Reaching Universal Health Coverage
through District Health System
Strengthening: Using a modified
Tanahashi model sub-nationally to
attain equitable and effective coverage
December 2013
Maternal, Newborn and Child Health
Working Paper
UNICEF Health Section, Program Division
unite for children
Reaching Universal Health Coverage through District Health System Strengthening:
Using a modified Tanahashi model sub -nationally to attain equitable and effective
coverage
© United Nations Children’s Fund (UNICEF), New York, 2013
Knowledge Management and Implementation Research Unit, Health Section, Program Division
UNICEF
3 UN Plaza, New York, NY 10017
December 2013
This is a working document. It has been prepared to facilitate the exchange of knowledge and
to stimulate discussion. The findings, interpretations and conclusions expressed in this paper
are those of the authors and do not necessarily reflect the policies or views of UNICEF or of the
United Nations. The text has not been edited to official publication standards, and UNICEF
accepts no responsibility for errors.
The designations in this publication do not imply an opinion on legal status of any country or
territory, or of its authorities, or the delimitation of frontiers.
The editors of the series are Theresa Diaz and Alyssa Sharkey of UNICEF Program Division. For
more information on the series, or to submit a working paper, please contact [email protected]
or [email protected].
© UNICEF/BANA2009-00914/Noorani
ii
MATERNAL, NEWBORN AND CHILD HEALTH
WORKING PAPER
December 2013
Reaching Universal Health Coverage through
District Health System Strengthening: Using a
modified Tanahashi model sub-nationally to attain
equitable and effective coverage
Thomas O’Connell
Alyssa Sharkey
Keywords: health system strengthening, district-level, district health system strengthening,
performance, planning, resource allocation, equity, universal health coverage, child health,
health services
Comments may be addressed by email to: [email protected]
iii
ACKNOWLEDGEMENTS
We warmly acknowledge the valuable insights and editing provided on drafts of this paper by
Ulrika Baker and Dorcus Kiwanuka Henriksson of the Karolinska Institutet; and Ngashi Ngongo,
Gabriele Fontana, Kumanan Rasanathan and Julia Kim of UNICEF.
This work was supported by a generous grant from the Rockefeller Foundation.
iv
TABLE OF CONTENTS
ACKNOWLEDGEMENTS ................................................................................................................................ iv
ACRONYMS ................................................................................................................................................... 6
BACKGROUND ............................................................................................................................................... 7
REVISING THE TANAHASHI APPROACH FOR HEALTH SECTOR PLANNING .................................................... 8
Redefining stages of coverage into determinants of effective coverage ............................................... 10
Modifications made to the scope of the Tanahashi model .................................................................... 13
EQUITY ........................................................................................................................................................ 20
APPLICATION OF THE MODEL AT THE DISTRICT LEVEL ............................................................................... 21
Using District Health System Strengthening to achieve Universal Health Coverage with equity .......... 22
Case study 1: Modified Tanahashi model supports DHSS in Uganda ..................................................... 24
Case study 2: District Health System Strengthening in Democratic Republic of the Congo88 ................ 26
The enabling environment ...................................................................................................................... 27
Next steps ............................................................................................................................................... 28
CLOSING REMARKS ..................................................................................................................................... 30
REFERENCES ................................................................................................................................................ 31
ACRONYMS
CHWs
Community Health Workers
CRC
Convention on the Rights of the Child
DHMTs
District Health Management Teams
DHS
Demographic and Health Surveys
DRC
Democratic Republic of the Congo
HSS
Health System Strengthening
iCCM
Integrated Community Case Management
LMICs
Low and Middle Income Countries
LQAS
Lot Quality Assessment Survey
MBB
Marginal Budgeting for Bottlenecks
MDG
Millennium Development Goal
MICS
Multiple Indicator Cluster Surveys
MNCH
Maternal, Newborn and Child Health
MoH
Ministry of Health
PHC
Primary Health Care
UHC
Universal Health Coverage
WASH
Water, Sanitation and Hygiene
WHO
World Health Organization
6
BACKGROUND
In recent years, global initiatives and partnerships have tracked the encouraging progress made
towards reducing mortality among children under-five in many countries. 1, 2 However, this
progress and the policy adjustments made to redirect trajectories towards meeting the
Millennium Development Goal for child mortality (MDG 4), have largely occurred at national
levels.3 Lamentably, many of the countries that have made good progress in reducing their
under-five mortality rates at a national level have also experienced worsening inequities
between their wealthy and poor sub-populations,4 as well as widening disparities across other
socio-cultural group attributes such as ethnicity, geography, food security, and citizenship.5-8
This, in turn, has significant implications for finishing the “unfinished agenda” of the MDGs for
maternal and child health services, as well as for discussions on moving towards Universal
Health Coverage (UHC) as a part of the post-2015 agenda.9-11
In light of this, two questions should be answered when aiming to achieve UHC with equity.
First, are UHC policies ‘equity focused’ so the path to UHC, i.e. the polices and strategies
implemented, closes instead of widens disparities in use of services and health outcomes?
Second, are the planning and monitoring processes implemented in a pro-equity manner?
Achieving measureable progress necessitates identifying the reasons behind inequities in
efforts to attain UHC ,12 which in turn requires a comprehensive and more integrated
assessment of health system functioning,13 particularly at sub-national and service delivery
levels.14-16 It is essential to determine why certain sub-populations are less likely to receive
effective coverage, meaning coverage that ensures each person utilises needed health services
that are appropriate and with sufficient quality to have impact.17
However, efforts to understand the underlying causes of poor health outcomes and address
access and utilization gaps at these levels, including identification of bottlenecks preventing
effective coverage, have been problematic for several reasons. First, district level data relating
to health services’ coverage, access, and utilisation are often weak, unreliable, and
incomplete.18, 19 Second, with a few exceptions (mostly in middle income countries),20 tools and
information systems to obtain the disaggregated data needed to systematically assess equity of
services uptake are rarely present at the district level.21 In many cases, Demographic and Health
Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS) have served as the main source for
sub-national (often regional or provincial) data disaggregated by gender, wealth and other
socio-economic determinants of health. However the utility of these data for programme
planning and monitoring is limited as they are only available every few years and, critically, are
rarely analysed with contemporaneous household expenditure surveys to separate out financial
from non-financial barriers to the uptake of health services.22
In addition, efforts to understand UHC gaps within low and middle income countries (LMICs)
have often focused solely on the technical functioning of the health sector and have
overlooked, with a few notable exceptions, such as household wealth,23, 24 the relevance of
social determinants of health.25 Such a limited diagnostic view can lead to policy responses that
exacerbate health inequities.26, 27
7
These reasons may in part explain why health systems in LMICs typically do not succeed in
reaching the most marginalised and excluded.28, 29_ENREF_1 Indeed, evidence shows that richer
and more urban groups tend to capture a disproportionate share of public sector services and
resources in many LMICs.16, 30 However, there are some well known exceptions. For example,
Gwatkin and Ergo describe healthcare strategies based upon "Progressive Universalism," under
which the most poor and disadvantaged have access to health services, and are the first to
capture increases in health resources.11 They highlight Brazil's Family Health Programme and
Mexico's Popular insurance initiative, two efforts that offer healthcare subsidies or free
coverage to the most poor first, so as they are not left out of subsidized programs.
