Quality improvement collaboratives as part of a quality improvement intervention package for preterm births at sub-national level in East Africa: a multi-method analysis.

BACKGROUND: Quality improvement collaboratives (QIC) are an approach to accelerate the spread and impact of evidence-based interventions across health facilities, which are found to be particularly successful when combined with other interventions such as clinical skills training. We implemented a QIC as part of a quality improvement intervention package designed to improve newborn survival in Kenya and Uganda. We use a multi-method approach to describe how a QIC was used as part of an overall improvement effort and describe specific changes measured and participant perceptions of the QIC. METHODS: We examined QIC-aggregated run charts on three shared indicators related to uptake of evidence-based practices over time and conducted key informant interviews to understand participants' perceptions of quality improvement practice. Run charts were evaluated for change from baseline medians. Interviews were analysed using framework analysis. RESULTS: Run charts for all indicators reflected an increase in evidence-based practices across both countries. In Uganda, pre-QIC median gestational age (GA) recording of 44% improved to 86%, while Kangaroo Mother Care (KMC) initiation went from 51% to 96% and appropriate antenatal corticosteroid (ACS) use increased from 17% to 74%. In Kenya, these indicators went from 82% to 96%, 4% to 74% and 4% to 57%, respectively. Qualitative results indicate that participants appreciated the experience of working with data, and the friendly competition of the QIC was motivating. The participants reported integration of the QIC with other interventions of the package as a benefit. CONCLUSIONS: In a QIC that demonstrated increased evidence-based practices, QIC participants point to data use, friendly competition and package integration as the drivers of success, despite challenges common to these settings such as health worker and resource shortages. TRIAL REGISTRATION NUMBER: NCT03112018.

Integrating Social Determinants in Decision-Making Processes for Health: Insights from Conceptual Frameworks-the 3-D Commission.

The inclusion of social determinants of health offers a more comprehensive lens to fully appreciate and effectively address health. However, decision-makers across sectors still struggle to appropriately recognise and act upon these determinants, as illustrated by the ongoing COVID-19 pandemic. Consequently, improving the health of populations remains challenging. This paper seeks to draw insights from the literature to better understand decision-making processes affecting health and the potential to integrate data on social determinants. We summarised commonly cited conceptual approaches across all stages of the policy process, from agenda-setting to evaluation. Nine conceptual approaches were identified, including two frameworks, two models and five theories. From across the selected literature, it became clear that the context, the actors and the type of the health issue are critical variables in decision-making for health, a process that by nature is a dynamic and adaptable one. The majority of these conceptual approaches implicitly suggest a possible role for data on social determinants of health in decision-making. We suggest two main avenues to make the link more explicit: the use of data in giving health problems the appropriate visibility and credibility they require and the use of social determinants of health as a broader framing to more effectively attract the attention of a diverse group of decision-makers with the power to allocate resources. Social determinants of health present opportunities for decision-making, which can target modifiable factors influencing health-i.e. interventions to improve or reduce risks to population health. Future work is needed to build on this review and propose an improved, people-centred and evidence-informed decision-making tool that strongly and explicitly integrates data on social determinants of health.

Improving Decision-Making for Population Health in Nonhealth Sectors in Urban Environments: the Example of the Transportation Sector in Three Megacities-the 3-D Commission.

Noncommunicable diseases (NCDs) represent a significant global public health burden. As more countries experience both epidemiologic transition and increasing urbanization, it is clear that we need approaches to mitigate the growing burden of NCDs. Large and growing urban environments play an important role in shaping risk factors that influence NCDs, pointing to the ineluctable need to engage sectors beyond the health sector in these settings if we are to improve health. By way of one example, the transportation sector plays a critical role in building and sustaining health outcomes in urban environments in general and in megacities in particular. We conducted a qualitative comparative case study design. We compared Bus Rapid Transit (BRT) policies in 3 megacities-Lagos (Africa), Bogotá (South America), and Beijing (Asia). We examined the extent to which data on the social determinants of health, equity considerations, and multisectoral approaches were incorporated into local politics and the decision-making processes surrounding BRT. We found that all three megacities paid inadequate attention to health in their agenda-setting, despite having considerable healthy transportation policies in principle. BRT system policies have the opportunity to improve lifestyle choices for NCDs through a focus on safe, affordable, and effective forms of transportation. There are opportunities to improve decision-making for health by involving more available data for health, building on existing infrastructures, building stronger political leadership and commitments, and establishing formal frameworks to improve multisectoral collaborations within megacities. Future research will benefit from addressing the political and bureaucratic processes of using health data when designing public transportation services, the political and social obstacles involved, and the cross-national lessons that can be learned from other megacities.

