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Int J Health Policy Manag 2018, 7(1), 35–47
doi 10.15171/ijhpm.2017.42
Original Article
Performance-Based Financing to Strengthen the Health
System in Benin: Challenging the Mainstream Approach
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htp://ijhpm.com
Int JJ Health
Int
Health Policy
Policy Manag
Manag
10.15171/ijhpm.2015.188
10.15171/ijhpm.2015.188
Elisabeth Paul1*, Mohamed Lamine Dramé2, Jean-Pierre Kashala2, Armand Ekambi Ndema2, Marcel Kounnou3,
Julien Codjovi Aïssan4, Karel Gyselinck5
Abstract
Background: Performance-based financing (PBF) is often proposed as a way to improve health system performance. In
Benin, PBF was launched in 2012 through a World Bank-supported project. The Belgian Development Agency (BTC)
followed suit through a health system strengthening (HSS) project. This paper analyses and draws lessons from the experience
of BTC-supported PBF alternative approach – especially with regards to institutional aspects, the role of demand-side actors,
ownership, and cost-effectiveness – and explores the mechanisms at stake so as to better understand how the “PBF package”
functions and produces effects.
Methods: An exploratory, theory-driven evaluation approach was adopted. Causal mechanisms through which PBF is
hypothesised to impact on results were singled out and explored. This paper stems from the co-authors’ capitalisation of
experiences; mixed methods were used to collect, triangulate and analyse information. Results are structured along Witter
et al framework.
Results: Influence of context is strong over PBF in Benin; the policy is donor-driven. BTC did not adopt the World
Bank’s mainstream PBF model, but developed an alternative approach in line with its HSS support programme, which is
grounded on existing domestic institutions. The main features of this approach are described (decentralised governance,
peer review verification, counter-verification entrusted to health service users’ platforms), as well as its adaptive process.
PBF has contributed to strengthen various aspects of the health system and led to modest progress in utilisation of health
services, but noticeable improvements in healthcare quality. Three mechanisms explaining observed outcomes within
the context are described: comprehensive HSS at district level; acting on health workers’ motivation through a complex
package of incentives; and increased accountability by reinforcing dialogue with demand-side actors. Cost-effectiveness and
sustainability issues are also discussed.
Conclusion: BTC’s alternative PBF approach is both promising in terms of effects, ownership and sustainability, and less
resource consuming. This experience testifies that PBF is not a uniform or rigid model, and opens the policy ground
for recipient governments to put their own emphasis and priorities and design ad hoc models adapted to their context
specificities. However, integrating PBF within the normal functioning of local health systems, in line with other reforms, is
a big challenge.
Keywords: Performance-Based Financing (PBF), Health System Strengthening (HSS), Local Health System, Benin, Lowand Middle-Income Countries (LMICs), Demand-Side Actors
Copyright: © 2018 The Author(s); Published by Kerman University of Medical Sciences. This is an open-access article
distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly
cited.
Citation: Paul E, Dramé ML, Kashala JP, et al. Performance-based financing to strengthen the health system in Benin:
challenging the mainstream approach. Int J Health Policy Manag. 2018;7(1):35–47. doi:10.15171/ijhpm.2017.42
Background
Health systems in many low- and middle-income countries
(LMICs) face a number of structural problems and
inefficiencies. In view of the lack of success of most reform
attempts, performance-based financing (PBF) has been
proposed as a way to catalyse comprehensive reforms and
help improve health system performance.1 PBF is a supplyside form of results-based financing whose core features are
the following: performance-based incentives are earned by
service providers; payments are targeted at individual health
facilities and administrations, often with trickle-down effect
to health workers; there is usually some split of functions
between regulation, purchasing, fund-holding, verification
and service delivery; payments are linked to outputs, modified
by quality indicators.2 Following a few positive experiences,
especially in Rwanda,3,4 PBF has fastly expanded in subFull list of authors’ affiliations is available at the end of the article.
Article History:
Received: 4 January 2017
Accepted: 25 March 2017
ePublished: 15 April 2017
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Summary
*Correspondence to:
Elisabeth Paul
Email: E.Paul@ulg.ac.be
Saharan Africa in the past decade. To our knowledge, PBF
implementation in LMICs has almost always been supported
by donors, particularly the World Bank which administers
the Health Results Innovation Trust Fund (HRITF) created
in 2007 to support results-based financing approaches in the
health sector (see https://www.rbfhealth.org). The Belgian
Development Agency (BTC) has also supported PBF in
several countries among which Rwanda and Burundi.
In Benin, after two inconclusive experiences led by the Ministry
of Health (MoH) in 2007 and BTC in 2008-2009, PBF was
again experimented in 2012 through a World Bank-supported
pilot project in eight health districts. The MoH then requested
BTC to follow suit in the five districts it was supporting
through a health system strengthening (HSS) project: ComéBopa-Grand Popo-Houeyogbé (CBGH), KlouèkanméToviklin-Lalo (KTL) and Aplahoué-Djakotomey-Dogbo
Paul et al
Key Messages
Implications for policy makers
•
Benin has experimented two performance-based financing (PBF) approaches: one under the mainstream World Bank model, and an alternative
one which differs substantially in terms of institutions, integration, and associated costs.
•
Understanding the mechanisms that explain observed outcomes can help refine the various elements of PBF design according to context
specificities.
•
It is possible to develop an alternative, less resource consuming PBF approach, grounded on existing domestic institutions and therefore
contributing to strengthening local health systems.
•
In Benin, PBF enabled to improve healthcare quality but increase in utilisation of health services did not automatically follow suit.
•
The alternative PBF approach developed in Benin has helped achieve progress mostly through: comprehensive health system strengthening
(HSS) at district level; acting on health workers’ motivation through a complex package of incentives; and increased accountability by reinforcing
dialogue with the demand-side actors.
Implications for the public
A bottom-up performance-based financing (PBF) approach has been developed and implemented in Benin since 2012 as an alternative to the
mainstream model supported by several donors. This approach is integrated in existing local institutions (decentralised governance, peer review
verification, counter-verification entrusted to health service users’ platforms); it is not much resource consuming and enables to strengthen the local
health system. PBF, including its ancillary components, has contributed to strengthen various aspects of the health system (equipment, information
system, human resources, governance). After four years of implementation, PBF has led to modest progress in utilisation of health services, but most
of all noticeable improvements in quality of care.
(ADD) in the Mono-Couffo region (South Benin); Bassila,
and Djougou-Ouaké-Copargo (DOC) in the AtacoraDonga region (North Benin). In 2015, PBF was scaled up in
all districts of the country thanks to financial support from
Gavi and the Global Fund to Fight Aids, Tuberculosis and
Malaria (GFATM) which adopted the World Bank’s approach.
The latter is similar to that implemented in other countries
(Rwanda, Burundi) and relies on a project coordination unit
for piloting, on an external firm for verification of results, and
on community-based organisations for counter-verification.
However, as explained below, BTC has developed a promising
alternative, more integrated and less resource-consuming
approach which is grounded on existing domestic institutions
and networks, aims to strengthen the local health system,
and uses peer review for verification of results and health
service users’ platforms for counter-verification. Since 2015,
the MoH has initiated a joint process aimed at harmonising
the PBF approaches in view of rendering it country-led and
sustainable.
As pointed by a recent literature survey, what PBF actually
entails is not straightforward, and existing PBF schemes
around the world differ on almost every single of its usual
composing elements; moreover, the exact mechanisms
through which PBF financial incentives, contractual features
and ancillary components such as increased control and
accountability mechanisms operate are not well understood.5,6
Therefore, the objective of this paper is to analyse and draw
lessons from the experience of the BTC-supported PBF
alternative approach developed in Benin, taking account
of its context, and to explore the mechanisms at stake so as
to better understand how the “PBF package” functions and
produces its effects. This is important to demonstrate that
PBF should not be viewed as a uniform or rigid model and on
the contrary, governments should adapt PBF designs to their
context specificities and priorities. The institutional aspects,
the role of demand side actors, the issues of ownership and
cost-effectiveness are given particular attention. The paper
concludes by discussing sustainability issues in relation to
PBF.