Equity in utilization of health services is more than a moral goal or a simple reflection of
UNICEF’s rights-based approach to child health. There is compelling evidence indicating that an
equity-focused approach also is the most effective way 28, 31, 32 to achieve UNICEF’s mission to
“advocate for the protection of children's rights, to help meet their basic needs and to expand
their opportunities to reach their full potential.”33
This paper explains the development of an approach to evaluating the capacity, and more
recently the equity, of health systems through the analysis of bottlenecks to effective coverage,
first fully described by Dr. T. Tanahashi of the World Health Organization in 1978. Though
revised over the ensuing years, Tanahashi’s approach to assess system bottlenecks is important
since it moves attention beyond access to health services and brings focus to the quality, and
thus the effectiveness, of interventions. This bottleneck analysis is foundational to UNICEF’s
efforts to reorient District Health System Strengthening (DHSS) methods towards the
attainment of equitable UHC. The sections below explain the development of a model for
analysis of bottlenecks at the district level. Included are descriptions of experiences from its
initial application as part of UNICEF’s efforts to support district health management teams in
achieving equitable, effective and universal health coverage. The discussion and conclusions
include suggestions on future directions for this work.
REVISING THE TANAHASHI APPROACH FOR HEALTH SECTOR PLANNING
While there are many national policies and guidelines for effective interventions to reduce
maternal and child mortality, these interventions do not always reach those who need them
most due to bottlenecks within and outside the health system. Even for those with access, care
may not be of good quality or be fully utilised in a manner appropriate to their needs.34 This
results in marginalised and at risk groups frequently lacking coverage, or getting less impact
from the services they do manage to access and utilise.
Tanahashi’s 1978 work to clarify the concept of health services coverage and his approach to
evaluate the effectiveness of coverage 35 forms the basis of UNICEF’s conceptual model and
approach to conducting analyses of health system bottlenecks. This seminal work put forth
several principles that remain guidelines for how health system strengthening (HSS) can achieve
national health goals effectively and efficiently. To orient HSS towards impact, Tanahashi
emphasized the importance of assessing not simply the proportion of the population that could
be covered by a health intervention, but instead emphasized the importance of “effective
coverage”, that is, coverage of sufficient quality to achieve the desired health impact.35, 36
8
Figure 1 illustrates Tanahashi’s description of coverage. To the left, the ratio of service capacity
to the target population provides the measure of nominal or potential coverage of the current
health system; that is, the proportion of the target population that could theoretically be
provided with coverage. To the right, the ratio of service output to the target population
provides the measure of effective coverage; that is, the proportion of the target population that
uses services of sufficient quality to have an impact. Utilization measures the gap, if any,
between what coverage could be in the existing system and what coverage actually is (i.e.,
effective coverage divided by nominal coverage). Tanahashi’s approach allows for assessment
of the capacity of the health system to achieve effective coverage by assessing both the
nominal (potential) capacity as well as the utilization of that capacity required to ensure
effective coverage for the entire target population.
Figure 1 Assessing health intervention coverage relevant to a target population; adapted from Tanahashi. 1978
Source: adapted from Tanahashi T. Health service coverage and its evaluation. Bulletin of the World Health
Organisation 1978; 56: 295-303.
Next, Tanahashi incorporated the notion that five measures of coverage can be used to assess
the capacity of the health system to deliver the full effect of interventions; i.e. achieve effective
coverage.32 These five measures of coverage reflect five distinct stages in the process of service
provision and permit an assessment of the potential capacity to deliver effective coverage, as
well as, “actual coverage” in terms of the health services output. He terms these measures
“availability”, “accessibility”, “acceptability”, “contact”, and “effectiveness”
coverages.37_ENREF_14
As shown in Figure 2, Tanahashi proposed examining the slope of the curve between each stage
of coverage to assess the relative size of coverage loss between each stage. A flatter curve (as
illustrated in the slope between “contact coverage” and “effectiveness coverage”) indicates a
larger loss of health system efficiency, drawing attention to an area in the process of service
provision that should be prioritized. He refers to this loss of efficiency as a ‘bottleneck’ in the
health system.
9
Figure 2 The relationships between service provision capacity, output, and utilisation
Source: Tanahashi T. Health service coverage and its evaluation. Bulletin of the World Health Organisation 1978;
56: 295-303.
In the above diagram, nominal coverage is measured by availability, accessibility and
acceptability, while actual ‘effective’ coverage is measured by contact and effectiveness. The
proportion of the target population that does not receive effective care is the gap needing to be
filled, as shown by the blue horizontal arrow.
Redefining stages of coverage into determinants of effective coverage
Early in the 21st century, there were efforts to adapt Tanahashi’s approach for use in the
Marginal Budgeting for Bottlenecks (MBB) tool. In 2002, in collaboration with the World Bank
and World Health Organisation, UNICEF developed the MBB to prioritise national strategies for
overcoming bottlenecks by evaluating various scenarios of estimated costs and potential
impacts. The MBB tool was “developed in the context of HIPC and PRSP1 in response to
requests from low-income countries to plan, cost and budget marginal allocations to health
services and to assess their potential impact on health coverage, MDGs related health
outcomes, and health outcomes of the poor.”38 For use in the MBB, researchers made several
adaptations to the original Tanahashi model.39
An early modification was to focus on determinants of effective coverage. Each determinant
was analogous to a Tanahashi stage that leads towards the goal of effective coverage. In
addition, ‘availability’ was divided into two determinants: availability of commodities and
availability of human resources.