Evaluation of neonatal mortality data completeness and accuracy in Ghana.

BACKGROUND: Cause-specific mortality data are required to set interventions to reduce neonatal mortality. However, in many developing countries, these data are either lacking or of low quality. We assessed the completeness and accuracy of cause of death (COD) data for neonates in Ghana to assess their usability for monitoring the effectiveness of health system interventions aimed at improving neonatal survival. METHODS: A lot quality assurance sampling survey was conducted in 20 hospitals in the public sector across four regions of Ghana. Institutional neonatal deaths (IND) occurring from 2014 through 2017 were divided into lots, defined as neonatal deaths occurring in a selected facility in a calendar year. A total of 52 eligible lots were selected: 10 from Ashanti region, and 14 each from Brong Ahafo, Eastern and Volta region. Nine lots were from 2014, 11 from 2015 and 16 each were from 2016 and 2017. The cause of death (COD) of 20 IND per lot were abstracted from admission and discharge (A&D) registers and validated against the COD recorded in death certificates, clinician's notes or neonatal death audit reports for consistency. With the error threshold set at 5%, ≥ 17 correctly matched diagnoses in a sample of 20 deaths would make the lot accurate for COD diagnosis. Completeness of COD data was measured by calculating the proportion of IND that had death certificates completed. RESULTS: Nineteen out of 52 eligible (36.5%) lots had accurate COD diagnoses recorded in their A&D registers. The regional distribution of lots with accurate COD data is as follows: Ashanti (4, 21.2%), Brong Ahafo (7, 36.8%), Eastern (4, 21.1%) and Volta (4, 21.1%). Majority (9, 47.4%) of lots with accurate data were from 2016, followed by 2015 and 2017 with four (21.1%) lots. Two (10.5%) lots had accurate COD data in 2014. Only 22% (239/1040) of sampled IND had completed death certificates. CONCLUSION: Death certificates were not reliably completed for IND in a sample of health facilities in Ghana from 2014 through 2017. The accuracy of cause-specific mortality data recorded in A&D registers was also below the desired target. Thus, recorded IND data in public sector health facilities in Ghana are not valid enough for decision-making or planning. Periodic data quality assessments can determine the magnitude of the data quality concerns and guide site-specific improvements in mortality data management.

"Top-down bottom-up" estimation of per capita cost of new-born care interventions in four regions of Ghana: beyond implementation to scalability and sustainability.

BACKGROUND: Limited financial, human and material health resources coupled with increasing demand for new-born care services require efficiency in health systems to maximize the available sources for improved health outcomes. Making Every Baby Count Initiative (MEBCI) implemented by local and international partners in 2013 in Ghana aimed at attaining neonatal mortality of 21 per 1000 livebirths by 2018 in four administrative regions in Ghana. MEBCI interventions benefited 4027 health providers, out of which 3453 (86%) were clinical healthcare staff. OBJECTIVE: Determine the per capita cost of the MEBCI interventions towards enhancing new-born care best practices through capacity trainings for frontline clinical and non-clinical staff. METHODS: Parameters for determining per capita cost of the new-born care interventions were estimated using expenditure on trainings, supervisions, monitoring and evaluation, advocacy, administrative/services and medical logistics. Data collection started in October 2017 and ended in September 2018. Data sources for the per capita cost estimations were invoices, expense reports and ledger books at the national, regional and district levels of the health system. RESULTS: Total of 4027 healthcare providers benefited from the MEBCI training activities comprising of 3453 clinical staff and 574 non-clinical personnel. Cumulative cost of implementing the MEBCI interventions did not necessarily match the cost per capita in staff capacity building; average cost per capita for all staff (clinical and non-clinical staff) was approximately US$ 982 compared to a per capita cost of US$ 799 for training only core clinical staff. Average cost per capita for all regions was approximately US$ 965 for all staff compared to US$ 777 per capita cost for only clinical staff. Per capita cost of training was relatively lower in regions with more staff than regions with lower numbers, perhaps due to economies of scale. CONCLUSION: The MEBCI intervention had a wide coverage in terms of training for frontline healthcare providers albeit the associated cost may be potentially unsustainable for Ghana's health system. Emerging digital training platforms could be leveraged to reduce per capita cost of training. Large-scale on-site batch-training approach could also be replaced with facility-based workshops using training of trainers (TOTs) approach to promote efficiency.

