Deepthi Wickremasinghe

'Scaling-up is a craft not a science': Catalysing scale-up of health innovations in Ethiopia, India and Nigeria.

Donors and other development partners commonly introduce innovative practices and technologies to improve health in low and middle income countries. Yet many innovations that are effective in improving health and survival are slow to be translated into policy and implemented at scale. Understanding the factors influencing scale-up is important. We conducted a qualitative study involving 150 semi-structured interviews with government, development partners, civil society organisations and externally funded implementers, professional associations and academic institutions in 2012/13 to explore scale-up of innovative interventions targeting mothers and newborns in Ethiopia, the Indian state of Uttar Pradesh and the six states of northeast Nigeria, which are settings with high burdens of maternal and neonatal mortality. Interviews were analysed using a common analytic framework developed for cross-country comparison and themes were coded using Nvivo. We found that programme implementers across the three settings require multiple steps to catalyse scale-up. Advocating for government to adopt and finance health innovations requires: designing scalable innovations; embedding scale-up in programme design and allocating time and resources; building implementer capacity to catalyse scale-up; adopting effective approaches to advocacy; presenting strong evidence to support government decision making; involving government in programme design; invoking policy champions and networks; strengthening harmonisation among external programmes; aligning innovations with health systems and priorities. Other steps include: supporting government to develop policies and programmes and strengthening health systems and staff; promoting community uptake by involving media, community leaders, mobilisation teams and role models. We conclude that scale-up has no magic bullet solution - implementers must embrace multiple activities, and require substantial support from donors and governments in doing so.

District decision-making for health in low-income settings: a systematic literature review

Health management information systems (HMIS) produce large amounts of data about health service provision and population health, and provide opportunities for data-based decision-making in decentralized health systems. Yet the data are little-used locally. A well-defined approach to district-level decision-making using health data would help better meet the needs of the local population. In this second of four papers on district decision-making for health in low-income settings, our aim was to explore ways in which district administrators and health managers in low- and lower-middle-income countries use health data to make decisions, to describe the decision-making tools they used and identify challenges encountered when using these tools. A systematic literature review, following PRISMA guidelines, was undertaken. Experts were consulted about key sources of information. A search strategy was developed for 14 online databases of peer reviewed and grey literature. The resources were screened independently by two reviewers using pre-defined inclusion criteria. The 14 papers included were assessed for the quality of reported evidence and a descriptive evidence synthesis of the review findings was undertaken. We found 12 examples of tools to assist district-level decision-making, all of which included two key stages—identification of priorities, and development of an action plan to address them. Of those tools with more steps, four included steps to review or monitor the action plan agreed, suggesting the use of HMIS data. In eight papers HMIS data were used for prioritization. Challenges to decision-making processes fell into three main categories: the availability and quality of health and health facility data; human dynamics and financial constraints. Our findings suggest that evidence is available about a limited range of processes that include the use of data for decision-making at district level. Standardization and pre-testing in diverse settings would increase the potential that these tools could be used more widely.

District decision-making for health in low-income settings: a case study of the potential of public and private sector data in India and Ethiopia

Many low- and middle-income countries have pluralistic health systems where private for-profit and not-for-profit sectors complement the public sector: data shared across sectors can provide information for local decision-making. The third article in a series of four on district decision-making for health in low-income settings, this study shows the untapped potential of existing data through documenting the nature and type of data collected by the public and private health systems, data flow and sharing, use and inter-sectoral linkages in India and Ethiopia. In two districts in each country, semi-structured interviews were conducted with administrators and data managers to understand the type of data maintained and linkages with other sectors in terms of data sharing, flow and use. We created a database of all data elements maintained at district level, categorized by form and according to the six World Health Organization health system blocks. We used content analysis to capture the type of data available for different health system levels. Data flow in the public health sectors of both counties is sequential, formal and systematic. Although multiple sources of data exist outside the public health system, there is little formal sharing of data between sectors. Though not fully operational, Ethiopia has better developed formal structures for data sharing than India. In the private and public sectors, health data in both countries are collected in all six health system categories, with greatest focus on service delivery data and limited focus on supplies, health workforce, governance and contextual information. In the Indian private sector, there is a better balance than in the public sector of data across the six categories. In both India and Ethiopia the majority of data collected relate to maternal and child health. Both countries have huge potential for increased use of health data to guide district decision-making.