1
HIPC: Highly Indebted Poor Countries initiative; PRSP: Poverty Reduction Strategy Papers
10
This modified model was easier for practitioners to use since it reflected the types of data that
were available and permitted the identification of bottlenecks through a step-wise approach
that evaluates six determinants of the effectiveness of coverage of an intervention:
1.
2.
3.
4.
5.
6.
Availability of essential health commodities
Availability of human resources
Accessibility of distribution points for the interventions
Initial utilization of interventions
Continuity/completeness in the continuous utilization of interventions
Quality of interventions delivered.
The first three determinants focus mainly on supply-side constraints, while the final three focus
largely on demand-side barriers. Each of the six determinants are shown in Figure 3 and
described in detail below.
Figure 3 A modified Tanahashi model based on analysing determinants of effective coverage
Source: adapted from Tanahashi T. Health service coverage and its evaluation. Bulletin of the World Health
Organisation 1978; 56: 295-303.
The six determinants currently used for assessing national level health system bottlenecks are:
Availability of essential health commodities: This represents the availability of critical health
system inputs, such as drugs, vaccines, and related commodities, in sufficient quantities to
cover the target population. The availability of commodities is critical to quality service delivery
for maternal, newborn and child health18 and has an important influence on utilization.40
Availability of trained human resources: The issue here is not simply sufficient staff, but staff
trained in providing quality and effective interventions or services. It requires that supervisory
and incentive systems be in place to motivate and enforce compliance with global and national
norms and standards. An expanding body of evidence directly links increased availability of
skilled health workers with improved maternal, newborn and child health outcomes. 41-43
11
Accessibility–physical accessibility of service delivery points: This represents the conditions
determining physical access to health services such as distance, travel time or ease with which a
client can access a facility, outreach session, or community-based provider (often expressed as
the opportunity cost).44
Initial utilisation: This represents the first use of, or contact with, services or interventions. For
example, first antenatal contact, first polio immunisation, or initial breastfeeding.
Understanding the reasons for a gap between available supply and this measure of initial
demand, relative to that supply, is critical for assessing a major area of potential system
weakness. In addition, when the analysis of the gap between supply and demand is made with
data disaggregated by critical population attributes, such as gender, wealth assets or location
(e.g. urban vs. rural), patterns of inequities begin to emerge. As Penchansky and Thomas have
described, the ‘fit between characteristics and expectations’ of providers and clients is critical
and has an important influence on utilization.45 They group these characteristics into five areas:
affordability (clients’ ability and willingness to pay), accommodation (how well providers meet
clients’ constraints and preferences) and acceptability (reflecting clients’ comfort level with the
provider and service delivered), as well as two additional characteristics that are represented in
this model by the supply side determinants above (availability and accessibility).
Continuous coverage (including appropriateness): This indicates the extent to which the full
course of contact or intervention required to be fully effective (for example, proportion of
women receiving four antenatal contacts) was achieved. In addition, a key consideration is
whether the care received is appropriate. Appropriateness incorporates two dimensions:
appropriateness of the service itself and appropriateness of the setting in which the care is
provided.46
Appropriateness of coverage
An example of inappropriate service is directing poor patients to treatment interventions with lower
impact than those accessed by richer groups. For example, substituting effective HIV/AIDS or malaria
medicines with lower costs alternatives for the poor, such as less effective ART combination or
chloroquine instead of ACTS for malaria. Achieving UHC with equity to reach the last child requires
the provision of the same needed package of services regardless of a child’s circumstances,
background or other attributes.
An example of inappropriate setting is directing poor patients to out-patient services instead of
more effective in-patient alternatives, or if they are forced to use poorly stocked public facilities that
offer limited treatment options, compared to a more effective set of interventions that richer or
more urban groups can routinely access.
UHC with equity is not achievable through a piecemeal approach in which the poor are given the
crumbs off a health services table set for the rich.
12
Effective coverage: In his original 1978 paper, Tanahashi described effectiveness coverage as
the “number of people who have received satisfactory service”; in effect, those receiving a
service or intervention of sufficient quality to achieve impact.47, 48 In the revised model, we
build on this concept and use the term effective coverage to represent the quality of the
intervention defined as the minimum amount of inputs and processes sufficient to produce the
desired health effects. For instance, complete immunization is necessary, but not sufficient, to
represent effective coverage; the child should also have received all vaccines on time, received
vaccines of good quality and potency, and all administered with a sterile syringe. The quality of
service provided is critical in determining whether coverage is effective.49 Donabedian makes
the refinement that quality has two further aspects, technical and interpersonal.50 This more indepth assessment of what constitutes a quality intervention is driving efforts by UNICEF to
develop a mixed methods approach to assessing the causes of bottlenecks to UHC. Qualitative
methods supplement quantitative analyses of factors that correlate with insufficient use of
services to measure and assess interpersonal aspects of quality based on client-provider
interactions.21, 51
Importantly, the six determinants model retains Tanahashi’s critical distinction between
nominal (potential) and effective (actual) coverage, as it highlights the gap between available
supply (service capacity) and the three determinants of service output (initial utilisation,
contact coverage, and effective coverage). Ultimately the combination of bottlenecks identified
determines the quality, and hence the effectiveness, of coverage in any given setting. As long as
these bottlenecks exist, programmatic interventions will fail to reach those in need and an
effectiveness coverage “gap” will remain, with perpetuation of inequitable health outcomes.
Removing the bottlenecks is, therefore, a mandatory step towards UHC and, by extension, to
the achievement of equitable impact.52
Modifications made to the scope of the Tanahashi model
The analysis of bottlenecks by Tanahashi was applied to discrete interventions across the health
system, without any categorization or grouping of the interventions. The current method used
by UNICEF has modified this in two ways.
First, beginning in 2004, an intervention was assigned to one of three health system delivery
channels, also termed service delivery platforms, that reflect how the intervention is primarily
provided. The three platforms of service delivery were initially designated as:
1. Family-oriented
2. Population-oriented
3. Facility-based.38
Family-oriented was mainly comprised of home-based management of childhood illnesses and
behaviour change efforts to promote hand washing, breast-feeding and child nutrition.
Population-oriented comprised outreach services in communities provided by salaried staff
who typically were based in health facilities. Facility-based care included inpatient or outpatient
services given at primary, secondary or tertiary care facilities.
13
These channels were the basis for applying the Tanahashi model using the MBB, a spread sheetbased software programme used to assess health system bottlenecks, to estimate the cost of
reducing bottlenecks, and estimate the impact achieved in terms of women’s and children’s
lives saved.