Health system redesign for maternal and newborn survival: rethinking care models to close the global equity gap.

Large disparities in maternal and neonatal mortality exist between low- and high-income countries. Mothers and babies continue to die at high rates in many countries despite substantial increases in facility birth. One reason for this may be the current design of health systems in most low-income countries where, unlike in high-income countries, a substantial proportion of births occur in primary care facilities that cannot offer definitive care for complications. We argue that the current inequity in care for childbirth is a global double standard that limits progress on maternal and newborn survival. We propose that health systems need to be redesigned to shift all deliveries to hospitals or other advanced care facilities to bring care in line with global best practice. Health system redesign will require investing in high-quality hospitals with excellent midwifery and obstetric care, boosting quality of primary care clinics for antenatal, postnatal, and newborn care, decreasing access and financial barriers, and mobilizing populations to demand high-quality care. Redesign is a structural reform that is contingent on political leadership that envisions a health system designed to deliver high-quality, respectful care to all women giving birth. Getting redesign right will require focused investments, local design and adaptation, and robust evaluation.

Level of confidence in and endorsement of the health system among internet users in 12 low-income and middle-income countries.

INTRODUCTION: People's confidence in and endorsement of the health system are key measures of system performance, yet are undermeasured in low-income and middle-income countries (LMICs). We explored the prevalence and predictors of these measures in 12 countries. METHODS: We conducted an internet survey in Argentina, China, Ghana, India, Indonesia, Kenya, Lebanon, Mexico, Morocco, Nigeria, Senegal and South Africa collecting demographics, ratings of quality, and confidence in and endorsement of the health system. We used multivariable logistic regression to assess the association between confidence/endorsement and self-reported quality of recent healthcare. RESULTS: Of 13 489 respondents, 62% reported a health visit in the past year. Applying population weights, 32% of these users were very confident that they could receive effective care if they were to 'become very sick tomorrow'; 30% endorsed the health system, that is, agreed that it 'works pretty well and only needs minor changes'. Reporting high quality in the last visit was associated with 4.48 and 2.69 greater odds of confidence (95% CI 3.64 to 5.52) and endorsement (95% CI 2.33 to 3.11). Having health insurance was positively associated with confidence and endorsement (adjusted odds ratio (AOR) 1.68, 95% CI 1.49 to 1.90 and AOR 1.34, 95% CI 1.22 to 1.48), while experiencing discrimination in healthcare was negatively associated (AOR 0.67, 95% CI 0.56 to 0.80 and AOR 0.63, 95% CI 0.53 to 0.76). CONCLUSION: Confidence and endorsement of the health system were low across 12 LMICs. This may hinder efforts to gain support for universal health coverage. Positive patient experience was strongly associated with confidence in and endorsement of the health system.

Evaluation of two newborn resuscitation training strategies in regional hospitals in Ghana.

AIM: In Ghana, institutional delivery has been emphasized to improve maternal and newborn outcomes. The Making Every Baby Count Initiative, a large coordinated training effort, aimed to improve newborn outcomes through government engagement and provider training across four regions of Ghana. Two newborn resuscitation training and evaluation approaches are described for front line newborn care providers at five regional hospitals. METHODS: A modified newborn resuscitation program was taught at the Greater Accra Regional Hospital (GARH) and evaluated with real-time resuscitation observations. A programmatic shift, led to a different approach being utilized in Sunyani, Koforidua, Ho and Kumasi South Regional Hospitals. This included Helping Babies Breathe (HBB) and Essential Care for Every Baby (ECEB) training followed by objective structured clinical examinations (OSCE) with manikins at fixed intervals. Data was collected on training outcomes, fresh stillbirth and institutional newborn mortality rates. RESULTS: Training was conducted for 412 newborn care providers. For 120 staff trained at GARH, resuscitation observations and chart review found improvements in conducting positive pressure ventilation. For 292 providers that received HBB and ECEB training, OSCE pass rates exceeded 90%, but follow-up decreased from 98% to 84% over time. A decrease in fresh stillbirth and institutional newborn mortality occurred at GARH (p â€‹< â€‹0.05), but not in the other four regional hospitals. CONCLUSION: Newborn resuscitation training is warranted in low-resource settings; however, the optimal training, monitoring and evaluation approach remains unclear, particularly in referral hospitals. Although, mortality reductions were observed at GARH, this cannot be solely attributed to newborn resuscitation training.

