Can a standards-based approach improve access to and quality of primary health care? Findings from an end-of-project evaluation in Ghana
Can a standards-based approach improve access to and quality of primary health care? Findings from an end-of-project evaluation in Ghana
Christina MalyID 0 1
Richard Okyere Boadu 1
Carina Rosado 1
Aliza Lailari 1
Bernard Vikpeh-Lartey 1
Chantelle Allen 1
0 Monitoring, Evaluation and Research, Jhpiego, Johns Hopkins University Affiliate , Baltimore, MD , United States of America, 2 Department of Health Information Management, University of Cape Coast, Cape Coast, Ghana, 3 Strategy & Analytics, Deloitte Consulting, LLP, Rossylyn, VA, United States of America, 4 Strategic Information and Evaluation, Elizabeth Glaser Pediatric AIDS Foundation , Washington, DC , United States of America, 5 Independent Development Consultant , Takoradi, Ghana, 6 Technical Leadership and Innovations, Jhpiego , Johns Hopkins University Affiliate , Baltimore, MD , United States of America
1 Editor: Samiksha Singh, Public Health Foundation of India , INDIA
Jhpiego implemented a 5-year project to strengthen the Community-Based Health Planning and Services (CHPS) model in six coastal districts of Ghana's Western Region. The project utilized a quality improvement approach (Standards-Based Management and Recognition [SBM-R]) to strengthen implementation fidelity of the CHPS model. This article presents findings from an end-of-project evaluation comparing quality, access to care, and experience of care in intervention and comparison CHPS zones.
Funding: This project, evaluation and most of the
writing activities were funded by Jubilee Partners
through Ghana Tullow LTD agreement number
operations/west-africa/ghana) which was awarded
to Jhpiego Corporation. Additional funding for
development of this manuscript was provided by
A non-equivalent, posttest?only, end-of-project evaluation compared 12 randomly selected
intervention zones with 12 matched comparison zones. Data from standards-based
assessments measured provision of care in three categories: community engagement, clinical
services, and facility readiness and management. Access to and experience of care were
assessed using a household survey of 426 randomly selected community members from
the selected CHPS zones. Bivariate and multivariate analyses were conducted to compare
performance on these measures between intervention and comparison CHPS zones.
Overall, intervention zones outperformed comparison zones on achievement of standards
(83.6% vs 58.8%) across all three assessment categories, with strongest results in
community engagement (85.7% vs. 41.4%). Respondents in intervention zones were more than
twice as likely to have received a home visit from a community health officer, three times as
likely to have a home visit from a community health volunteer, and more likely to have
Jhpiego (https://www.jhpiego.org/). The funders
had no role in study design, data collection and
analysis, decision to publish, or preparation of the
Competing interests: Please note this study was
funded by Jubilee Partners as part of the overall
project award; the funding agency did not have a
role in the study design, data collection, analysis or
the decision to submit for publication. The funding
does not alter our adherence to PLOS ONE policies
on sharing data and materials.
attended a health talk (41.9% vs. 27.0%). Client experiences of care were reported as
positive in both study arms.
The evaluation demonstrated improved access to quality care; however, there were very
few differences in client experience of care between intervention and comparison zones. As
Ghana and other countries are committed to scaling up universal health care, a pragmatic
approach such as SBM-R could prove useful to engage both facility- and community-based
service providers, as well as community members, to improve provision of care.
Ghana has passed several health-related laws in line with global and/or regional priorities [
and introduced a national health insurance scheme, while moving out of low-income status as
a country in 2010 . In addition, the crude maternal mortality ratio has dropped by nearly
50% over the last 25 years (634 per 100,000 live births in 1990 to 319 in 2015)  and over 90%
of women attend at least one antenatal care visit [
]. Despite these improvements, Ghana
made only slow progress on Millennium Development Goals 4 and 5, reducing under-5
mortality and maternal mortality, respectively [
], and significant inequities in income and health
outcomes remain [
]. To address these challenges, Ghana has prioritized universal
provision of primary health care in line with the Ouagadougou Declaration on Primary Health Care
and Health Systems in Africa  and Sustainable Development Goal 3, which includes
provision of universal health coverage (UHC) [
]. To operationalize this goal at the national level,
Ghana began scaling up Community-Based Health Planning and Services (CHPS) [
CHPS model delivers health care directly to the household and community levels by placing
community health officers (CHOs) in communities and using community-based approaches
for delivery of primary health services.