36
Methods
Since it aims to “open the black box” of PBF,5 this paper adopted
an exploratory, theory-driven evaluation approach.7 Indeed,
the successive BTC health sector support programmes have
been designed as pilot, research-action programmes aimed
at testing a number of hypotheses supposed to contribute to
increasing health system performance through strengthening
the health system at central, intermediate (departmental) and
local (district) levels. The technical and financial document
orienting the current programme, called PASS-Sourou, lays
out a complex intervention logic explaining how planned
activities are hypothesised to interact towards five expected
results, which together are hypothesised to strengthen the
health system’s three key dimensions: supply-side, demandside and governance. Noticeably, PBF is not isolated as a single
activity or result, but is referred to as a transversal approach
contributing to several results, with activities relating both
to the supply-side and demand-side of the system. The
programme orientation document also specifies that the PBF
model should keep on being tested so as to ensure it is peoplecentred, equity-oriented and sustainable.8
From this programme orientation document as well as from
authors’ participation in the design and development of the
BTC alternative PBF approach since 2012, and through an
iterative process, three causal mechanisms through which
PBF is hypothesised to impact on results were singled out,
that we intend to explore in this paper: (i) comprehensive
HSS at district level; (ii) acting on health workers’ motivation
through a complex package of incentives; and (iii) increased
accountability by reinforcing dialogue with demand-side
actors. This set of hypotheses may basically be outlined as
shown in Figure 1.
Since the BTC alternative PBF approach has been conceived
as a systemic intervention with a possibly broad range of
effects on the health system, and thus since we intend to
analyse the interactions between PBF and the local health
system, we broadly followed the PBF monitoring & evaluation
framework proposed by Witter and colleagues.2 Therefore
results are presented based on analyses of: (1) the influence
International Journal of Health Policy and Management, 2018, 7(1), 35–47
Paul et al
Figure 1. Hypotheses on How the BTC Alternative PBF Model Impacts
on Results. Abbreviations: HSS, health system strengthening; BTC,
Belgian Development Agency; PBF, performance-based financing.
of context over PBF; (2) policy formulation; (3) design; (4)
implementation; (5) effects of PBF on health systems.
This paper stems from the co-authors’ capitalisation of
experiences, that is usually defined as transformation of
experience into shareable knowledge.9 It is issued after 4
years of research-action, at a time when, on the one hand,
both World Bank and BTC funds available to support PBF
are ending (respectively in June and September 2017); and
on the other hand, the MoH is urged to take stock of donorsupported PBF schemes to design its own model and find
budget rooms to finance it. The theory-driven evaluation
approach adopted was conceived through an iterative process
and relies on crossed perspectives from all the co-authors.
They have all been involved either directly or indirectly in
the BTC programme – be it as coordinator of the overall
HSS programme, technical assistant, MoH recipient at
departmental or district level, headquarter backstopping or
consultant; one of them is also an academic with extensive
experience in Benin. For each of the five domains analysed
below, mixed methods were used to collect, triangulate and
analyse information, including: financial and technical data
produced by the BTC-supported project over four years (third
quarter 2012 to third quarter 2016), routine data about the
health system and results, existing records and studies on
the PBF approaches implemented in Benin; key stakeholders
interviews performed at national and operational levels during
a previous research10; and mainly participative observation
of PBF implementation – including on the field by those coauthors involved at departmental and district levels, and also
during the PBF harmonisation process launched by the MoH
in 2015 (as members of the four joint missions and other
technical workshops), which enabled to compare the pros and
cons of the two PBF models implemented to date.
Results
Influence of Context over Performance-Based Financing
As argued by Witter and colleagues, since health systems
are complex adaptive systems, it is necessary to include the
context in understanding and documenting PBF, and to
monitor the continuous interactions between the context
and other PBF domains (or features) over time.2 Benin
makes no exception and PBF was introduced in a complex
system plagued with important bottlenecks. The National
Health Forum organised in November 2007, which gathered
some 600 participants, performed an in-depth assessment
of the health sector context, and formulated a number of
recommendations which guided the design in 2009 of the
new 10-year health sector development plan. Main issues
identified relate to governance in the health sector (poor
performance, lack of leadership), poor quality of healthcare,
inadequate infrastructure and equipment, and the need to
valorise human resources for health – some of them will later
be targeted by PBF (governance, quality, human resources).
However, if the importance of establishing a management
system based on a culture of performance, accountability
and results was referred to, the possibility of introducing PBF
was not mentioned. Rather, “orthodox” solutions to improve
governance and staff motivation (such as salary increases and
distance allowances) were proposed. An emerging priority
was to install a consistent quality insurance system in the
health sector.11 As for the 2009-2018 Health Sector Plan, it
also only vaguely refers to the need to design mechanisms
enabling to incentivize staff retention and performance,
through improving working conditions, valorisation of
performance, and adoption of retention measures. This plan
does not mention PBF.12
Introduction of PBF in the health sector in Benin was
obviously propelled by its international popularity, which also
triggered additional donors later during the implementation
phase. As explained below, PBF was introduced with support
from various donors – mainly the World Bank, but also BTC
who piloted a performance premium scheme in one district in
2008 and 2009, plus other donors who also initiated punctual
PBF schemes (notably UNICEF at community level). Another
influential contextual element deals with the creation in 2011
of a joint HSS platform, following the signature in November
2010 of the first “Compact” between the MoH and five donors
within the framework of the International Health Partnership
and related initiatives. The HSS platform gathers the World
Bank, GFATM, Gavi and BTC around the MoH, with support
from the World Health Organization (WHO). In this context,
the four main donors agreed on a geographical distribution of
their HSS support so as to cover all the 34 health districts of
the country: 8 were already supported by the World Bank and
5 by BTC; Gavi and the GFATM agreed to support respectively
the 2 and 19 remaining districts. Involvement of new donors
will prompt a harmonisation process and thus adaptation of
some elements of the design of both PBF approaches.
Policy Formulation
The World Bank project’s Appraisal document candidly
explains that:
“In 2007, Benin started to test [Results-Based Financing
(RBF)] in 3 districts. According to an evaluation carried out
in 2008, the experiment was plagued with numerous issues
related to implementation […]. After several workshops
and study tours (in Rwanda), the MoH decided to continue
and even to scale-up this experience, but only after a deep
redesign of the RBF mechanism. The MoH then applied
for a RBF grant ($11 million) under the Multi-Donor Trust
Fund for Health Results Innovation […]. [H]ealth workers’
International Journal of Health Policy and Management, 2018, 7(1), 35–47
37
Paul et al
unions were involved very early in the policy dialogue,
as they were initially quite reluctant to RBF. Again, after
several workshops and one study tour to Rwanda, they
became strongly supportive of the mechanism. Finally, in
August 2009, the Cabinet (“Conseil des Ministres”) officially
declared RBF a key priority for the health sector.”13
The World Bank approach is a mainstream one. It is very much
inspired by the Rwandan experience and follows the standards
of the World Bank PBF Toolkit.14 The project was initially
conceived under a randomised control trial enabling to test
the efficacy of various PBF designs with a control group. In
2012, following implementation of PBF in the 8 World Banksupported districts, the MoH requested BTC to also introduce
a PBF component in its existing HSS programme. However,
BTC developed an alternative approach, more suited to its
ongoing intervention. Benin later submitted HSS proposals
to Gavi and the GFATM comprising a PBF component
based on the World Bank approach, which was presented as
the national approach. Since 2015, PBF has been a national
strategy however exclusively financed by donors. The World
Bank’s project coordination unit coordinates PBF activities in
29 districts, while BTC supports coordination mechanisms in
its 2 regions of intervention.