Towards universal health coverage: what are the system requirements for effective large-scale community health worker programmes?

Against the background of efforts to strengthen health systems for universal health coverage and health equity, many African countries have been relying on lay members of the community, often referred to as community health workers (CHWs), to deliver primary healthcare services. Growing demand and great variability in definitions, roles, governance and funding of CHWs have prompted the need to revisit CHW programmes and provide guidance on the implementation of successful programmes at scale. Drawing on the synthesised evidence from two extensive literature reviews, this article determines foundational elements of functioning CHW programmes, focusing in particular on the systems requirements of large-scale programmes. It makes recommendations for the effective development of large-scale CHW programmes. The key foundational elements of successful CHW programmes identified are (1) embeddedness, connectivity and integration into the larger system of healthcare service delivery; (2) cadre differentiation and role clarity in order to maintain clear scopes of work and accountability; (3) sound programme design based on local contextual factors and effective people management; and (4) ongoing monitoring, learning and adapting based on accurate and timely local data in order to ensure optimal fit to local context since one size does not fit all. We conclude that CHWs are an investment in health systems strengthening and community resilience with enormous potential for contributing to universal health coverage and the sustainable development goals if well designed and managed. While the evidence base is uneven and mixed, it provides extensive insight and knowledge to strengthen, scale up and sustain CHW programmes throughout Africa.

In Low- And Middle-Income Countries, Is Delivery In High-Quality Obstetric Facilities Geographically Feasible?

Delivery in a health facility is a key strategy for reducing maternal and neonatal mortality, yet increasing use of facilities has not consistently translated into reduced mortality in low- and middle-income countries. In such countries, many deliveries occur at primary care facilities, where the quality of care is poor. We modeled the geographic feasibility of service delivery redesign that shifted deliveries from primary care clinics to hospitals in six countries: Haiti, Kenya, Malawi, Namibia, Nepal, and Tanzania. We estimated the proportion of women within two hours of the nearest delivery facility, both currently and under redesign. Today, 83-100 percent of pregnant women in the study countries have two-hour access to a delivery facility. A policy of redesign would reduce two-hour access by at most 10 percent, ranging from 0.6 percent in Malawi to 9.9 percent in Tanzania. Relocating delivery services to hospitals would not unduly impede geographic access to care in the study countries. This policy should be considered in low- and middle-income countries, as it may be an effective approach to reducing maternal and newborn deaths.

Expectations of healthcare quality: A cross-sectional study of internet users in 12 low- and middle-income countries.

BACKGROUND: High satisfaction with healthcare is common in low- and middle-income countries (LMICs), despite widespread quality deficits. This may be due to low expectations because people lack knowledge about what constitutes good quality or are resigned about the quality of available services. METHODS AND FINDINGS: We fielded an internet survey in Argentina, China, Ghana, India, Indonesia, Kenya, Lebanon, Mexico, Morocco, Nigeria, Senegal, and South Africa in 2017 (N = 17,996). It included vignettes describing poor-quality services-inadequate technical or interpersonal care-for 2 conditions. After applying population weights, most of our respondents lived in urban areas (59%), had finished primary school (55%), and were under the age of 50 (75%). Just over half were men (51%), and the vast majority reported that they were in good health (73%). Over half (53%) of our study population rated the quality of vignettes describing poor-quality services as good or better. We used multilevel logistic regression and found that good ratings were associated with less education (no formal schooling versus university education; adjusted odds ratio [AOR] 2.22, 95% CI 1.90-2.59, P < 0.001), better self-reported health (excellent versus poor health; AOR 5.19, 95% CI 4.33-6.21, P < 0.001), history of discrimination in healthcare (AOR 1.47, 95% CI 1.36-1.57, P < 0.001), and male gender (AOR 1.32, 95% CI 1.23-1.41, P < 0.001). The survey did not reach nonusers of the internet thus only representing the internet-using population. CONCLUSIONS: Majorities of the internet-using public in 12 LMICs have low expectations of healthcare quality as evidenced by high ratings given to poor-quality care. Low expectations of health services likely dampen demand for quality, reduce pressure on systems to deliver quality care, and inflate satisfaction ratings. Policies and interventions to raise people's expectations of the quality of healthcare they receive should be considered in health system quality reforms.