Reflecting evolutions in health system structures, particularly for countries with decentralised
systems, the three channels are now often labelled:
1. Community-based
2. Outreach services
3. Facility-based.
The change in channel labels results from the recent shift in focus for the community platform
from assessing bottlenecks to home-based care, to assessing them for integrated Community
Case Management (iCCM), a specific set of child and maternally-oriented health services
typically provided by Community Health Workers (CHWs).29, 32, 53 While there is much diversity
in the scope of practice of CHWs, ranging from volunteers focused largely on community
promotion, to paid and highly trained workers, the potential importance of iCCM in reaching
UHC with equity is growing. For the outreach and facility based channels, assessing human
resources continues to refer to paid workers who are regulated or licensed by the state.54, 55
An early application of this modification was in Ethiopia. There it was used to assess the costs
and impact of introducing a Health Extension Worker program designed to overcome identified
bottlenecks in service capacity for remote communities and low utilisation due to demand side
issues.56
The diagram below depicts the three service delivery platforms currently used, with the vertical
arrows indicating bundles of health interventions. Each vertical arrow represents a programspecific package of services, while the red crosses show which service delivery channels could
be the primary channel or channels for delivery of selected interventions within that bundle.
For example, iCCM by definition is given via the community platform; thus, a bottleneck
analysis would focus on platform constraints specific to the delivery of iCCM services. Likewise,
in the case of routine immunizations (vaccines), one would assess service delivery bottlenecks
for two channels, outreach (e.g. immunization days in communities) and the facility platform,
but typically not for the community channel as few countries permit CHWs to provide injectable
immunizations to children. Some components of newborn care are delivered through the
community channel (umbilical cord care and cleaning) and in facilities. In selected cases, as in
nutrition, all three platforms are involved. Some nutrition interventions are provided in
communities (e.g. Community Management of Acute Malnutrition), outreach (through child
health days) and in facilities (treatment of Severe Acute Malnutrition), requiring bottleneck
assessments for the relevant services primarily delivered by each of the three channels.
14
Figure 4 Bottleneck analysis for the three service delivery platforms, showing selected bundles of services
The second modification made to the Tanahashi model was the introduction of the concept of a
tracer intervention, which makes the analysis more manageable and systematic. A tracer
intervention is one that is representative of a set of health service interventions. An analysis of
health system bottlenecks that constrain the effective coverage of the tracer can reasonably be
generalised to assessing bottlenecks faced by all the interventions in that package. For example,
assessing bottlenecks to effective coverage for polio vaccine can be a proxy for assessing health
system bottlenecks impacting the entire set of immunizations a child is supposed to receive. It
is reasonable to assume that many of the platform-specific problems that impact polio vaccine
coverage will have a similar impact on measles vaccines, rotavirus vaccines, and other vaccines
given to children through that platform. Thus, bottleneck analysis of oral polio vaccine as a
tracer can serve as a proxy for all vaccines in that package (bundle).
Of note, it is critical that the service delivery platform is the same for all interventions in the
bundle from which the tracer is taken. So in the case of routine immunizations, the tracer is
used to assess all immunizations given through a single platform, facility-based contacts.
However, for immunizations delivered through outreach, the bottleneck assessment targets
outreach services, instead of the facility-based service delivery platform.
In general, for each of the three service delivery channels, certain interventions can be grouped
together to assess the strength of that service delivery channel. This takes advantage of the fact
that bundles of health interventions are typically processed similarly, and hence they are likely
to face similar health system constraints (bottlenecks) that hinder the ability to attain high
levels of effective (quality) coverage.38 The analysis of health system bottlenecks for the ‘tracer’
functions as a proxy for analysing the health system bottlenecks common to all the
interventions in the package that the tracer represents.57
15
Thus, use of the tracer greatly reduces the amount of analyses required, as each tracer is a
proxy for several related interventions
Criteria for selecting a robust and reliable tracer include:
1. Evidence of a high and measurable impact on outcomes (mortality, disease incidence, or
coverage).
2. Internationally recommended intervention;
3. Nationally relevant and appropriate; and
4. Sufficient data available for all six coverage determinants for the tracer.
Modifications due to differences in data on supply and demand
Tanahashi fully intended his model to be used in a practical way to guide systematic evaluation
of bottlenecks in service delivery and the constraining factors responsible for these bottlenecks,
and in the selection of effective measures to improve services.14 Tanahashi suggested the
model could be adapted for different diagnostic purposes by changing the denominator. For
instance, a “population-specific” analysis could be carried out on urban and rural subpopulations of the total target group, in order to assess how differences in rural and urban
service provisions could lead to different types of bottlenecks. In this example, the denominator
is the proportion of the target population living in rural areas in the first instance, and the
proportion in urban areas, in the second.35 As shown below, bottlenecks might differ
substantially depending on location. Despite having a larger proportion of the population in
rural areas, the total availability coverage is disproportionately captured by the smaller urban
population. If there were an equitable distribution of bottlenecks, the line tracing the
constraints to full coverage for the rural area would have the same shape as the line for the
total population.
Figure 5 Population specific analysis by location (rural vs. urban)
Source: adapted from Tanahashi T. Health service coverage and its evaluation. Bulletin of the World Health
Organisation 1978; 56: 295-303.
16
Tanahashi suggested that the model could also be modified to obtain information on specific
sub-groups. For example, he noted that by setting the denominator to the target population
that already had access, the analysis could be sharpened to focus on demand-side issues of
acceptability, initial contact, and effectiveness of the coverage.35 This flexibility in the model
was exploited in subsequent revisions.
An assumption in the original Tanahashi model that limits its application is that the data on
service provision at each of the five levels of coverage uses the same denominator throughout.