According to our field observations and interviews performed
since 2006, PBF is not a home-grown policy but is donordriven in Benin. Some former MoH top executives were
initially opposed to PBF, and it is only after intensive lobbying
from the World Bank (including workshops and study tours
in Rwanda) that they finally bought the idea. However,
ownership of PBF within and outside the MoH remains limited
to a few people (see below) – and for long, only the World
Bank approach had some kind of visibility outside the project
coordination unit and a few MoH top managers. Outside
an independent study performed in 2013 and published in
2014,10 it is only during the 2015 joint annual health sector
review, and later an inter-agency field mission organised in
June 2015, that the coexistence of two PBF approaches was
discussed by the MoH and its main partners. Consequently, a
process aimed at harmonising PBF in view of its sustainability
was initiated by the MoH and supported by BTC and other
donors. Four joint missions were organised between July 2015
and October 2016. They enabled to identify strengths and
weaknesses of each approach in view of refining a Beninese
PBF approach, and to inform a wider range of stakeholders
about PBF. However, national ownership of PBF is weak, as
testified by the fact that a number of key stakeholders within
and outside the MoH were only informed about PBF during
the second and third joint missions on PBF harmonisation in
October 2015 and July 2016.15,16 Moreover, in early 2017, there
is still no national MoH entity formally in charge of PBF, and
no domestic budget to finance it.
Design
BTC did not adopt the World Bank standard PBF design,
which relies on a project coordination unit for overall piloting,
strategic purchasing and payments; a purposely-created
external verification agency, managed by an international
consultancy firm, charged with verification, coaching and
technical assistance; and punctually hired community-based
organisations for community counter-verification (however,
38
this happened only in 2014). For coherence-sake with focus
of its initial HSS support programme as well as for budget
constraints, BTC developed an alternative ad hoc approach
through an action-research process, with strong involvement
of recipients and backing from a research institution charged
with scientific support to the programme.17 This approach
builds on existing institutions and local networks with light
external support, and uses peer review for verification. This
makes it both more integrated and owned at national and
local levels, and less resource consuming. Its main features
are described below.
Performance-Based Financing Coordination
An important feature of PBF in general is separation between
the various functions of regulation, financing, purchase of
services, service provision and data verification, thus creating
a clear division of labour between each player and contributing
to transparency.14 The BTC-supported alternative approach
has entrusted PBF coordination to a steering committee
organised quarterly at departmental (provincial) level,
consisting of representatives from the departmental health
office, donors, mayors, civil society organizations (CSOs),
health services users’ platforms (see below), the mutual health
organisations’ medical officer, and service providers. This
committee is in charge of adapting the overall PBF approach
to the local context, deciding on the level of PBF subsidies
based on results checked through verification and counterverification, and managing complaints.
Purchasing and Payment Functions
The PBF purchasing function is devoted to city councils
that take decisions and sign the PBF contracts. The latter are
also co-signed by the departmental directorate for health,
BTC, steering committee chairman, and each health facility.
To date, PBF subsidy payment is still managed by the BTC
programme, but stakeholders are now exploring how to
delegate it to a national institution.
Verification of Results
Verification of results reported by health facilities is based on
peer review through mixed team supplemented by external
stakeholders in order to guarantee independence. At health
centre (HC) level, a mixed peer review team composed of
a doctor, a midwife, a financial officer, and a nurse coming
mainly from the departmental office and an external district
leads verification quarterly. It ensures simultaneously
verification of quantities along a matrix of quantitative
indicators, and quality assessment along another matrix
of quality measures. It also draws the sample to be used for
counter-verification. At district hospital (DH) level, a mixed
peer review team coordinated by the departmental health
office and supervised by the mutual health organisations’
medical officer leads verification quarterly. It only controls
quality of healthcare since BTC has so far chosen not to
include quantitative indicators at hospital level. At the
level of the district health management team (DHMT),
quantitative indicators are quarterly pre-validated by the
local departmental directorate for health, and then audited
by another departmental directorate for health and mutual
health organisations’ medical officer.
International Journal of Health Policy and Management, 2018, 7(1), 35–47
Paul et al
Counter-Verification
Interestingly – this is to our knowledge the only example in
Africa – counter-verification of results at community level
is entrusted to health services users’ platforms, which are
networks gathering a wide range of relevant stakeholders
(representatives from local councils, CSOs/ non-governmental
organizations (NGOs), mutual health organisations,
community health workers) whose creation and functioning
has been supported by BTC for several years. They are both
in charge of controlling the effectiveness of care (based on a
sampling of HCs records) and conducting satisfaction surveys
among HCs and DH patients.
Quantitative and Qualitative Measures
Overall, the BTC approach puts a lot of emphasis on quality
of care: at HC level, bonuses calculated based on actual
quantitative indicators (number of cases times “prices”
associated to each indicator) are weighed by a qualitative index
combining assessment of technical quality and customers’
satisfaction. At DH level, only qualitative measures are taken
into account. Finally, once PBF subsidies are allocated to
each facility, about 30%-40% is kept by the facility to finance
functioning and activities, while the rest is distributed to
motivate staff (all categories included) according to a flexible
multi-criteria allocation grid.
Implementation
BTC started to implement PBF at DHMT level in the third
quarter (Q3) of 2012. Then it was progressively rolled over at
HC and DH level in the three districts of a first department
(Mono-Couffo) in the first quarter (Q1) of 2013, and then
in the 2 districts of the other department (Atacora-Donga)
in the second quarter (Q2) of 2013. The initial design
was progressively adapted with revision of indicators and
qualitative matrices in Q2 2014 and later in Q3 2015. The
criteria for calculation of DHMT subsidies also evolved: they
were initially based on implementing routine activities, but
now are also linked to the attainment of some performance
indicators by HCs in their district. The level of PBF subsidies
also increased so as to progressively align on the level of those
granted by the World Bank, which were initially much higher.
Other adaptations include gradual involvement of private
HCs and community health workers in PBF, in line with the
relevant national policy documents; as well as the introduction
of equity bonuses to provide extra incentives to disadvantaged
facilities. BTC had initially programmed a 1.5 million EUR
envelope to support PBF until the end of 2015, and then to
transfer PBF management to the World Bank. However, this
was actually not possible and BTC rose another 1 million
EUR funding in order to finance PBF until September 2017.
Table 1 shows the main evolutions in quantitative indicators
and their associated premium or price at HC level.
Influence of context is noticeable in the fact that adaptations
in implementation were particularly prompted by the
harmonisation process in view of PBF sustainability initiated
in 2015. The MoH launched this process following a
recommendation from the health sector’s joint annual review.
It was much welcome since the GFATM started to support
PBF in 19 districts in Q3 2015, and Gavi in the remaining
two districts in Q4 2015. A first joint mission aimed at PBF
harmonisation was organised by the MoH (with support
from consultants hired by BTC) in July 2015, which enabled
to carry out a consensual comparative analysis of the two
PBF approaches implemented to identify room for mutual
improvements. A roadmap for PBF harmonisation in view of
its sustainability was elaborated and later regularly updated,
and a number of general principles agreed upon. A second
joint mission, organised in October 2015, allowed setting the
path for the definition of common, consensual indicators
and quality measure matrices. Technical officers from the
Table 1. Evolutions in Quantitative Indicators and Their Associated Premium at HC Level, 2013-2016
Indicator
Price Applied in
2013 (XOF)a
Price Applied Q1 2014– Price Applied Q3
Q2 2015 (XOF)
2015–Q3 2015 (XOF)
1.
New outpaient consultaion
130
150
200
2.