Sustainable Development Goal 3 is focused on universal access to care, and also on
highquality care; thus, as Ghana and other countries strive for UHC, an emphasis on quality of care
is needed [
]. As coverage of care expands, greater understanding of the quality of health
services will be required, both in terms of the provision of care and the client experience of
A good example of the increasing global commitment to quality of care and valuing the
client?s experience of care is the World Health Organization?s new quality of care framework for
maternal and newborn health [
]. The framework articulates the importance of provision of
care and client experience of care within the health systems building blocks. Ensuring the
quality of care through this framework may include implementation of quality improvement
initiatives with increased monitoring of progress, as well as engagement and feedback on clients?
experiences of care [
Audit and feedback have been shown to improve quality of care [
]. In this approach, an
individual?s or facility?s practice or performance is compared to professional standards or
targets (audited), and the results are fed back to the individual or facility. The aim of this process
is to engage health care providers in identifying and addressing gaps to achieve the required
professional standards. This approach formed the cornerstone of the Supportive Technical
Assistance for Revitalizing CHPS (STAR CHPS) project that was initiated in 2011 in six coastal
districts of Western Region, Ghana. This paper presents results of an end-of-project evaluation
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in 2015 that assessed access to and quality of community-based primary health services
provided in STAR CHPS-supported sites, compared to non-intervention sites.
The CHPS model
Based on the positive findings of operations research conducted by the Navrongo Health
Research Center in the Upper East Region between 1994 and 1996, the Ghana Ministry of
Health (MOH) launched CHPS in 1999 as a national health policy initiative [
]. The Ghana
Health Services (GHS) mobilized community support for CHOs posted to a CHPS zone to
deliver primary health care at the household and community levels to improve geographic
access. A CHPS zone encompasses up to 5,000 persons or 750 households and is usually
comprised of several communities [
]. The community participates in CHPS through an elected
community health management committee (CHMC) and by nominating or serving as
community health volunteers (CHVs) in their CHPS zone. CHPS is an important strategy to
improve geographic access to primary health care and maternal and child health services,
particularly for remote and rural populations [
]. Table 1 describes the roles and responsibilities
of the various members of the CHPS model outlined in the national guidelines [
Ghana has demonstrated a national commitment to implementation and scale-up of the
CHPS strategy by investing in infrastructure, creating and expanding a cadre of community
health nurses through community health nursing schools, and re-aligning CHPS districts to
electoral areas [
]. However, CHPS scale-up has been slower than anticipated. In 2013, when
the STAR CHPS project was being designed, only about 22% of CHPS zones were reported by
the MOH as being functional [
]. Nyonator [
] labeled this the CHPS ?implementation
In 2011, Jhpiego received a 5-year grant from the Jubilee Partners (Tullow Oil, Kosmos
Energy, Anadarko Petroleum, Ghana National Petroleum Corporation, and Petro SA) to
implement the STAR CHPS project. The project partnered with the GHS Western Regional
Health Directorate to support implementation and scale-up of CHPS activities in 62 CHPS
zones across all six coastal districts of this region. The goal was to increase access to quality
primary health care (Fig 1) by improving the quality of services and strengthening community
A community health nurse, enrolled nurse, or midwife trained in the
CHPS model and placed in a CHPS zone to work with communities to
provide basic primary health care.
Community members elected by chiefs and community opinion leaders.
CHMCs serve as the primary liaison between community members and
CHOs and are responsible for the welfare of CHOs. CHMCs also select
and supervise CHVs.
Laypersons in the communities elected by chiefs, elders, and CHMC
members at a formal community forum, or durbar. CHVs support the
CHO by providing health education and conducting community outreach
and home visits where they provide health education and referrals and/or
treat minor ailments. They receive technical supervision from the CHO
and management oversight from the CHMC.
District-level health managers (e.g., district health directors, public health
nurses, health information officers) who work together to provide
technical leadership, management, and expertise to ensure delivery of
facility- and community-based health services in the district.