Moreover, it assumes the data used provides a comprehensive reflection of all services
available, private and public. In short, the denominator does not vary across the original five
stages, or the current six coverage determinants now used. In reality, much of the data used to
represent the supply side of health services (i.e., availability and accessibility) come from public
sector datasets, such as routine health information systems; thus, underestimating private
sector services provisions which are important sources of care in many countries.58-60 There are
a variety of non-state systems and providers such as Faith-Based and other Non-Governmental
Organizations (FBOs/NGOs), other private for-profit and non-profit systems, Civil Society
Organizations (CSOs), and services provided by donors and development partners (including
services provide to refugees and other displaced populations). In contrast, much of the data
used to represent the demand side of health services (i.e., acceptability, contact coverage, and
effectiveness coverage) come from household surveys that capture issues related to utilisation,
continuity of care, and quality of care by sub-populations, regardless of where they received
care. As a result, the relationship among acceptability, contact coverage, and effectiveness
coverage can readily represent drop offs in coverage (i.e. bottlenecks), whereas the supply side
bottlenecks may be more difficult to capture as private sector data on NGOs and other nonstate providers is rarely fully available.61
In our model, there is no assumption of a linear causal relationship among the three supply side
determinants: the adequacy of commodities, trained personnel and access points are usually
not directly related, though trends in their levels tend to be positively correlated. 62, 63_ENREF_62
This has two implications. First, there is no downward left to right slope across the three supply
side determinants; they can have varying and independent levels.
Second, the denominator does not necessarily include the entire target population, instead it is
the proportion of the target population that the public sector has the capacity to serve. This
reflects the reality that in most countries, while the public sector is ultimately responsible for
ensuring everyone has an equitable opportunity to use a service or access an intervention, 12 the
private sector may actually provide a significant proportion of supply side inputs (e.g.
commodities, human resources, and access points).60, 64, 65 However, under these
circumstances, provision of essential primary health care (PHC) services, such as immunization,
may be sub-optimal due to minimal profit incentives.66 The figure below shows that initial
utilisation of 50% is achieved through the public sector providing 35% of the service capacity,
and the private sector providing the remaining 15%.
17
Figure 6 Private and public sector service capacities
It would not be feasible or realistic to build excess public sector capacity that duplicates what
the private sector does, or could provide. Investments should focus on building public sector
service capacity to fill gaps that the private sector cannot, or will not, fill.
Given that data on the private sector is incomplete, interpretation of the supply side data
relevant to provision of PHC services must be made with a realistic estimate of what the private
sector does provide, and what it could provide with innovative approaches.67 It requires a
nuanced understanding of how ‘for profit’ and ‘not-for-profit’ private sector providers differ in
the scope of PHC services provided and user fees charged.68 Importantly, it takes time and
expertise to build an acceptably accurate estimate of private sector inputs, neither of which is
readily available at the sub-national level. While eventually this problem should diminish as
more complete data becomes available; for now, it is frequently the case that supply side data
will not capture all providers, and the analysis of bottlenecks to the supply of services will have
to be adapted accordingly.
As in the Tanahashi model, our model requires the denominator for the three demand side
determinants to be the same, and there must be a cascade.62 For example, it would not be
possible for the proportion of the target population receiving continuous or quality care to
exceed the proportion that sought initial care.
In the figure below, Point 1 indicates that staff shortages limits the capacity of the system, so it
can only deliver to 50% of the target population. Point 2 demonstrates that starting from initial
utilisation coverage, the slope must either be flat (all use is effective) or cascading, meaning
there is some loss of system efficiency in the utilisation of potential service capacity, resulting in
a reduction of actual (effective) coverage.
18
Figure 7 Adapting the bottleneck analysis when data on private sector provision is incomplete
Source: adapted from G. Fontana, DIVA training presentation, UNICEF, 2013
The causality analysis, assessing the root causes of identified bottlenecks, is influenced by the
distinction between supply and demand side data. Analysing supply-side factors looks closely at
health systems processes and managerial competencies, as depicted below, whilst taking into
account what the private sector does and could contribute. Analysing the reasons behind
demand-side bottlenecks requires assessment of factors such as acceptability, perceived value,
and trust from the perspectives of clients and communities. Assessing the effectiveness of final
coverage, i.e. the impact achieved, examines how well interventions adhere to global and
national quality protocols.
Figure 8 Analyses of causal factors leading to supply, demand and quality bottlenecks
Source: adapted from G. Fontana, DIVA training presentation, UNICEF, 2013
19
In summary, the assessment of bottlenecks is now categorized into supply, demand and quality
determinants of coverage, as is the assessment of the causes of bottlenecks. This approach
permits identification and assessment of the causes of bottlenecks to be adapted to data sets
that frequently fail to capture all non-state service providers. With the shift from five measures
of coverage to six determinants of effective coverage, and the flexibility to interpret results
despite lacking important data on non-state provision of health services, the Tanahashi model
provides a useful guide to assess supply and demand bottlenecks at national and local levels,
and to tease out differences across various population groups. The accompanying causal
analysis of the reasons for those bottlenecks sheds light on supply-side and demand-side issues
that result in ineffective coverage.
UNICEF has incorporated this modified model into much of its programming over the past
decade. The revised Tanahashi model, using the MBB method, has been used to assess
bottlenecks in over 50 countries.62 Applications include program specific analyses, such as
scaling up newborn care, 69 and cost-effectiveness comparisons (in terms of child deaths and
stunting events averted) between an equity-focused approach to health programming that
prioritises the most deprived communities, against a mainstream approach representative of
current national health strategies.16
EQUITY
There is growing acceptance that equity has attributes that distinguish it from equality.70-72
Equality requires everyone to have the same resources. Equity requires everyone to have the
opportunity to access the same resources. The aim of equity-focused policies is not to eliminate
all differences so that everyone has the same level of income, health, and education. Rather, the
goal is to eliminate the unfair and avoidable circumstances that deprive children of their
rights.73
This is placed into the context of UNICEF’s work in the report Re-focusing on Equity: Questions
and Answers, which states:
Equity means that all children have an opportunity to survive, develop, and reach their full
potential, without discrimination, bias, or favouritism. This interpretation is consistent with the
Convention on the Rights of the Child (CRC), which guarantees the fundamental rights of every
child, regardless of gender, race, religious beliefs, income, physical attributes, geographical
location, or other status.73
Current discussions on equity are also derived from the work on social determinants by the
World Health Organization (WHO). The WHO’s 2008 report of the Commission on the Social
Determinants of Health identified three main requirements to "close the health gap": 1)
"Improve the conditions of daily life – the circumstances in which people are born, grow, live,
work, and age", 2) "Tackle the inequitable distribution of power, money, and resources", and 3)
"Measure and understand the problem and assess the impact of action."_ENREF_35 The
analysis of health system bottlenecks can help put into practice the third requirement through
a better understanding of the factors creating health gaps.