Atended eutocic birth
2000
2500
3000
3.
Emergency delivery reference
2000
2500
3000
4.
Completely vaccinated children
500
600
1500
5.
Pregnant women fully immunized in tetanus toxoid vaccine (TT2-5)
300
400
1200
6.
Pregnant women who received the 2nd dose of sulfadoxine-pyrimethamine
300
400
1200
7.
Family planning acceptors (end of month)
700
800
1000
8.
Screening for tuberculosis Koch Bacillus +
2000
3500
6000
9.
Tuberculosis cases treated and cured
3500
8000
9000
10.
Referred cases arrived at the DH
700
800
900
11.
Acute severe malnutriion cases detected and clinically treated at HC
1000
12.
Acute severe malnutriion cases referred by the HC and arrived at the DH
1000
13.
Acute severe malnutriion cases treated at HC for up to 28 days and declared
cured according to criteria
2000
14.
Children born from seroposiive mothers whose delivery respected the
protocol and whose PCR 1 test was carried on
10 000
Abbreviaions: HC, Health Centre; DH, district hospital.
Source: Data collected from the BTC HSS “PASS-Sourou” programme.
a
655.957 XOF = 1 Euro.
International Journal of Health Policy and Management, 2018, 7(1), 35–47
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Paul et al
2 programmes pursued this work until a third mission
organised in July 2016. However, a number of issues were
not agreed upon at that time – notably the costing of the new
indicator matrices, and choice of common mechanisms and
institutions for verification and counter-verification. BTC
therefore decided to adapt its indicator and quality matrices,
but to keep its pricing level.
Perceptions by local stakeholders about PBF are mixed. A
qualitative survey performed in November 2013 in 2 health
districts – one supported by BTC, another one by the World
Bank – showed that after 1 or 2 years of PBF implementation,
field actors welcomed PBF – especially additional supervision
and training attached to it – and were overall satisfied with PBF.
However, they did not show a sense of ownership and viewed
it as “another project.” Local stakeholders also accommodated
the operational instructions to suit their constraints (eg,
adapted the records they were supposed to fill in). A major
issue under both approaches was perception of unfairness
of PBF. This arose from the fact that until the introduction
of equity bonuses, the subvention of all facilities, whatever
their initial endowment, were determined based on the same
indicators and quality checklist. Thus disadvantaged facilities
lacking material, equipment or staff, were automatically
penalised, despite the efforts they made. Moreover, BTC
started by giving financial incentives to DHMTs while staff
at HC level received only low premiums in the first two years
of implementation.10 However, since then, BTC has regularly
adapted its approach to address the problems raised in
departmental steering committees. PBF subsidies were raised,
qualitative matrices adapted, and equity bonuses introduced.
Moreover, contrary to the World Bank’s, the BTC programme
entails an infrastructure and equipment facility, which was
used to level out HCs in that respect.
Costs
Main cost items relate to managing the programme (as long as
it is a separate entity), generating and verifying performance
data. However, in Benin, the management costs of the
integrated PBF approach developed in the BTC programme
are not very resource consuming. Table 2 shows the annual
PBF management costs under the BTC alternative approach
as implemented in 2016, covering 5 health districts for an
estimated population of 1 759 925 inhabitants.
This amounts to 0.22 EUR management cost per person
per year. Note that it is possible to complement the current
verification strategy to reinforce its independence, for
instance by adding external controls on a sample of
verification mission, a quality control of satisfaction surveys
and community feedback activities: this would raise the cost
per person per year to 0.24 EUR.
In addition to management costs, one has to add the cost
of PBF subsidies. Actual subsidies paid over the period Q4
2012–Q3 2016 are shown in Figure 2.
In 2015, cost of PBF subsidies paid to structures amounted
to 0.36 EUR per person per year, to which transaction costs
amounting to 0.23 EUR per person per year need to be added,
bringing the total PBF cost to 0.59 EUR per person per year.
As a matter of comparison, in the eight districts supported by
the World Bank project, subsidies paid to DHs amounted to
US$0.15 (0.14 EUR) per person per year and subsidies paid
to HCs amounted to US$0.95 (0.86 EUR) per person per
year in 2015, hence 1 EUR PBF subsidies paid to structures;
cost of the external verification agency amounted on average
to US$0.15 (0.14 EUR) per person per year for verification,
plus US$0.21 (0.19 EUR) per person per year for technical
assistance over the period 2012-2015. Note however that this
includes neither the general management costs of the project
coordination unit, nor counter-verification since it happened
only in 2014.18
Effects of Performance-Based Financing on Health Systems
It is difficult to isolate the PBF effects – especially since it does
not only comprise financial premiums, but also includes a
number of contractual features and “ancillary components”
which contribute to its effects.5 In Benin as well, PBF stricto
sensu is complemented by various ancillary supports. It is
noticeable that BTC’s alternative PBF scheme is embedded
in an HSS programme, hence it was expected to act upon
Table 2. Annual PBF Management Costs Under the BTC Approach as Implemented in 2016 (EUR)
Cost
Euros
Technical assistancea
177 488
General managementb
65 670
Organisation of steering committees (2 departments)
12 196
Verification of results (peer-review)
106 714
HC level
73 176
DH level
12 196
DHMT level
12 196
Departmental directorate for health level
Counter-verification of results by health services users’ platforms (control of effectiveness of care and customer satisfaction surveys)
HC level
DH level
Total management costs per year
9147
28 965
24 392
4573
391 034
Abbreviations: BTC, Belgian Development Agency; PBF, performance-based financing; DHMT, district health management teams; HC, Health centre; DH, district
hospital.
Source: Data collected from the BTC HSS “PASS-Sourou” programme based on actual costs in 2015 and 2016.
a
Based on assumpions on the relaive share of ime spent by each technical assistant of the programme to PBF, varying from 12.5% (2 mutual health
organisaions’ medical oicers) to 60% (2 counsellors of the demand-side facility).
b
Assumpion: 10% of the programme’s overheads plus scieniic support budget.
40
International Journal of Health Policy and Management, 2018, 7(1), 35–47
Paul et al
300,000
250,000
200,000
150,000
Total HCs
Health Centres
100,000
Total District
Hospitals
DHs
Total DHMTs
50,000
Q3 2016
Q2 2016
Q4 2015
Q1 2016
Q3 2015
Q2 2015
Q4 2014
Q1 2015
Q3 2014
Q2 2014
Q4 2013
Q1 2014
Q3 2013
Q2 2013
Q4 2012
Q1 2013
0
8
9
Source: Data collected from the BTC HSS “PASS-Sourou” programme
Figure 2. PBF Subsidies Paid by BTC Since Q4 2012a.
Abbreviations: DHMTs; district health management teams; PBF, performance-based financing; BTC, Belgian Development Agency; HCs, health
centres; DHs, district hospitals.
Source: Data collected from the BTC HSS “PASS-Sourou” programme.
a
Reduction in Q3 2014 stems from change in qualitative matrix.
the various building blocks of the health system. A first
causal mechanism identified in the process of this theorydriven evaluation is precisely about comprehensive HSS at
district level. The HSS programme allows the provision of
comprehensive and systemic support to the 5 districts in
view of strengthening capacities and developing local health
systems. Such comprehensive support comprises integrated
supervision by a multidisciplinary team at each level of the
health system, from HCs to departmental management
teams; continuous in-job training; infrastructure
rehabilitation and medical equipment maintenance; reference
& counter reference; support to the local governments and
representatives from service users. The PBF components are
perfectly integrated within the vision of a strong local health
system: for instance, PBF verification missions go beyond mere
verification of results, but are also opportunities for coaching,
retro-information from communities, dissemination of good
practices, and progressive development of a quality insurance
approach. This coherent approach enables to multiply the
benefits from PBF and, according to feedback from DHMTs
and healthcare providers, has contributed to improving
quality of care. Moreover, consistent local HSS was expressed
as a hypothesis to explain that PBF had slightly better results
in the districts supported by BTC than those supported by
the World Bank (field observation during the fourth joint
mission on PBF harmonisation, October 2016).19,20
Main observed effects are explained below, as well as other
tentative causal mechanisms by which PBF impacts on results.