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Fig 1. STAR CHPS project design.
engagement. The STAR CHPS project was designed to close the ?implementation gap? by
improving fidelity to the national CHPS model, especially community engagement and
support components. The project built the capacity of all members of the CHPS team to support
implementation and service delivery, and utilized a quality improvement approach to
strengthen fidelity to the CHPS model and to ensure that all implementation steps and
milestones of the model were achieved [
]. The assumption underlying the project?s approach was
that improving quality of care would also improve client experience of care, and improving
fidelity to the CHPS model would result in a greater number of clients having access to
primary care [
Improving quality of care. This project applied the Standards-Based Management and
Recognition (SBM-R) audit and feedback quality improvement approach [
]. SBM-R uses
continuous audit, action planning, feedback, and recognition of progress to improve service
quality. It engages health service providers and managers to work together to address gaps in
performance. The theoretical foundation of the SBM-R approach is fully described by
Necochea and colleagues [
Traditionally, this approach has been used in facility-based settings; this was the first time
SBM-R was applied to a community-based model. STAR CHPS and GHS staff jointly
implemented SBM-R with CHOs, CHMCs, CHVs, and DHMTs.
Over the 5-year life of the project (2011?2016), the following four-step process was
followed: 1) set standards?set 188 standards with 1,242 verification criteria based on an
extensive desk review of national guidance and strategies to consolidate expected clinical services,
facility readiness and management, and community engagement for CHPS; 2) implement
standards?conducted assessments, action planning, support visits, and capacity development;
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3) measure progress?re-assessed; and 4) provide recognition?provided reward and
recognition events and certificates [
Building capacity of health service providers. To address the specific service provider
capacity gaps identified by the initial SBM-R assessments, the STAR CHPS and GHS staff
delivered a modified version of the GHS-recommended 12-day course for CHOs that included
orientation on the CHPS model, community engagement, and specified clinical services. After
training and assessments, GHS and STAR CHPS conducted supportive supervision visits to
follow up on progress and support CHOs to address performance issues that had been
identified. In addition, the project and GHS facilitated monthly district-based CHOs meetings to
share progress and lessons learned.
Strengthening community mobilization and participation and building capacity of
CHMCs and CHVs. STAR CHPS supported each of the DHMTs to work with the chiefs and
community opinion leaders to establish or strengthen the community-related structures,
including identification and support of CHVs and establishment of CHMCs in each CHPS
zone, in accordance with national policy and implementation guidance.
Once CHVs and CHMCs were selected and formally introduced to their communities, the
project oriented them on the CHPS model and various tools and approaches to be used in
their work. CHVs learned how to conduct home visits in keeping with the GHS national
policy and STAR CHPS provided home visiting bags to all CHVs with simple supplies and
A posttest only, non-equivalent control group design was adapted for the formal evaluation at
the end of the project. Comparison groups were selected from districts adjacent to the six
project districts within the same region.
The project encompassed 62 CHPS zones. Nineteen CHPS zones that had received less
than 2 years of project support and five urban CHPS zones were excluded from the sampling
pool. The remaining 38 zones were stratified by duration of project support (3 or 4 years), and
12 were randomly sampled to ensure proportional representation by duration of support.
Frequency matching on the following three criteria was used to randomly sample an additional 12
comparison CHPS zones from similar districts in the same region: 1) number of years of
existence; 2) staff-to-population ratio; and 3) existence of a brick-and-mortar facility, as the CHPS
model can be implemented with or without a physical facility. However, for the purposes of
this evaluation we only included those with a physical structure.
A household survey was conducted for the purpose of gathering data on access to and
perceptions of quality of care provided through CHPS zones. For this survey, three communities
from each of the 24 sampled CHPS zones were selected. The community in which the CHPS
zone facility was located was purposively selected and two other communities within the
catchment area were randomly selected. Within each zone, 18 households were surveyed across the
three selected communities, for a maximum total sample size of 432. The sample size was
calculated to detect a 15% absolute difference in the proportion of survey respondents who
reported receiving high-quality care at intervention zones versus comparison zones with 80%
power and the type 1 error fixed at 5%. To account for possible confounding due to similarities
among clients being served by the providers from any one CHPS zone, within-facility
correlation of responses was assumed to be 0.01 based on routine monitoring data from similar
projects. Data were collected in the 24 sampled CHPS zones over 3 weeks in October and
November 2015. Please see S2 Tool Household Survey for full details.
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(n = 12) (n = 12)
1: 1,920 (636)
1: 1,588 (830)
(n = 215)
SBM-R assessment tool, data collection, and analysis
The SBM-R portion of the study included all members of the CHPS model?CHOs, CHVs,
CHMC members, and DHMTs. Current or retired GHS staff conducted the SBM-R
assessments after participating in a 4-day workshop. Training topics included research ethics and
informed consent, standard study operating procedures, standardized observations and
scoring for the SBM-R assessment tool, and use of a tablet-based application for SBM-R assessment
data collection. Thirteen of the 15 data collectors had previously conducted SBM-R
assessments for routine project activities. GHS staff were assigned to collect data in CHPS zones
where they had not previously worked or done assessments for the project.