20
The revised Tanahashi model, if used with data disaggregated by geographic area (urban vs.
rural location), wealth, or other population attributes, can identify disparities in access and use
of services. Recent work on understanding why the use of services varies across different
groups has led to assessment of drivers of inequity, such as financial and non-financial barriers,
and inequities in knowledge dissemination and awareness.74-77
However, the analysis of national survey data, while helpful in discerning major patterns of
inequities for a country as a whole, is not typically granular enough to help district managers
assess unfair and avoidable differences within their district. To reach the last child, the local
barriers to reaching the last household must be identified and removed.
APPLICATION OF THE MODEL AT THE DISTRICT LEVEL
Since 2010, UNICEF and its global, national and local partners began testing the modified
Tanahashi model, designed for use at the district level, to identify and understand critical
bottlenecks in maternal, newborn and child health (MNCH) service delivery.78 The bottleneck
analysis tools employed were not the same as the MBB used nationally, but instead represent a
collection of locally-adapted tools, at the core of which is the modified Tanahashi model.79 In
almost all cases, the costing and impact modules of the MBB have not been adapted for district
level use, though the need for such modules is being assessed.
As with the national model, the DHSS approach is based on the notion that assessing
bottlenecks can guide the development of responses and contribute to achieving UHC. By
examining disaggregated data from sub-national areas such as districts, an equity dimension
can be systematically introduced.80 When combined with a causal analysis that examines nonfinancial and financial access, and utilisation barriers at the point of service faced by at-risk subpopulations, a more equity-focused set of UHC policies, strategies, and investments can be
developed.29
The revised Tanahashi approach has formed the basis for a DHSS approach developed by
UNICEF. This flexible and outcome-based approach has been applied in more than ten countries
to identify and understand critical bottlenecks in maternal, newborn and child health (MNCH)
service delivery. It includes four steps (Diagnose, Intervene, Verify and Adjust) to help
understand inequities, and identify and respond to health system and demand-side bottlenecks
that arise at the district level.
21
Figure 9 Four components of DHSS
Source: adapted from N. Ngongo and G. Fontana, DIVA training presentation, UNICEF, 2012
While beyond the scope of this paper to discuss each step in detail, the key point is that each
builds on existing processes within the district planning cycle to improve health outcomes by
being more responsive to the specific needs of marginalised groups.81 For instance, in
Botswana, the district-based bottleneck analysis led to implementing an equity-focused plan to
scale up maternal and child survival interventions to directly address leading causes of death
among at-risk groups with low effective utilisation of PHC services.82
Using District Health System Strengthening to achieve Universal Health Coverage with equity
Frenz and Vega refer to Whitehead’s definition of inequity as the systematic “differences in
health that are not only unnecessary and avoidable but, in addition, are considered unfair and
unjust.”83 Inequities in health outcomes across population subgroups reflect varying abilities to
access and use socially provided benefits and entitlements.72 Bottleneck analysis at subnational and district levels can contribute to quality-oriented health care by identifying barriers
to equity-based programming, which if overcome, can lead to equity focused UHC (by tackling
inequitable distributions).84
Because equity-based programming requires local knowledge of deprivation and coverage
patterns, UNICEF is collaborating with ministries of health, district health management teams
and their partners, to enhance district performance for equitable health programming. UNICEF
is working with countries in sub-Saharan Africa and South Asia to adapt existing data collection
tools to assess patterns of inequity at the district level. A Tanahashi-based approach is used to
identify underlying causes and support district health management teams in using this
information to improve their equity-focused programming in a timely manner.85
The modified Tanahashi model is used to structure an initial analysis of bottlenecks in the
“Diagnose” step and in the analysis that occurs during on-going monitoring in the “Verify” step.
The information gleaned from these assessments supports district health management teams
and their partners in setting priorities and targets for equity-based programming in a
systematic and informed manner. Through the bottleneck analyses inequities are identified and
22
responses are designed to develop pro-equity strategies and activities that can be integrated
into annual district operational plans.
The figure below illustrates how the bottleneck analysis can be applied to an equity-focused
sub-national bottleneck assessment.
Figure 10 Applying the bottleneck analysis to sub-national areas
Source: adapted from N. Ngongo and G. Fontana, DIVA training presentation, UNICEF, 2013
The figure shows the initial division of the analysis into the assessment of supply and
demand-side data for a single health intervention. This is a granular refinement of Tanahashi’s
population-specific analysis in which he independently assessed bottlenecks for rural and urban
sub-populations. In this example, two sub-national areas are compared to assess differences in
supply-side and demand-side bottlenecks, as well as in the quality of the interventions. This
analysis is from work in Uganda (see case study below) where district data is generated using
Lot Quality Assessment Survey (LQAS) techniques.
LQAS is a small sample survey technique currently being evaluated to determine whether it is a
cost-effective way to gather sub-national data.86 LQAS allows an estimate of the likelihood of
the actual coverage falling between two thresholds, such as 50% and 80%, and is not typically
used to provide a point estimate of coverage (e.g. 75%). In the figure above, when the LQASderived indicator exceeds the upper threshold, it is assigned a green colour. Falling within the
thresholds is marked yellow, while falling below the threshold is marked red. In this way, critical
bottlenecks (the red rectangles) are prioritised for urgent action; yellow ones for continued
effort, and green ones are considered satisfactory for the time period being assessed. As
progress occurs, more of the coverages should move into the green zone, prompting an upward
revision of the thresholds.
23
LQAS has been increasingly used to assess patterns of inequity for sub-national planning.87 In
the figure below, the district averages are assigned color-coded numbers, with LQAS derived
values shown for its three constituent sub-districts. It is clear there are differences between
areas A, B, and C that may lead to different strategies for overcoming identified bottlenecks.
For instance, Sub-district C has a major problem with geographic access relative to A and B,
which may point to an urgent need to scale up access points for ARV treatment. Sub-district B
may instead decide to concentrate on removing financial barriers to starting services, while A
may focus on increasing the number of person adhering to treatment protocols.
Figure 11 Variances in bottlenecks for effective use of ante-retroviral medicines in three sub-districts
Source: adapted from N. Ngongo and G. Fontana, DIVA training presentation, UNICEF, 2013
Case study 1: Modified Tanahashi model supports DHSS in Uganda
In 2011, the Ugandan Ministry of Health (MoH) requested UNICEF’s support to operationalize
their Health Sector Strategic and Investment Plan 2010/11-2014/2015 (HSSIP) through two
district-based projects: Community and District Empowerment for Scale-Up (CODES) and Health
for Poorest Quintile/Population (HPQ/HPP). Workshops, backstopped by UNICEF and run by
local non-governmental organisations, engaged District Health Management Teams (DHMTs) in
assessing local data, identifying bottlenecks and their causes, and developing solutions
appropriate to decision and fiscal space limits. Community interviews elicited perceptions on
financial and social barriers to accessing health services in order to better understand the
causes of the demand-side bottlenecks.