Infrastructure and Equipment
The BTC HSS programme comprises a facility aimed at
reinforcing infrastructure and equipment, notably to support
blood transfusion, emergency neonatal and obstetric care,
and hospital hygiene. Moreover, with the introduction of
PBF, a share of PBF subsidies is kept at facility level to finance
investment on small equipment and activities like motorbikes
to facilitate immunisation and mother & chid health outreach
activities; repair of ambulances and supervision vehicles; tiling
of operating rooms and maternity wards; accommodation for
waiting rooms, acquisition of curtains, bed sheets, and hand
washing devices contributing to hospital hygiene and patient
comfort. Choice of acquisition and/or repair of equipment are
oriented in view of improving quality of services according to
PBF matrices requirements and standards (technical quality)
as well as feedback from community surveys (perceived
quality).
Information Systems
Another building block strengthened in the context of PBF
is the national health information and management system
(NHIMS). Verification of results enabled to support facilities
in better fulfilling the NHIMS. One observes a reduction in
the gap between the obviously over-reported NHIMS data
and PBF-validated indicators over time in the five districts
supported by BTC (see Figures 3-5). Besides, the World
Bank project has supported a number of initiatives aimed
at improving data management, quality and utilisation
and thus synergy between PBF and NHIMS, among which
the implementation of the data warehouse district health
information system 2 (DHIS2) in all districts in 2015.
Human Resources
The effect of PBF on human resources is not measured
systematically. PBF has not had direct impact on health staff
hiring and deployment and overall, the districts supported
by BTC did not benefit from major health staff increase, as
illustrated in Figure 6. However, PBF had a likely indirect
0.6
NHMIS data
0.5
0.48
0.48
0.35
0.36
0.46
0.4
0.4 0
0.3
0.2
PBF validated
data
0.16
0.1
0
2012
2013
2014
2015
Figure 3. Outpatient Attendance (New Consultations/Person/Year).
Abbreviations: NHMIS, national health management information
system; PBF, performance-based financing.
International Journal of Health Policy and Management, 2018, 7(1), 35–47
41
Paul et al
120
100
98.24
80
101.24
79.05
94.75
97.6
82.18
80.39
NHMIS data
60
40
PBF validated
data
20
0
2012
2013
2014
2015
Figure 4. Fully Vaccinated Children (%).
Abbreviations: NHMIS, national health management information
system; PBF, performance-based financing.
70
60
58.61
64.17
53.91
50
40
64.06
66.02
56.29
NHMIS data
36.79
30
20
PBF validated
data
10
0
2012
2013
2014
2015
Figure 5. Attended Eutocic Deliveries (%).
Abbreviations: NHMIS, national health management information
system; PBF, performance-based financing.
effect on staff mobilisation. For instance, we have observed
that some HCs have called for support from neighbouring
HCs’ qualified staff to implement some technical activities in
order to reach PBF objectives. Two DHs in the Mono-Couffo
region took the initiative of entering into partnership with
the Faculty of Medicine to host trainees in fourth grade of
specialisation in gynaecology and obstetrics. In the context
of PBF, some healthcare professionals were hired to fill vital
gaps through service contracts (for example, a specialised
nurse was hired by a HC in the district of Bassila); however,
many did not remain at their assigned position (observation
from the BTC “PASS-Sourou” programme). More generally,
interviewed health providers reckoned that PBF forces them
to depart from routine, to be more professional and to respect
national norms.10 Peer review also helps concerned health
staff to improve their practice.
A second causal mechanism identified in the process of this
theory-driven evaluation is the fact that PBF appears to be
acting on health workers’ motivation through a complex
mechanism, all the more since beyond financial premiums,
all contractual features and ancillary components of PBF are
likely to impact on workers’ various sources of motivation.21
Bertone and colleagues22 have warned against the risk of
looking at PBF payments in isolation, without reference to the
overall remuneration of health workers. Their study confirms
that the remuneration of health workers is complex and
interrelated so that the different financial incentives cannot
be examined independently. They have assessed that in Sierra
Leone, PBF contributes to about 10% of the total income of
health workers – yet, despite this relatively low contribution,
workers’ views on the bonuses are positive while views on
salary are negative. In Benin, the average monthly salary of
clinical health staff at HC level was estimated at about 76
EUR, plus about 11 EUR in premiums in 2011 in the eight
districts supported by the World Bank.23 No such survey has
been recently performed in the districts supported by BTC,
but according to the Department of Financial and Material
Resources of the Mono-Couffo Departmental Health
Directorate, salaries have increased by 25% between 2011
and 2014 throughout civil service. In 2015, the PBF subsidies
distributed by BTC to health staff in the three districts in the
Mono-Couffo department amounted to 177 415 500 CFA
francs (270 468 EUR) – that is, an average of 157 283 CFA
francs (240 EUR) per agent, all categories of staff. At the same
time, the salary and allowances paid by the State amounted to
990 242 292 CFA francs (1 509 614 EUR), which means that
PBF financial premiums represent basically 13% of official
staff income (data obtained from the Department of Financial
and Material Resources/Departmental Health Office, and
25
20
GPs
Paedietricians
15
Gynaecologists
Surgeons
10
Other specialties
Nurses * 10
5
Midwives * 10
0
2012
2013
2014
2015
Figure 6. Evolution of Qualified Staff Per Category in the 3 districts Supported by BTC in the Mono-Couffo Department, 2012-2015.
Abbreviations: GPs, general practitioners; BTC, Belgian Development Agency.
Source: HR Department, Mono-Couffo Departmental Health Directorate.
42
International Journal of Health Policy and Management, 2018, 7(1), 35–47
Paul et al
BTC “PASS-Sourou” programme). Paul and colleagues10
already reckoned that whereas interviewed health staff often
referred to financial premiums in their discourse, actually the
latter were too weak—and “blurred” into so many others—to
have a real, lasting inciting effect. So the authors concluded
that PBF motivates health workers through other elements of
its “package”: especially, regular formative supervisions enable
to strengthen management and clinical capacities, thus play
an important role in improving performance; PBF also fosters
emulation amongst health facilities as well as improvement
in data collection and use of data for management purpose.
Moreover, it is important to note that PBF in Benin provides
financial incentives to all staff – including support staff –
which tends to favour teamwork (eg, motivate cleaners).
Populations (Health Service Users)
An important aspect of BTC’s HSS programme and
interesting feature of its alternative PBF approach is support
to organisation, capacity-building, and strong involvement
of the demand-side actors through so-called health services
users’ platforms. These platforms have been setup and
developed in view of defending the rights and strengthening
the voice of health services’ users. Their role is not limited
to PBF; they also manage complaints from health service
users, for instance. After a few years of operation, not only
their technical competences, but also their legitimacy, have
been strengthened, enabling true dialogue with healthcare
providers – which is not the case when contracting out NGOs
for punctual tasks.24
We have here, the third causal mechanism identified in the
process of this theory-driven evaluation: PBF especially
appears to be acting through increased accountability due to the
strengthened dialogue with the demand-side actors. Indeed,
the PBF approach developed was viewed as an opportunity to
implement the model of “Local Health System” as described in
the Dakar Declaration.25 This model updates the health district
and implies a multi-actor approach, shared stewardship, as
well as a focus on the right to health and increased ownership
by the local communities. The BTC alternative PBF approach
bestows involvement of health service users’ platforms in PBF
governance (through participation in departmental steering
committees) and counter-verification, plus other dedicated
tasks such as complaint management and follow-up. This has
undoubtedly reinforced their legitimacy and contributed to
strengthening the interaction and dialogue between supply
and demand for healthcare in the districts. Ultimately, this
has enabled strengthening of the local health system through
more balanced dialogue between service providers and
demand side actors, and consequently, it facilitated the search
for consensual solutions and problem solving.
indicators.19 Especially, outpatient attendance is still low in the
five districts, ranging from 14.54% to 47.14% in 2015 (coming
from resp. 12.78% and 22.28% in 2013) (PBF validated data).