The SBM-R assessment tool, which was the same tool used during routine project
assessments, covered 44 areas comprised of 188 performance standards and 1,242 verification
criteria (Table 2) across all four groups of participants. For the purpose of this evaluation, the
criteria were organized into three thematic categories: 1) community engagement; 2) facility
readiness and management; and 3) clinical services . Interviews, role plays, and
observations of patient care and other service provision were used to determine if each verification
criteria should be scored ?yes? or ?no.? When a CHMC did not exist or there was no CHV in a
CHPS zone, the assessors marked the criterion as ?no.? Overall scores for each CHPS zone
were calculated as the percentage of verification criteria scored ?yes.? Scores for each of the
three thematic categories were similarly calculated (Table 3). Table 4 presents percentage of
CHO, community health officer; CHV, community health volunteer; CHMC, community health management committee; CI, confidence interval.
a Multivariate model controlled for facility maturity, staff-to-population ratio, and clustering at the district level.
b For pragmatic purposes readiness (e.g. infrastructure, equipment, medicines) and management (e.g., data collection, reporting and use; financial and logistics
management) were grouped together and a summary score was calculated
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Mean % of Verification Criteria Achieved
(n = 12) (n = 12)
CHO, community health officer; CHV, community health volunteers; CHMC, community health management committee; CI, confidence interval.
a Multivariate model controlled for facility maturity, staff-to-population ratio, and clustering at the district level.
verification criteria achieved for each of the community engagement assessment areas by
study arm. Please see S1 Tool SBM-R for full details.
Means for staff-to-population ratio, number of CHOs per CHPS zone, and years in
existence were calculated for intervention and comparison zones from data obtained from the
Regional Health Directorate. To find the proportion of CHOs sampled, the percentage of
CHOs sampled per CHPS zone was first calculated, and then the average for intervention and
comparison CHPS zones overall was calculated. For both the bivariate and multivariate
analyses, we used a generalized linear regression model with Poisson distribution. The multivariate
analyses included the matching criteria, facility maturity, and staff-to-population ratio as
covariates in the model. Analyses were completed using Stata 13.
Household survey tool, data collection, and analysis
A team of 15 experienced household survey data collectors participated in a 4-day training
workshop on the objectives of the study, research ethics, including obtaining informed
consent, study standard operating procedures, and use of the mobile data collection application,
CommCare (www.commcarehq.org). The household questionnaire was developed by the
project team for the specific purpose of the end-line evaluation (S2 Tool). The survey was informed
by a literature review of other studies that examined access to and quality of care [
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After obtaining informed written consent, data collectors administered the 62-question
household survey to community members living within sampled CHPS zones.
The data collectors worked with local leaders in each community to identify the center of
the community where a random direction was chosen using the spin-the-bottle technique. A
random number application was used to determine the first household to approach, after
which every third house in the same direction was approached. If the community border was
reached, the data collector would turn clockwise and continue visiting the third nearest house
using the same method. This process continued until the target number of households in the
community was reached. If multiple households lived in the same house, a random number
was used to select the household to screen, then a recruitment script was used to identify the
person in the household most likely to accompany a family member to a health facility.
Households that included a potential SBM-R assessment respondent were excluded, as were those
under the age of 18 or those who had lived in the community less than 1 year.
Respondents were asked about various aspects of their experiences of care for both facility
and home visits: amount of time spent, perceived knowledge and skills of providers, respect of
clients, confidentiality, and overall satisfaction. As a proxy for economic status, information
on household assets was collected and used to create a composite household assets score. This
was an additive score with a potential range of 0 to 10, based on household ownership of
various household materials and whether respondents used a shared toilet. As the GHS mobilized
CHOs at CHPS zones to deliver primary health care at the household and community levels to
improve geographic access, respondents were also asked about their number of facility visits,
receipt of home visits, and participation in community-based activities as a proxy for access to
primary health care. Readiness included infrastructure, medicines, and tests required to deliver
the basic package of clinical services in line with the WHO SARA that outlines the prerequisite
inputs for quality services . Descriptive statistics and bivariate analysis were conducted to
determine whether there were significant differences between intervention and comparison
zones on a set of variables after adjusting for clustering at the household and community levels,
using the combined weights in Stata survey commands to account for the probability of
selection into the intervention zone (Table 5).