Evaluating the impact of a hospital scale-up phase of a quality improvement intervention in Ghana on mortality for children under five.

OBJECTIVE: To evaluate the scale-up phase of a national quality improvement initiative across hospitals in Southern Ghana. DESIGN: This evaluation used a comparison of pre- and post-intervention means to assess changes in outcomes over time. Multivariable interrupted time series analyses were performed to determine whether change categories (interventions) tested were associated with improvements in the outcomes. SETTING: Hospitals in Southern Ghana. PARTICIPANTS: The data sources were monthly outcome data from intervention hospitals along with program records. INTERVENTION: The project used a quality improvement approach whereby process failures were identified by health staff and process changes were implemented in hospitals and their corresponding communities. The three change categories were: timely care-seeking, prompt provision of care and adherence to protocols. MAIN OUTCOME MEASURES: Facility-level neonatal mortality, facility-level postneonatal infant mortality and facility-level postneonatal under-five mortality. RESULTS: There were significant improvements for two outcomes from the pre-intervention to the post-intervention phase. Postneonatal infant mortality dropped from 44.3 to 21.1 postneonatal infant deaths per 1000 admissions, while postneonatal under-five mortality fell from 23.1 to 11.8 postneonatal under-five deaths per 1000 admissions. The multivariable interrupted time series analysis indicated that over the long-term the prompt provision of care change category was significantly associated with reduced postneonatal under five mortality (ß = -0.0024, 95% CI -0.0051, 0.0003, P < 0.10). CONCLUSIONS: The reduced postneonatal under-five mortality achieved in this project gives support to the promotion of quality improvement as a means to achieve health impacts at scale.

Does postnatal care have a role in improving newborn feeding? A study in 15 sub-Saharan African countries.

BACKGROUND: Breastfeeding is known as a key intervention to improve newborn health and survival while prelacteal feeds (liquids other than breastmilk within 3 days of birth) represents a departure from optimal feeding practices. Recent programmatic guidelines from the WHO and UNICEF outline the need to improve newborn feeding and points to postnatal care (PNC) as a potential mechanism to do so. This study examines if PNC and type of PNC provider are associated with key newborn feeding practices: breastfeeding within 1 day and prelacteal feeds. METHODS: We use data from the Demographic and Health Surveys for 15 sub-Saharan African countries to estimate 4 separate pooled, multilevel, logistic regression models to predict the newborn feeding outcomes. FINDINGS: PNC is significantly associated with increased breastfeeding within 1day (OR = 1.35, P < 0.001) but is not associated with PLFs (OR = 1.04, P = 0.195). PNC provided by nurses, midwives and untrained health workers is also associated with higher odds of breastfeeding within 1 day of birth (OR = 1.39, P < 0.001, (OR = 1.95, P < 0.001) while PNC provided by untrained health workers is associated with increased odds of PLFs (OR = 1.20, P = 0.017). CONCLUSIONS: PNC delivered through customary care may be an effective strategy to improve the breastfeeding within 1 day but not to discourage PLFs. Further analysis should be done to examine how these variables operate at the country level to produce finer programmatic insight.

Absence of an association between Plasmodium falciparum infection and post-ivermectin Loa-related non-neurologic serious adverse events.

Although ivermectin treatment can induce serious adverse events (SAEs) in individuals harboring high Loa loa microfilaremia (mf), not all patients with high mf levels develop such reactions, suggesting that cofactors may be involved. A study was conducted in Cameroon to investigate the possible role of Plasmodium coinfection at the time of ivermectin treatment in the development of SAEs. Before their first ivermectin treatment, thick smears were obtained from 4,175 individuals to determine the burden of Plasmodium sp., L. loa, and Mansonella perstans. After treatment, 18 (4.3 per 1,000) patients developed a non-neurologic SAE. Logistic regression analysis, adjusting for age, sex, P. falciparum infection, and M. perstans infection intensities, confirmed that L. loa mf was the main risk factor for SAEs. We found no evidence that coinfection with P. falciparum at the time of ivermectin treatment was associated with the occurrence of Loa-related SAEs in this population.