Yet, a number of PBF validated indicators followed by BTC
(which are more reliable as shown above, but by definition
cannot be compared “before and after”) have improved over
the three years 2013-2015, and some districts have particularly
well improved their performance over the period, as shown
in Figures 7-9. Especially, the CBGH district experienced an
increase in attended deliveries (resp. deliveries referred from
HC to DH; family planning acceptor rate) from 33.49% (resp.
13.67%; 25.52%) in 2013 to 87.65% (resp. 97.57%; 90.53%) in
2016 (data extrapolated from the three first quarters).
As for quality improvement, Figures 10-12 show that quality
100%
80%
DOC
60%
Bassila
KTL
40%
ADD
20%
CBGH
0%
2013
2014
2015
2016
Figure 7. Proportion of Attended Deliveries at HCs Per District, 20132016a.
Abbreviations: DOC, Djougou-Ouaké-Copargo; KTL, KlouèkanméToviklin-Lalo; ADD, Aplahoué-Djakotomey-Dogbo; CBGH, Comé-BopaGrand Popo-Houeyogbé; HCs, health centres.
Source: BTC HSS “PASS-Sourou” programme (PBF validated data).
a
2016 data are extrapolated from the first 3 quarters of the year.
120%
100%
DOC
80%
Bassila
60%
KTL
40%
ADD
20%
CBGH
0%
2013
2014
2015
2016
Figure 8. Percentage of Deliveries Referred From HC to DH Per District,
2013-2016a.
Abbreviations: DOC, Djougou-Ouaké-Copargo; KTL, KlouèkanméToviklin-Lalo; ADD, Aplahoué-Djakotomey-Dogbo; CBGH, Comé-BopaGrand Popo-Houeyogbé; HC, health centre; DH, district hospital.
Source: BTC HSS “PASS-Sourou” programme (PBF validated data).
a
2016 data are extrapolated from the first 3 quarters of the year.
140%
120%
DOC
100%
Bassila
80%
KTL
60%
Health Outcomes
Overall, four years of implementation of PBF in the 5 districts
supported by BTC was associated with limited progress
in utilisation of health services, but most of all noticeable
improvements in some features of quality of care, including
user satisfaction. After correcting for autocorrelation, a recent
econometric study on panel routine data in Benin shows little
and non-significant effects of PBF (considered simplistically
as a “yes/no” variable) over a selection of quantitative
ADD
40%
CBGH
20%
0%
2013
2014
2015
2016
Figure 9. Family Planning Acceptor Rate Per District, 2013-2016a.
Abbreviations: DOC, Djougou-Ouaké-Copargo; KTL, KlouèkanméToviklin-Lalo; ADD, Aplahoué-Djakotomey-Dogbo; CBGH, Comé-BopaGrand Popo-Houeyogbé.
Source: BTC HSS “PASS-Sourou” programme (PBF validated data).
a
2016 data are extrapolated from the first 3 quarters of the year.
International Journal of Health Policy and Management, 2018, 7(1), 35–47
43
Paul et al
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
HCs KTL
HCs DOC
HCs ADD
HCs Bassila
HCs CBGH
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3
2013 2013 2013 2013 2014 2014 2014 2014 2015 2015 2015 2015 2016 2016 2016
Figure 10. Average Quality Scores at HC Level Per District, Q1 2013-Q3 2016.
Abbreviations: KTL, Klouèkanmé-Toviklin-Lalo; DOC, Djougou-Ouaké-Copargo; ADD, Aplahoué-Djakotomey-Dogbo; CBGH, Comé-Bopa-Grand PopoHoueyogbé; HCs, health centres.
Source: BTC HSS “PASS-Sourou” programme.
120%
100%
80%
DH KTL
DH DOC
60%
DH ADD
40%
DH Bassila
20%
DH CBGH
0%
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3
2013 2013 2013 2013 2014 2014 2014 2014 2015 2015 2015 2015 2016 2016 2016
Figure 11. Technical Quality Scores of DHs, Q1 2013-Q3 2016.
Abbreviations: KTL, Klouèkanmé-Toviklin-Lalo; DOC, Djougou-Ouaké-Copargo; ADD, Aplahoué-Djakotomey-Dogbo; CBGH, Comé-Bopa-Grand PopoHoueyogbé; DHs, district hospitals.
Source: BTC HSS “PASS-Sourou” programme.
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
DHMT KTL
DHMT DOC
DHMT ADD
DHMT Bassila
DHMT CBGH
Figure 12. Quality Scores of DHMT, Q4 2012-Q3 2016.
Abbreviations: KTL, Klouèkanmé-Toviklin-Lalo; DOC, Djougou-Ouaké-Copargo; ADD, Aplahoué-Djakotomey-Dogbo; CBGH, Comé-Bopa-Grand PopoHoueyogbé; DHMT, District Health Management Teams.
Source: BTC HSS “PASS-Sourou” programme.
scores have improved at all levels in the five districts. At
HC level, unweighted average quality score increased from
65.92% in Q2 2013 to 75.75% in Q3 2016. Unweighted average
technical quality score of DHs increased from 63.07% in Q1
2013 (only three hospitals included) to 89.82% in Q3 2016
44
(all 5 hospitals included). Unweighted average quality score
of DHMTs increased from 33.21% in Q4 2012 to 84.18% in
Q3 2016.
Mutual trust between populations and healthcare providers
has increased as well. User satisfaction rates have already
International Journal of Health Policy and Management, 2018, 7(1), 35–47
Paul et al
increased on average from 21% in Q3 2015 to 44% in Q1 2016
in the 2 DHs of the Atacora-Donga department, and from
20% in Q3 2015 to 40% in Q1 2016 for the three DHs of the
Mono-Couffo department (data collected by the BTC HSS
“PASS-Sourou” programme).
yet totally integrated with other processes. For instance, there
are duplications with the many concurrent missions regularly
visiting health facilities (in addition to PBF verification and
counter-verification, there are monthly DHMIS2 verifications,
regular monitoring and supervision missions, etc).
Discussion
Study Design
Contrary to the World Bank project’s initial design, BTC did
not construct its PBF scheme as a randomised control trial,
which prevents from demonstrating causal relationships
between PBF and observed results. Only “before-and-after”
comparisons can be made, and the effect of PBF cannot be
isolated since BTC’s project entails various interventions
aimed at strengthening the local health system in the five
supported districts. Since a quantitative impact assessment
does not fit the design of the BTC PBF scheme, we opted
for a theory-driven evaluation approach, and identified 3
causal mechanisms through which PBF seem to have had
effects and contribute to observed outcomes. Note that other
authors found evidence supporting these causal mechanisms
elsewhere: some have observed that PBF supported HSS (first
mechanism), including leadership, equipment and health
management and information system10,26-28; an increasing
number of studies have pointed the complex effects of
PBF over health workers’ motivation in LMICs (second
mechanisms)22,28-32; and Renmans and colleagues’5 framework
insist on the fact to consider patients as ‘benefitting principals’
in the PBF contract or scheme (third mechanism relating to
dialogue with demand-side actors). Using the Witter and
colleagues’ framework2 also helped us organise our results
in a logical way, enabling to include the context into the
analysis. However, other potential ways through which PBF
is supposed to impact on results have not been confirmed
in Benin, notably increased autonomy at facility level which
is still lagging behind – partly because of administrative
constraints, but also, as observed in some pilot districts
supported by BTC, partly due to reluctance to change and
lack of leadership in DHMTs and departmental teams.