Ethical approval for the study was obtained from Johns Hopkins Bloomberg School of
Public Health Institutional Review Board (00006456) and the Ghana Health Service Ethical Review
Committee (GHS-ERC 10/09/15).
CHPS zones in the intervention and comparison arms were similar in staff-to-population ratio
and years in existence (Table 2). An average of 3 CHOs worked at each CHPS zone (range of 1
to 4), except for one comparison zone that had 8 CHOs. A total of 137 individuals responded
to the SBM-R assessments across the 24 CHPS zones?53 CHOs, 23 CHVs, 22 CHMC
members, and 39 DHMT members. An average of 4.1 people per CHPS zone participated in the
study (intervention: 4.3; comparison: 3.8). DHMT members were not included in the average
as they support more than one CHPS zone. The slightly higher average in the intervention
zones was due in part because two comparison CHPS zones did not have a CHMC and one of
those zones was also lacking a CHV. All of these findings are presented in Table 2.
A total of 426 individuals responded to the household survey (of 428 screened and
consented). On average, the respondents were around 39 years old and had four living children.
Most respondents were female, married, and had some formal education. In intervention
zones, respondents had lower household asset scores, lived further from a CHPS facility and
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(n = 147)
(n = 163)
Percent Reported by Study Arm
Percent Reported by Study Arm
CHPS, Community-Based Health Planning and Services; CHO, community health officer; CHV, community health volunteers.
were less likely to identify as Muslim. Among respondents who reported any CHPS facility
visits, those living in intervention zones were generally further away, with less than half (48.3%)
reporting being within 30 minutes to the facility, while in comparison zones it was 59.5%. In
intervention zones, there were fewer Muslims and more respondents identifying as having
traditional, spiritualist, or no religious beliefs. These details are presented in Table 2.
On the SBM-R assessments, intervention zones significantly outperformed comparison zones
on achievement of overall standards-based verification criteria (intervention: 83.6%,
comparison: 58.8%, p-value <0.001) (Table 3). The greatest differences in performance were observed
in the community engagement assessments (85.7% vs. 41.4%, p-value <0.001), although
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differences were also seen in the other two categories: clinical services?90.0% vs. 71.1%
(pvalue <0.001) and facility readiness and management? 65.8% vs. 50.8% (p-value <0.001). As
part of the intervention, minor logistic support was provided to a few of the facilities, which
may have contributed to some of the differences seen in readiness scores. Cadre-specific
analysis of the community engagement assessments shows CHOs in intervention zones achieved
92.1% of verification criteria compared to 57.5% in comparison zones (p-value <0.001). CHVs
in intervention zones similarly outperformed those in comparison zones (83.0% vs. 26.9%,
pvalue, <0.001). CHMCs in interventions zones achieved 75.9% of criteria, whereas only 29.7%
of criteria were achieved in comparison zones (p-value <0.001). Findings are presented in
Performance was further analyzed by assessment area for each of the three categories.
Results for the community engagement assessment areas are presented in Table 4 by cadre of
respondent. Within the community engagement category, intervention zones significantly
outperformed comparison zones in every assessment area. Intervention zones generally
outperformed comparison zones in the other two categories as well. Full results are presented in
S1 Table. Within the facility readiness and management area intervention zones achieved
70.5% of verification criteria for financial management, as compared to 47.6% in comparison
zones. In terms of clinical services, again the intervention zones fared better than comparison
zones. Intervention CHPS zones achieved 95% of verification criteria on child immunization,
compared to only 66% of intervention zones.
CHOs in intervention zones were significantly more likely to engage other cadres of the
CHPS model versus those in comparison zones. For example, CHOs in intervention zones
were 37 times more likely to support CHVs (adjusted risk ratio [ARR] 37.32, p-value <0.001,
95% CI 6.4?219.07) and four times more likely to work with CHMCs (p-value <0.001, 95% CI
2.3?8.49) than their counterparts in comparison zones. Similarly, CHVs were nearly four
times more likely (p-value <0.001, 95% CI 2.5?6.3) to be able to manage minor home ailments
than those in comparison zones. CHMCs were 12times more likely to outperform comparison
zone committees in terms of resource mobilization and management (p-value <0.022, 95% CI
1.4?101.4). For all other assessment areas, intervention CHMCs were approximately twice as
likely to outperform comparison zone committees.