Using quality improvement methods to test and scale up a new national policy on early post-natal care in Ghana.

INTRODUCTION: The first week of life presents the greatest risk of dying for a young infant. Yet, due to the sociocultural, financial, geographical and health system barriers found in many resource-poor settings, infants do not access health care until much later. To reduce neonatal mortality, the Ghana Health Service proposed a new policy that promotes skilled care during the first week of life. We report the results of an initiative that uses quality improvement (QI) methods to test the feasibility and effectiveness of the new early post-natal care (PNC) policy and its subsequent scale-up throughout northern Ghana. METHODS: Over a 10-month period, 30 networked QI teams from 27 rural health facilities developed and tested both facility-based and community-based changes to their processes of maternal and neonatal care. Coverage and outcome data were analysed using an interrupted time-series design. RESULTS: Over 24 months, early PNC increased from a mean of 15% to 71% for visits within the first 48 h, and from 0% to 53% for visits on Day 6 or 7. We observed a slower increase in skilled delivery (mean of 56% to 82%) over a longer period of time (35 months). Facility-based neonatal mortality remained unchanged: mean of 5.1 deaths per 1000 deliveries. Using the most effective change ideas developed in the 27 test facilities, the early PNC policy was scaled up over the subsequent 2 years to 576 health facilities in all 38 districts of northern Ghana. CONCLUSIONS: This initiative demonstrates the utility of a QI approach in testing, implementing and subsequent scaling up a national policy for early PNC in a resource-constrained setting. This approach provides a model for improving the implementation of other national health policies to accelerate the achievement of the Millennium Development Goals in Ghana and other resource-poor countries.

A strategy for reducing maternal and newborn deaths by 2015 and beyond.

BACKGROUND: Achievement of Millennium Development Goal (MDG) 4 for child survival requires acceleration of gains in newborn survival, and current trends in improving maternal health will also fall short of reaching MDG 5 without more strategic actions. We present a Maternal Newborn and Child Health (MNCH) strategy for accelerating progress on MDGs 4 and 5, sustaining the gains beyond 2015, and further bringing down maternal and child mortality by two thirds by 2030. DISCUSSION: The strategy takes into account current trends in coverage and cause-specific mortality, builds on lessons learned about what works in large-scale implementation programs, and charts a course to reach those who do not yet access services. A central hypothesis of this strategy is that enhancing interactions between frontline workers and mothers and families is critical for increasing the effective coverage of life-saving interventions. We describe a framework for measuring and evaluating progress which enables continuous course correction and improvement in program performance and impact. SUMMARY: Evidence for the hypothesis and impact of this strategy is being gathered and will be synthesized and disseminated in order to advance global learning and to maximise the potential to improve maternal and neonatal survival.

Impact evaluation of a quality improvement intervention on maternal and child health outcomes in Northern Ghana: early assessment of a national scale-up project.

OBJECTIVE: To evaluate the influence of the early phase of Project Fives Alive!, a national child survival improvement project, on key maternal and child health outcomes. DESIGN: The evaluation used multivariable interrupted time series analyses to determine whether change categories tested were associated with improvements in the outcomes of interest. PARTICIPANTS: The evaluation used program and outcome data from interventions focused on health-care staff in 27 facilities. SETTING: Northern Ghana. INTERVENTION: The project uses a quality improvement (QI) approach whereby process failures are identified by health staff and process changes are tested in the health facilities and corresponding communities to address those failures. MAIN OUTCOME MEASURES: The maternal health outcomes were early antenatal care attendance and skilled delivery, and the child health outcomes were underweight infants attending child wellness clinics, facility-level neonatal mortality and facility-level infant mortality. RESULTS: Postnatal care changes for the first 1-2 days of life (ß= 0.10, P = 0.07) and the first 6-7 days of life (ß = 0.10, P = 0.07) were associated with a higher rate of visits by underweight infants to child wellness clinics. There was an association between the early pregnancy identification change category with increased skilled delivery (ß = 1.36 P = 0.07). In addition, a greater number of change categories tested was associated with increased skilled delivery (ß = 0.05, P = 0.01). CONCLUSION: The QI approach of testing and implementing simple and low cost locally inspired changes has the potential to lead to improved health outcomes at scale both in Ghana and other low- and middle-income countries.