Cost-Effectiveness
Several authors have warned about the contradiction between
the widespread use of PBF and the lack of studies of its costs
or cost-effectiveness.33-35 A recent study in Tanzania warns
against very high incremental costs of PBF (ranging from
US$540 to US$907 in the pilot experiment and from US$94
to US$261 for a national programme per additional facilitybased birth), as well as to potential substantial opportunity
costs diverting attention from service delivery.28 The BTC
alternative PBF model is not much resource-consuming since
we estimated that in 2015, its total cost amounted to 0.59 EUR
per person per year. This is far below the usual rule of thumb
of an overall output budget of US$3 (2.8 EUR) per person
per year recommended in low-income countries.14 It has to
be noted however that it is complemented by other financial
supports by BTC (including other HSS activities), other
development partners, and of course the government budget
and user fees. Since we have been unable to disentangle PBF
and attribute measurable effects to PBF, we cannot estimate
the cost-effectiveness of the BTC alternative PBF model. It can
just be mentioned that, in the context of the learning process
from the joint PBF harmonisation missions, Gavi and the
Global Fund mandated an analysis of the PBF effects based
on routine data along some selective quantitative indicators.
Despite methodological constraints, notably due to poor
quality of routine data, it shows no significant differences
between the performance of the BTC-supported districts
and those under the World Bank for most selected indicators
– but even a significantly higher PBF impact on outpatient
attendance and antiretroviral therapy initiation for pregnant
women in the districts supported by BTC – and this at a much
lower cost.19
Limitations of the Belgian Development Agency Alternative
Belgian Development Agency Approach
The BTC PBF approach is promising and not much resourceconsuming in terms of verification: overall, five full time
equivalents per year are devoted to verification of results,
that is, one full time equivalent per health district covering
on average 350 000 inhabitants. However, it also entails some
flaws. Firstly, under the current system, the independence of
peer verification may be questioned, especially compared to the
external verification agency option chosen by the World Bank,
Gavi and GFATM. Potential collusion between controllers
and controlees is yet balanced by counter-verification at
community level (which is not made in the World Bank
districts) as well as inclusion of third-parties (notably, mutual
health insurance medical officer) in verification teams.
Secondly, the difficulty in measuring technical quality of care
leads to quite cumbersome matrices and heavy measurement
processes. Thirdly, even if BTC intended to build on existing
institutions (DHMTs, departmental directorates for health,
municipalities, and health service users’ platforms), PBF is not
Sustainability Issues
Despite promising results, PBF sustainability is at risk in
Benin, both from institutional and financial points of view.
A harmonisation process is under way, but the Beninese
authorities have not yet decided on what institutional
design PBF should take in the post-donor programme era
– which is coming soon, since three development partners’
programme are ending by mid or end of 2017. It is definitely
necessary to de-verticalise PBF at the national level (as is
intended by the BTC programme), and to integrate it into
normal functioning of the health system, as a transversal HSS
strategy. However, this will not be an easy task since up to
date, PBF is not yet coherent with a number of other reforms.
Especially, the relation with the extension of the universal
health coverage scheme and quality insurance processes is
unclear. The national health financial strategy as well does
not clearly state how PBF should position itself vis-à-vis other
financing sources (central and deconcentrated government
budgets, programme funding, user fees). Moreover, the
World Bank approach – which is now implemented in 29
out of 34 districts – is at odds with decentralisation. At the
International Journal of Health Policy and Management, 2018, 7(1), 35–47
45
Paul et al
technical level too, integration of PBF requires streamlining
its design and reshaping a number of other processes
(monitoring, supervisions, etc). As for financial sustainability,
the government needs to find sufficient resources – and find
appropriate ways of channelling them – to sustain PBF after
donors have pulled out.36
Conclusion
This paper shows that an alternative, integrated PBF approach
– as compared to the mainstream one promoted by the
World Bank PBF Toolkit14 – developed with support from
BTC in Benin proves to be at the same time less resourceconsuming and promising in terms of effects, especially with
respect to local HSS (eg, local capacities, infrastructure and
equipment), improved technical aspects of healthcare quality,
and patient satisfaction. This approach is based on existing
institutions that are in charge of governance (at departmental
level), verification (through peer review, thus also enabling
to mutually strengthen capacities) and counter-verification
(through health service users’ platforms that reinforce dialogue
between supply and demand in local health systems). It is
thus a good basis for both ownership and sustainability. This
experience testifies that PBF is not a uniform or rigid model,
and opens the policy ground for recipient governments to put
their own emphasis and priorities and design ad hoc models
adapted to their context specificities.
Future phases of PBF development in Benin will need
to take account of the experience accumulated by both
interventions, so as to identify the most appropriate, efficient
and sustainable design possible. However, several issues
still need to be further studied to guide policy-making. In
particular, one observes very different patterns of evolution
between districts: some of them respond positively to PBF,
others stagnate in terms of performance. Hence, the need to
better understand the causes of these differences, and take
appropriate decisions accordingly. However, integrating PBF
within the normal functioning of local health systems, in
full coherence with other reforms (decentralisation, human
resource development, universal health coverage), remains a
big challenge.
Acknowledgements
This papers stems from collaboration between the BTCfunded PASS-Sourou programme and the “Effi-Santé”
research project funded at the University of Liège, Liège,
Belgium through the ARC grant for Concerted Research
Actions, financed by the French Community of Belgium
(Wallonia-Brussels Federation). We would like to thank two
reviewers for very useful comments on previous drafts of the
paper.
Ethical issues
The PASS-Sourou programme has been approved by the MoH in Benin as a
pilot programme, formally approving to lead research-action activities.
Competing interests
Authors declare that they have no competing interests.
Authors’ contributions
All authors contributed to collection and analysis of qualitative data through
interviews, participative observation and capitalisation of experiences, as well
46
as to data analysis and elaboration of programme theories. JPK, AEN, MK, and
JCA collected primary financial and technical data. EP performed the literature
review and drafted the first version of the manuscript. All authors contributed to
subsequent and final drafts of the paper and approved its final version.
Authors’ affiliations
1
Economie politique et économie de la santé, Faculté des Sciences sociales,
Université de Liège, Liège, Belgium. 2PASS-Sourou Programme, Belgian
Development Agency, Benin. 3Comé District, Ministry of Health, Comé, Benin.
4
Atacora-Donga Departmental Health Team, Ministry of Health, Natitingou,
Benin. 5Belgian Development Agency, Brussels, Belgium.
References
1. Meessen B, Soucat A, Sekabaraga C. Performance-based
financing: just a donor fad or a catalyst towards comprehensive
health-care reform? Bull World Health Organ. 2011;89(2):153156. doi:10.2471/BLT.10.077339
2. Witter S, Toonen J, Meessen B, Kagubare J, Fritsche G, Vaughan
K. Performance-based financing as a health system reform:
mapping the key dimensions for monitoring and evaluation. BMC
Health Serv Res. 2013;13:367. doi:10.1186/1472-6963-13-367
3. Basinga P, Gertler PJ, Binagwaho A, et al. Effect on maternal and
child health services in Rwanda of payment to primary healthcare providers for performance: an impact evaluation. Lancet.
2011;377(9775):1421-1428. doi:10.1016/S0140-6736(11)601773
4. Rusa L, Ngirabega J, Janssen W, Van Bastelaere S, Porignon D,
Vandenbulcke W. Performance-based financing for better quality
of services in Rwandan health centres: 3-year experience.