The number of CHPS facility visits reported in the year prior to the survey did not differ
significantly between respondents in intervention zones and comparison zones, while analysis on
items more directly related to the community-based components of the CHPS model did
show differences (Table 5). Nearly 40% of respondents in intervention zones reported having
at least one home visit from a CHO in the prior year, compared to 18% of respondents in
comparison zones (p-value, <0.001). Reports of home visits in the past year from CHVs were more
than three times higher in intervention zones (29.8% vs. 8.5%, p-value <0.001). In the year
prior to the survey, nearly 42% of respondents in intervention zones attended a health talk led
by a CHO, compared to 27% of respondents in comparison zones (p-value <0.004).
Attendance at a child welfare clinic did not differ significantly between study arms. While
differences in home visits, a proxy for access to services, did demonstrate some differences between
study arms, the effect on the client experience of care did not show much variance. Overall
satisfaction with visits to CHPS facilities and being appreciative of home visits was
overwhelmingly high by respondents in both intervention and comparison zones.
Few differences between the study arms were noted on more specific aspects of client
experience of care. Regarding CHOs having the knowledge and skills to perform services during
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facility visits, there was a difference in overall distribution of responses by study arm
(pvalue = 0.009). Fewer respondents in intervention versus comparison zones reported that they
felt the CHOs had the knowledge and skills to perform services (89.1% vs. 96.9%). However,
when asked the same question about interactions with the same cadre of providers during
home visits, the responses in the intervention and comparison zones were similar (98.4% vs.
100%). Similarly, there was a statistically significant difference in distribution of responses
regarding CHOs keeping client health and personal information confidential during facility
visits between study arms (p-value = 0.047). Fewer respondents in intervention versus
comparison zones felt CHOs kept their health and personal information confidential during facility
visits (84.4% vs. 92.6%), but on the same variable during home visits, responses were similar
across study arms.
Respondents in both study arms reported feeling CHOs were more respectful during home
visits than during facility visits; with no statistical differences in overall distribution of
responses between study arms in either visit setting. When asked about the amount of time
spent with a CHO or CHV, respondents in intervention zones were more likely to report the
?right amount of time? was spent, rather than the visit being too long or short. The distribution
of responses regarding the length of visit between study arms was statistically significant for
facility visits (p-value = 0.049). A higher proportion of respondents in the intervention arm
reported the facility visit being the ?right amount of time? (78.9% vs. 71.2%). For home visits
conducted by CHOs, the difference in response distribution (p-value = 0.053) was at, but not
below the set value for statistical significance. For CHV home visits, more respondents in
intervention zones (88.5%) reported the right amount of time was spent, compared to
comparison zones (72.2%). The difference in overall response distribution (p-value = 0.06) did not
meet the set value for statistical significance.
Ghana is making progress in achieving Sustainable Development Goal 3 and UHC primarily
through the national scale-up and implementation of the CHPS model [
]. For these
goals to be achieved, services need to be high quality and people-centered within health
systems that can respond to local realities, demographics, and resource allocation [29?30]. This
evaluation examined access to, and quality of, CHPS services in intervention and comparison
sites after 2 to 4 years of project support.
The CHPS model relies on community engagement as a mechanism to overcome barriers to
accessing health care in Ghana by taking health care directly to the homes of community
members through home visits, outreach activities, and direct participation of community
members. Yet community engagement has been the weakest component of the
]. As a proxy for access to primary health care, the evaluation asked respondents about
visits to CHPS facilities, home visits received, and participation in community-based activities
]. Intervention zones achieved a significantly higher proportion of standards relating to
community engagement than comparison zones and respondents in intervention zones were
more likely to have had at least one home visit from a CHV and a CHO and to have attended a
community outreach event. These findings suggest this intervention was successful in
overcoming one of the biggest hurdles to successful scale-up of the CHPS model. They are in line
with findings of Sakeah et al. (2014) who documented the crucial role strengthening
community engagement had on increased access to skilled delivery in CHPS zones [
intervention zones reaching more than double the percentage of respondents with CHO home
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visits (39% vs 18%) than comparison zones, this still falls short of the ambitious goals of
reaching all households. Given the criticality of home visits as a component of the CHPS model,
designing interventions or support that can overcome the challenges related to this component
warrants further exploration.
Interestingly, respondents in both intervention and comparison sites reported similar
numbers of facility visits. The project team did anticipate that strengthened community
engagement and linkages would lead to more confidence and greater utilization of fixed facilities. It
may be of interest to explore this result further.