Using the information gathered, participating DHMTs identified key barriers to health, nutrition
and water and sanitation interventions at the facility, outreach and community levels of service
delivery, as well as their underlying causes. These included illegal fees and bribes demanded of
mothers for services that are supposed to be free, persistent stock-outs of anti-malarials and
zinc, lack of community awareness of hand-washing and sanitation practices, lack of familiarity
with pneumonia, malaria, and diarrhoea danger signs among both mothers of children under
five and community health workers, and insufficient outreach sessions.
The example below shows preliminary data on inter-district differences in immunization using
the LQAS approach. While the data may not be fully accurate since the LQAS data needs to be
carefully validated and verified by other methods, it does strongly indicate that actionable data
can be obtained through the use of a Tanahashi-based approach to sub-national assessments of
inequities. For instance, districts A, D and E face chronic staff shortages due to low staff
24
retention, while more urban districts have better staffing. In part, this is due to inequitable
investments, with some districts receiving more financing for human resources. Another factor
is illegal user fees, which community members in all five districts identified as one of the
greatest barriers to use of services, particularly in the case of poorer households.
Figure 12 Comparison of preliminary data on full immunization coverage in Uganda
Source: adapted from presentation on Community and District Empowerment for Scale-up in Uganda, UNICEF,2013
Based on these and similar findings for other tracer interventions, as a direct result of the
bottleneck analysis, the DHMTs developed locally tailored interventions they identified as
feasible, such as improving initial utilisation and effective coverage through radio spots, VHT
quarterly meetings chaired by local political and community leaders, increased messaging via
churches/mosques, implementation of the SMS-based and community-empowering “uReport”
monitoring system, expanded use of an SMS-based ‘mTrac’ system to report human resources
and stock shortfalls, and complete birth registration for children under five. In addition, each
facility will be regularly assessed by managers and community members (via SMS-based
community oversight) to ensure the fee schedule is visible and complete, and that staff
members wear name badges to improve accountability for the care they provide.
25
Case study 2: District Health System Strengthening in Democratic Republic of the Congo88
UNICEF is also working with the Ministry of Public Health (MoPH) and district health
management teams in the Democratic Republic of the Congo (DRC) to use DHSS to
operationalize the strategies of the National Health Development Plan (NHDP) 2011-2015.
Achieving the NHDP objectives is being pursued through increasing service capacity and
utilisation using a mix of public and non-state providers, the latter largely consisting of Faith
based Organization.
A core NHDP objective is strengthening district health management capacity and information
systems. UNICEF’s Child Survival and Development Programme and the Health for the Poorest
Populations Project were entry points for this work, under the leadership of the MoPH. UNICEF
and the MoPH have engaged key partners including World Health Organisation, World Bank,
European Union, the German Agency for International Cooperation, Management Sciences for
Health, and the University of Kinshasa, to put the decentralised monitoring process on the
agenda of health systems strengthening in 207 priority districts.89
A phased approach to implementation started with field-testing of the methodology and tools
in one district in March 2012, and then followed in May 2012 with methods refinement and
implementation in five districts across five provinces. In a first phase district, bottleneck
analysis was used to examine fifteen interventions: nine in health (antenatal care, preventing
mother to child HIV transmission, skilled birth attendance, home-based newborn care,
immunizations, bednets, CCM for diarrhoea); two in nutrition (exclusive infant breastfeeding,
complementary feeding); two in WASH (hand-washing, improved sanitation); one in child
protection (birth registration); and one in education (quality primary education).
Data were collected through health management information system (HMIS) and health facility
surveys to identify supply-side bottlenecks (commodities, human resources, geographical
access); while household surveys (using LQAS) and qualitative studies (using focus groups and
key informant interviews) identified demand-side bottlenecks (utilisation, continuity, quality,
and environmental factors such as financial and non-financial barriers).
The main bottlenecks identified were supply related: 1) districts lack essential drugs because of
inadequate health financing, 2) health workers (in adequate numbers) lack the necessary skills
since training curricula have not been updated through the many years of war and political
instability, and c) geographic access is a critical problem due to a combination of low population
density and lack of adequate infrastructure, except for programmes that have outreach
activities.88
26
Figure 13 Modified bottleneck analysis as part of equity-focused DHSS, 2012 Source: ‘Updates on implementation
of L3M of Mores in the Democratic Republic of Congo’, UNICEF, 2013
The result is major variances in effective coverage across the districts, as a function of the
varying levels of services capacity and services utilisation within each district. To address these
challenges to equitable and effective use, the districts are working with partners to support one
plan and one budget to address prioritised bottlenecks; mobilise resources to procure
equipment and medicines; increase the frequency of outreach activities; establish an integrated
training strategy to retrain staff in relevant MNCH issues (leveraging existing vertical program
funds); and routinely verify implementation to track progress and coordinate multi-partner
efforts to adjust as necessary.89
The enabling environment
Beginning in 2008, the initial work to assess equity of health service utilisation across different
sub-populations showed that progress towards the MDGs, while impressive, had in many cases
increased the gap between rich and poor, urban and rural, and between other sub-populations.
This was highlighted in UNICEF’s 2010 seminal report, Narrowing the gaps to meet the goals.28
The core message of this report was that the MDGs can be reached, both more quickly and with
greater equity, if the policy path to UHC focuses on investments that help the most
disadvantaged catch up in terms of utilisation of quality and appropriate services. This led to a
more systematic and expansive approach to the causal analysis that follows the identification of
bottlenecks.
Originally, much of the work centred around technical solutions to supply and demand-side
bottlenecks. The focus was on strategies to improve commodities and human resource
27
management, ways to extend access to service points, and steps to remove user fees and
knowledge barriers that constrained use of available services. As DHSS efforts advanced, it
quickly became apparent there was a need to systematically assess and resolve issues of
management skills and capacities.81 As a result, much of the DHSS efforts in Botswana, DRC,
Uganda and other countries include extensive efforts to build management competencies.
