S., BERMAN, P. & BHATNAGAR, A. 2009. Career Preferences of Medical and Nursing Students in Uttar Pradesh. Washington, DC: World Bank.

SÆTHER, E. 2005. Physicians’ Labour Supply: The wage impact on hours and practice combinations. Labour, 19, 673-703.

SCOTT, A. 2006. The Productivity of the Health Workforce. Australian Economic Review, 39, 312-317.

SERRA, D., SERNEELS, P., LINDELOW, M. & MONTALVO, J. G. 2010. Discovering the real world: Health workers’ career choices and

20

early work experience in Ethiopia. Africa Human Development Series The World Bank: Washington, DC.

SHIELDS, M. A. 2004. Addressing nurse shortages: what can policy makers learn from the econometric evidence on nurse labour supply?*. The Economic Journal, 114, F464-F498.

STEINHARDT, L. C., AMAN, I., PAKZAD, I., KUMAR, B., SINGH, L. P. & PETERS, D. H. 2011. Removing user fees for basic health services: a pilot study and national roll-out in Afghanistan. Health Policy and Planning, 26, ii92-ii103.

VUJICIC, M., ALFANO, M. & SHENGELIA, B. 2010. Getting health workers to rural areas: Innovative Analytic Work to Inform Policy Making. Health, Nutrition and Population (HNP) Discussion Paper. The World Bank, Washington, DC.

VUJICIC, M., OHIRI, K. & SPARKES, S. 2009. Working in health: Financing and managing the public sector health workforce, The World Bank, Washington, DC.

VUJICIC, M., SHENGELIA, B., ALFANO, M. & THU, H. B. 2011. Physician shortages in rural Vietnam: using a labor market approach to inform policy. Social Science & Medicine, 73, 970-7.

WHALLEY, D., GRAVELLE, H. & SIBBALD, B. 2008. Effect of the new contract on GPs' working lives and perceptions of quality of care: a longitudinal survey. British Journal of General Practice, 58, 8-14.

WITTER, S. 2005. An unnecessary evil? User fees for healthcare in low-income countries. Save the Children Fund.

WITTER, S., DIENG, T., MBENGUE, D., MOREIRA, I. & DE BROUWERE, V. 2010. The national free delivery and caesarean policy in Senegal: evaluating process and outcomes. Health Policy and Planning, 25, 384-392.

WITTER, S. & GARSHONG, B. 2009. Something old or something new? Social health insurance in Ghana. BMC International Health and Human Rights, 9, 20.

WITTER, S., KHADKA, S., NATH, H. & TIWARI, S. 2011. The national free delivery policy in Nepal: early evidence of its effects on health facilities. Health Policy and Planning, 26, ii84-ii91.

21

WORLD HEALTH ORGANIZATION 2006. The World Health Report: working together for health. World Health Organization: Geneva.

WORLD HEALTH ORGANIZATION 2008. WHO Meeting on User Fee Impact On Access And Equity And On Lessons Learnt For the Pacific. In: ORGANIZATION, W. H. (ed.).

WORLD HEALTH ORGANIZATION 2010. Human Resources for Health Country Profile Thailand.

WORLD HEALTH ORGANIZATION 2011. Human Resources for Health Country Profile Timor-Leste. Available at http://www.searo.who.int/entity/human_resources/data/tls_profile.pdf.

YATES, R. 2009. Universal health care and the removal of user fees. The Lancet, 373, 2078-2081.

22