Quality of care
Various models of quality have been explored and defined in the literature, our evaluation
examined two aspects of quality of care: provision of care and client experience of care.
Provision of care. A Cochrane review found that an audit and feedback approach is most
likely to lead to improvements in practices when baseline performance is low and when the
approach is performed by a colleague or supervisor, is provided both verbally and in writing, is
repeated over time, and includes targets and an action plan [
]?all aspects present in the
STAR CHPS intervention. Consistent with the findings of this review, intervention zones
outperformed comparison zones on all three categories of standards?clinical services, facility
readiness and management, and, most remarkably, community engagement. This approach
was effective in addressing gaps as the standards assisted implementation though articulating
not only what to do, but how to do it (i.e., standards with detailed verification criteria). The
SBM-R approach used in this project has been implemented in over 30 countries, but is usually
focused on delivery of services in a facility [
]. This project and its evaluation
demonstrated the applicability of the approach for a community-based, primary health care service
delivery platform and for volunteers and community committees. The performance standards
developed in this work were reviewed and referenced by the Ghana MOH during the 2015
update of the CHPs policy because they provided a full description of the details on CHPS
service delivery. In addition, they were also included in the 2016 updated CHPS implementation
guidance as part of the basic package of services.
Client experience of care. The classical Donabedian framework that categorizes
dimensions of care into structure, process, and outcomes [
] is frequently the basis for assessing
provision and experience of care. Despite the rich legacy of this framework, client experience
of care and satisfaction remain challenging to accurately measure and interpret [
In a systematic review of determinants of women?s satisfaction with maternal health care in
developing countries, Srivastava et al. (2015) noted that in most interventions, the underlying
theory of change proposes that responsive and culturally appropriate care will enhance
utilization and thus improve outcomes [
]. However, the review also found that satisfaction ratings
were high across almost all studies. They question if this could be due to lack of awareness and
low levels of literacy. If poor women have limited access to public services, they may not have a
sense of entitlement to health care. Thus, even basic facilities would be satisfactory to them.
Consistent with this, our findings showed that respondents in both intervention and the
comparison CHPS zones reported very high overall levels of satisfaction with care received in
facilities and during home visits.
Despite intervention zones statistically outperforming comparison zones overall on
standards-based assessments, respondents in both study arms almost universally reported being
satisfied or very satisfied with facility visits and glad or very glad about receiving home visits.
Further adding to the complexity, respondents had differing opinions on the same cadre of
providers, depending on whether the services were provided in a facility or during a home
14 / 19
visit. This finding is in line with existing literature on the nature of power dynamics and
An approach used by Alhassan et al. [
] found that facilitating systematic community
engagement (SCE) interventions around quality of care enabled existing community groups to
reflect on perceived quality of care, using 10 pre-defined domains detailed on a community
scorecard. Community feedback was shared with health providers who used the information
to develop action plans to address gaps in perception of quality. After six months a second
SCE assessment showed improvements in perceptions of quality. This low-cost, relatively
simple SCE approach, which also enabled providers to reflect on motivation, safety and risk
mitigation, may add value to standards-based quality improvement interventions [
The study findings have several limitations. We randomly selected intervention zones,
comparison zones, and household participants and matched comparison and intervention zones,
in accord with the posttest only, non-equivalent control group design. However, there may be
true differences between the groups that we were unable to measure given the design, which
was selected because project baseline data, and data on comparison zones, were not available.
Further, intervention sites were all in coastal districts, while comparison districts were adjacent
and inland. As with other surveys, social desirability bias is a concern. Further, we used
selfreport of visits to facilities, home visits, and exposure to community events as measurement
variables. Although not feasible due to financial and time constraints, as well as concerns for
the quality of service statistic data, a stronger design would have included a record review of
service utilization and health outcomes. The SBM-R assessments may have been prone to the
Hawthorne effect, although any bias would be expected to be similar in intervention and
comparison zones. The Rosenthal effect may have led to the assessors encouraging intervention
zone participants more than those in comparison zones. We attempted to mitigate this by not
assigning assessors to CHPS zones where they had previously worked. Further, by nature of
the intervention, comparison zone participants had no prior exposure to the assessment tool.
Generalizability of the findings to other locations may be limited because the project was
implemented in six coastal districts of Western Ghana.