Strategies include strengthening supervisory, data management and problem solving skills, and
improving management of resources.82, 88_ENREF_78
An evaluation of social factors is also increasingly included in the assessment of national and
sub-national health systems bottlenecks. With the growing body of research on social
determinants, environmental factors are recognised as critically influential in making progress
towards UHC.27, 90, 91 Linking work on social determinants to HSS and DHSS focuses efforts on
improving the enabling environment in which DHSS occurs. The enabling environment can be
defined as the current policies, strategies, budgets and social factors (social, cultural and
economic barriers that perpetuate health inequities) that constrain the decision space of
district health managers and their teams in efforts to effectively address major bottlenecks to
UHC. Creating more decision space for DHSS involves many factors, but a core thrust is
advocating for “transparency and managing for results and accountability, through resultsbased public budgeting and evidence-based policy-making.”92
Next steps
To date, UNICEF has conducted bottleneck analyses within the DHSS approach using the
modified Tanahashi model in several countries including Botswana, Democratic Republic of
Congo (DRC), Mali, Malawi, Niger, Nigeria, Sierra Leone, Uganda and Zambia. In all countries in
which the approach has been implemented to date, positive feedback is emerging on how the
process has increased DHMT capacity and willingness to monitor for results, and lead to
improved operational plans and decision making. In DRC, for example, the information
obtained via the bottleneck analysis supported a reprogramming of activities to maximize
efficiency and effectiveness.89 The approach is also proving to be a powerful advocacy tool to
demonstrate to donors and finance ministry officials why channelling resources to address
bottlenecks leads to results. For instance, in March 2012 a district in Uganda used their analysis
to secure increased funding from development partners in order to resolve major bottlenecks.93
These initial experiences in DHSS underscore the importance of including an analysis of the
broader social context within which inequities are generated, and expanding the decision space
by improving the enabling environment. They also highlight the importance of both financial
and non-financial barriers (including cultural/religious factors, maternal education, negative
perceptions or distrust of services, and perceptions of value-added services) that might be
underlying causes for insufficient demand or enabling factors that might promote effective
coverage.21, 22
Applying a framework to the causal analysis of bottlenecks assists DHSS efforts to incorporate
social health determinants. One useful framework is described by Franz & Vega; it considers the
broader social context and can inform future iterations of local bottleneck analyses and DHSS
work.83 Based on a review of theoretical literature and evidence generated through health
systems research on equity of access as it relates to UHC, their framework highlights the
28
complexity of the multi-stage process by which individuals recognise the need for health care,
find available and acceptable services, make contact and ultimately receive an appropriate
intervention. It builds on Tanahashi’s earlier model, incorporating several social dimensions and
linking them to the goal of UHC.
Figure 14 UHC and Equity of Access. Effective coverage for all health needs as a result of supply and demand “fit”
Source: Frenz P & Vega J. Universal health coverage with equity: what we know, don’t know and need to know.
Background paper for the global symposium on health systems research. 16-19 November 2010, Montreux,
Switzerland.
The framework situates the dimensions of equity of access to UHC within universal health
policies (including financing, manpower, organisation and education) and social policies
(including those relating to education, housing, employment and work conditions, and cultural
issues). The model illustrates the relationship between these policies and characteristics of the
health delivery system, as well as characteristics of the population, and how these contribute to
the realisation of UHC with equity.
UNICEF is using this model and other recent research on equitable pathways to UHC to further
adapt the Tanahashi approach to determining causes of bottlenecks to the equitable uptake of
primary health services at sub-national levels. The core methodology is based on the
framework proposed by Frenz and Vega for analysing health systems and a Tanahashi approach
linked to an assessment of the social determinants of health.83 Building on this equity-focused
DHSS methodology, UNICEF seeks to incorporate the systematic use of data from this diagnostic
process to support District Health Systems Strengthening (DHSS) efforts, and to generate
evidence on social and financial inequities in order to influence national and sub-national
political processes and policies. To accomplish this, UNICEF wishes to develop and test an
29
innovative analytical approach, robust enough for use in a wide range of contexts. The goals
are to integrate qualitative and quantitative methods to assess and address causes of health
system bottlenecks and barriers to UHC using selected tracer interventions, and to monitor
progress towards their resolution.21, 22, 51
CLOSING REMARKS
There are numerous publications on diagnostic approaches to delineating access barriers due to
inadequate supply, insufficient demand, and out of pocket fees at the point of service. Some
research also addresses the burden of indirect fees and other opportunity costs. And there, in
terms of a comprehensive and holistic diagnosis of barriers to UHC, it tends to stop. Few
authors expand the diagnosis to include non-financial institutional and social barriers to UHC,
though Di McIntyre, and Frenz and Vega, have made vital contributions. Fewer researchers still
have tried to apply a truly comprehensive view to sub-national monitoring and planning
processes to deliver UHC.
Yet, anecdotal evidence and a few empirical studies show that inequitable patterns of
bottlenecks, both institutional and individual, are serious impediments to UHC with equity. To
support equity-focused programming, UNICEF uses the modified Tanahashi approach in more
than 50 UNICEF programme countries for national and sub-national system strengthening
efforts to achieve UHC. The evidence to date is consistent and clear: health interventions must
have quality to be effective; that is, to achieve impact in terms of reducing preventable illness,
suffering and death.94
The Tanahashi model in its current revised form supports identification of critical health system
bottlenecks that restrict UHC. Once bottlenecks are identified, a causal analysis (incorporating
both qualitative and quantitative methods) is critical to understanding why bottlenecks exist
and to inform strategic responses in order to achieve UHC with equity. Underlying causes may
be financial or non-financial, or related to broader contextual factors, such as the social
determinants of health. Addressing these requires multifaceted and synergistic solutions that
often cross health system functions, and involve community participation and intersectoral
action.
On going monitoring and action to redress bottlenecks requires this stronger and more
systematic assessment of district level causes. This causal analysis remains grounded in
Tanahashi's original approach to assessing insufficient accessibility, availability, acceptability,
contact, and effective coverage of health services, but has been expanded to identify
management and financial causes, and factors that differ among subpopulations which seem to
correlate with observed inequities. Further, part of the movement towards UHC can involve use
of real-time monitoring to provide a basis for actionable information, and a shift towards a
more proactive and results-based approach to assessing and removing barriers. UNICEF has
several initiatives exploring how Rapid SMS and other mHealth and eHealth approaches can
improve the flow of data, help pinpoint and monitor inequities in access of and use of services,
and improve the quality of services that are received.95 This will help reorient health
programmes to better account for equity and social determinants of health.
30
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