Trop Med Int Health. 2009;14(7):830-837. doi:10.1111/j.13653156.2009.02292.x
5. Renmans D, Holvoet N, Garimoi Orach C, Criel B. Opening the
‘black box’ of performance-based financing in low- and lower
middle-income countries: a review of the literature. Health Policy
Plan. 2016;31(9):1297-1309. doi:10.1093/heapol/czw045
6. Ssengooba F, McPake B, Palmer N. Why performance-based
contracting failed in Uganda – an “open-box” evaluation
of a complex health system intervention. Soc Sci Med.
2012;75(2):377-383. doi:10.1016/j.socscimed.2012.02.050
7. Van Belle S, Marchal B, Dubourg D, Kegels G. How to develop
a theory-driven evaluation design? Lessons learned from an
adolescent sexual and reproductive health programme in West
Africa. BMC Public Health. 2010;10(1):741. doi:10.1186/14712458-10-741
8. Belgian Development Agency. Dossier technique et financier
– Programme d’appui au secteur de la sante “PASS-Sourou”,
Bénin. 2014. Code DGD: NN 3014055. Code navision: BEN 13
025 11.
9. De Zutter P. Des histoires, des savoirs, des hommes. l’expérience
est un capital. Série Dossiers pour un débat n°35. Paris: Eds.
Charles-Léopold Meyer; 1994.
10. Paul E, Sossouhounto N, Eclou DS. Local stakeholders’
perceptions about the introduction of performance-based
financing in Benin: a case study in two health districts. Int J
Health Policy 2014;3(4):207-214. doi:10.15171/ijhpm.2014.93
11. Etats généraux de la santé au Bénin. Rapport général, Cotonou,
November 21-24, 2007.
12. République du Bénin, Ministère de la Santé. Plan national de
développement sanitaire 2009-2018.
13. World Bank. ‘Project Appraisal Document on a Proposed IDA
Grant in the Amount of SDR 14.9 million (US$22.8 million
equivalent) of which SDR 5.1 million originates from pilot CRW
resources (US$7.8 million equivalent) to the Republic of Benin
for a Health System Performance Project’, Report No: 53930-BJ;
April 9, 2010.
14. Fritsche GB, Soeters R, Meessen B. Performance-Based
International Journal of Health Policy and Management, 2018, 7(1), 35–47
Paul et al
Financing Toolkit. Washington, DC: The World Bank; 2014.
15. République du Bénin, Ministère de la Santé. La pérennisation du
financement basé sur les résultats (FBR) dans le secteur de la
santé au Bénin. Aide-mémoire de la mission conjointe du 12 au
16 octobre 2015.
16. République du Bénin, Ministère de la Santé. La pérennisation du
financement basé sur les résultats (FBR) dans le secteur de la
santé au Bénin. Aide-mémoire de la mission conjointe du 5 au
8 juillet 2016.
17. Jansen C, Lodi E, Lodenstein E, Toonen J, eds. Vers une
couverture maladie universelle au Bénin (Towards universal
health coverage in Benin). Amsterdam: KIT Publishers; 2013.
18. AEDES/Scen-Afrik. PRPSS. Analyse du coût de la vérification
et de l’AT dans le cadre du FBR au Bénin; Power Point
Presentation, July 2016.
19. Johnson P, Bello K, Meessen B, Korachais C. Effets des
expériences du financement basé sur les résultats (FBR) dans le
secteur de la santé au Bénin. Une analyse à partir des données
de routine collectées de 2010 à 2015. Institute of Tropical
Medicine, Antwerp, and CERRHUD for Gavi and the Global
Fund; July 2016.
20. Sambiéni NE (Dir.). Les mécanismes à l’œuvre dans la
production d’effets différenciés du financement basé sur les
résultats (FBR) dans le secteur de la santé au Bénin, rapport
général (financement: Fonds mondial). Université de Parakou,
FLASH; 2016.
21. Paul E, Renmans D. Performance-based financing in the heath
sector in low- and middle-income countries: Is there anything
whereof it may be said, see, this is new? Int J Health Plann
Manage. 2017. doi:10.1002/hpm.2409
22. Bertone MP, M Lagarde, S Witter. Performance-based financing
in the context of the complex remuneration of health workers:
findings from a mixed-method study in rural Sierra Leone. BMC
Health Serv Res. 2016;16:286. doi:10.1186/s12913-016-1546-8
23. Lemière C, De Walque D, Ayivi-Guedehoussou N, Juquois M.
Evaluation d’Impact du Financement Basé sur les Résultats,
Rapport d’analyse de l’enquête de base; 2012.
24. Ghesquière G, Hounouvi AT, Dramé ML, Gyselinck K, Paul E.
Les opportunités du financement basé sur les résultats comme
plateforme d’interactions entre l’offre et la demande pour le
renforcement du système local de santé au Bénin. Belgian
Development Agency (BTC); November 2015.
25. Community of Practice Health Service Delivery. Renewing
health districts for advancing universal health coverage in
Africa. Report of the regional conference “Health districts in
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
Africa: progress and perspectives 25 years after the Harare
Declaration”; October 21-23, 2013; Dakar, Senegal.
Peerenboom PB, Basenya O, Bossuyt M, et al. La bonne
gouvernance dans la réforme du financement du système de
santé au Burundi. Santé Publique. 2014;2(26):229-240.
Nahimana E, McBain R, Manzi A, et al. Race to the Top:
evaluation of a novel performance-based financing initiative
to promote healthcare delivery in rural Rwanda. Glob Health
Action. 2016;28;9:32943. doi:10.3402/gha.v9.32943
Bhatnagar A, George AS. Motivating health workers up to a
limit: partial effects of performance-based financing on working
environments in Nigeria. Health Policy Plan. 2016;31(7):868877. doi:10.1093/heapol/czw002
Lohmann J, Houlfort N, De Allegri M. Crowding out or no
crowding out? A Self-Determination Theory approach to health
worker motivation in performance-based financing. Soc Sci Med.
2016;169:1-8. doi:10.1016/j.socscimed.2016.09.006
Aninanya GA, Howard N, William JE, et al. Can performancebased incentives improve motivation of nurses and midwives in
primary facilities in northern Ghana? A quasi-experimental study.
Glob Health Action 2016;9:32404. doi:10.3402/gha.v9.32404
Khim K. Are health workers motivated by income? Job
motivation of Cambodian primary health workers implementing
performance-based financing. Glob Health Action. 2016;9:31068.
doi:10.3402/gha.v9.31068
Shen GC, Nguyen HTH, Das A, Sachingongu N, Chansa C,
Qamruddin J, Friedman J. Incentives to change: effects of
performance-based financing on health workers in Zambia. Hum
Resour Health. 2017;15(1):20. doi:10.1186/s12960-017-0179-2
Kalk A, Paul FA, Grabosch E. ‘Paying for performance’ in
Rwanda: does it pay off? Trop Med Int Health. 2010;15(2):182190.
doi:10.1111/j.1365-3156.2009.02430.x
Ireland M, Paul E, Dujardin B. Can performance-based financing
be used to reform health systems in developing countries?
Bull World Health Organ. 2011;89(9):695-698. doi:10.2471/
BLT.11.087379
Borghi J, Little R, Binyaruka P, Patouillard E, & Kuwawenaruwa
A. In Tanzania, the many costs of pay-for-performance leave
open to debate whether the strategy is cost-effective. Health
Affairs. 2015;34(3):406-414. doi:10.1377/hlthaff.2014.0608
Paul E. Marché de services relatif à réalisation d’une étude sur la
viabilité et la pérennisation de l’approche du Financement Basé
sur les Résultats (FBR) au Bénin – Rapport final, CSC BTC/CTB
BEN 405. Published July 18, 2016.
International Journal of Health Policy and Management, 2018, 7(1), 35–47
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