While the evaluation demonstrated improved access to quality care in zones that used a
standards-based approach, there were limited differences between intervention and comparison
zones in clients? experiences of care. As Ghana and other countries scale-up UHC, a pragmatic
approach such as SBM-R could prove useful to engage both facility- and community-based
service providers as well as community members to improve provision of care. SBM-R, as a
standalone quality improvement approach, can complement other government quality
improvement processes or structures. As it can also be led by facilities as a self-assessment,
SBM-R can be sustainable. In addition, we must continue to grapple with how to improve and
accurately measure the client?s experience of care [
]. Further work is needed to ensure
that client experience is built into the design, implementation, monitoring, and evaluation of
quality improvement interventions. Tools that are more sensitive for measuring and
interpreting experience of care are needed for both monitoring and evaluation  so that countries
like Ghana can ensure that the care clients receive meets their needs and contributes to
Sustainable Development Goal 3??ensure healthy lives and promote well-being for all at all ages?
15 / 19
S1 Table. Results of bivariate and multivariate analyses of percentage of verification
criteria achieved for assessment areas.
S1 Tool. SBM-R assessment tool.
S2 Tool. Household survey.
In 2011, the Jubilee Partners, (a consortium of oil companies including Tullow Ghana, Kosmos
Energy, Anadarko Petroleum, Ghana National Petroleum Corporation, and Petro SA) funded
Jhpiego to implement a 5-year project to increase access to quality primary health care for six
coastal districts of the Western Region of Ghana. This evaluation was funded by the project. At
the time of this study, authors Richard Okyere Boadu, Carina Rosado, Aliza Lailari, and
Bernard Vikpeh-Lartey were employed by Jhpiego Ghana. The authors are grateful to the Ghana
Health Service Western Regional Health Directorate for its support and partnership in both
the implementation of the STAR CHPS project and the evaluation. In particular, the
researchers acknowledge the support of Dr. Linda Amarkai Vanotoo (former Director of Health
Services, Western Region), Dr. K. Enin Karikari (former Director of Health Services, Western
Region), Dr. Emmanuel Kwadwo Tinkorang (former Western Regional Health Director of
Health Services), and Joseph Newton and Joseph Kobena Arthur (Regional CHPS
Coordinators). District Directors of Health Services and their staff in the six targeted districts were
instrumental in conducting this study. Data collectors worked tirelessly in challenging
conditions to complete the household surveys and collect data from CHPS zones. Special thanks to
Jhpiego Ghana staff Major Regina Isabel Akai-Nettey (Rtd), Fred Effah, Alishea Galvin, and
Jhpiego staff Heather Harrison and Gahan Furlane for their support and review of this
manuscript, and our editor Elizabeth Thompson, for her thorough and thoughtful edit. Jean Sack?
who provided immense support with the literature review before the study and during the
manuscript development process?we are grateful for your tireless efforts to keep us current
with the literature. We also thank Edgar Necochea, Stacie Stender, Debora Bossemeyer,
Young-Mi Kim, and especially Maureen Flood of Jhpiego for their critical reviews. A special
thanks goes to Judith Fullerton for her vital guidance and support in finalizing this article.
Thanks to Gayane Yenokyan at the Johns Hopkins Bloomberg School of Public Health for her
support with sample size calculations and guidance on data analysis; to the former-project
director, Joyce Ablordeppey, who supported project implementation and data collector
training; Francis Essuman and John Asibey, Jhpiego drivers who competently and safely navigated
our data collectors and staff around nine districts; and Douglas Frimpong-Nnuroh for support
with translations and the data collectors? workshop.
Conceptualization: Christina Maly, Richard Okyere Boadu, Bernard Vikpeh-Lartey, Chantelle
Data curation: Carina Rosado, Aliza Lailari.
Formal analysis: Carina Rosado, Aliza Lailari.
16 / 19
Funding acquisition: Christina Maly, Chantelle Allen.
Investigation: Christina Maly, Richard Okyere Boadu, Carina Rosado, Aliza Lailari, Bernard
Methodology: Christina Maly, Chantelle Allen.
Project administration: Christina Maly, Richard Okyere Boadu, Bernard Vikpeh-Lartey,
Supervision: Christina Maly, Richard Okyere Boadu, Carina Rosado, Aliza Lailari, Bernard
Visualization: Carina Rosado, Aliza Lailari.
Writing ? original draft: Christina Maly, Richard Okyere Boadu, Carina Rosado, Aliza Lailari,
Bernard Vikpeh-Lartey, Chantelle Allen.
Writing ? review & editing: Christina Maly, Chantelle Allen.
17 / 19
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