District decision-making for health in low- income settings: a feasibility study of a data-informed platform for health in India, Nigeria and Ethiopia

Low-resource settings often have limited use of local data for health system planning and decision-making. To promote local data use for decision-making and priority setting, we propose an adapted framework: a data-informed platform for health (DIPH) aimed at guiding coordination, bringing together key data from the public and private sectors on inputs and processes. In working to transform this framework from a concept to a health systems initiative, we undertook a series of implementation research activities including background assessment, testing and scaling up of the intervention. This first paper of four reports the feasibility of the approach in a district health systems context in five districts of India, Nigeria and Ethiopia. We selected five districts using predefined criteria and in collaboration with governments. After scoping visits, an in-depth field visit included interviews with key health stakeholders, focus group discussions with service-delivery staff and record review. For analysis, we used five dimensions of feasibility research based on the TELOS framework: technology and systems, economic, legal and political, operational and scheduling feasibility. We found no standardized process for data-based district level decision-making, and substantial obstacles in all three countries. Compared with study areas in Ethiopia and Nigeria, the health system in Uttar Pradesh is relatively amenable to the DIPH, having relative strengths in infrastructure, technological and technical expertise, and financial resources, as well as a district-level stakeholder forum. However, a key challenge is the absence of an effective legal framework for engagement with India’s extensive private health sector. While priority-setting may depend on factors beyond better use of local data, we conclude that a formative phase of intervention development and pilot-testing is warranted as a next step.

The stars seem aligned: a qualitative study to understand the effects of context on scale-up of maternal and newborn health innovations in Ethiopia India and Nigeria.

BackgroundDonors commonly fund innovative interventions to improve health in the hope that governments of low and middle-income countries will scale-up those that are shown to be effective. Yet innovations can be slow to be adopted by country governments and implemented at scale. Our study explores this problem by identifying key contextual factors influencing scale-up of maternal and newborn health innovations in three low-income settings: Ethiopia, the six states of northeast Nigeria and Uttar Pradesh state in India.MethodsWe conducted 150 semi-structured interviews in 2012/13 with stakeholders from government, development partner agencies, externally funded implementers including civil society organisations, academic institutions and professional associations to understand scale-up of innovations to improve the health of mothers and newborns these study settings. We analysed interview data with the aid of a common analytic framework to enable cross-country comparison, with Nvivo to code themes.ResultsWe found that multiple contextual factors enabled and undermined attempts to catalyse scale-up of donor-funded maternal and newborn health innovations. Factors influencing government decisions to accept innovations at scale included: how health policy decisions are made; prioritising and funding maternal and newborn health; and development partner harmonisation. Factors influencing the implementation of innovations at scale included: health systems capacity in the three settings; and security in northeast Nigeria. Contextual factors influencing beneficiary communities’ uptake of innovations at scale included: sociocultural contexts; and access to healthcare.ConclusionsWe conclude that context is critical: externally funded implementers need to assess and adapt for contexts if they are to successfully position an innovation for scale-up.

Taking knowledge users’ knowledge needs into account in health: an evidence synthesis framework

The increased demand for evidence-based practice in health policy in recent years has provoked a parallel increase in diverse evidence-based outputs designed to translate knowledge from researchers to policy makers and practitioners. Such knowledge translation ideally creates user-friendly outputs, tailored to meet information needs in a particular context for a particular audience. Yet matching users’ knowledge needs to the most suitable output can be challenging. We have developed an evidence synthesis framework to help knowledge users, brokers, commissioners and producers decide which type of output offers the best ‘fit’ between ‘need’ and ‘response’. We conducted a four-strand literature search for characteristics and methods of evidence synthesis outputs using databases of peer reviewed literature, specific journals, grey literature and references in relevant documents. Eight experts in synthesis designed to get research into policy and practice were also consulted to hone issues for consideration and ascertain key studies. In all, 24 documents were included in the literature review. From these we identified essential characteristics to consider when planning an output—Readability, Relevance, Rigour and Resources—which we then used to develop a process for matching users’ knowledge needs with an appropriate evidence synthesis output. We also identified 10 distinct evidence synthesis outputs, classifying them in the evidence synthesis framework under four domains: key features, utility, technical characteristics and resources, and in relation to six primary audience groups—professionals, practitioners, researchers, academics, advocates and policy makers. Users’ knowledge needs vary and meeting them successfully requires collaborative planning. The Framework should facilitate a more systematic assessment of the balance of essential characteristics required to select the best output for the purpose.

Catalysing scale-up of maternal and newborn health innovations: lessons from a case study in North-Eastern Nigeria

Scaling-up successful maternal and newborn health (MNH) innovations to a wider geographical area should improve the survival of more women and babies. This case study looked at an innovation known as the Emergency Transport Scheme (ETS) that aims to increase demand for maternal and newborn health (MNH) services in North-Eastern Nigeria by providing timely and affordable transport to health facilities for mothers and newborn babies in rural communities. Lessons from this study could help implementing organisations, national and state governments and donors to scale-up successful innovations in the future.

“It’s About the Idea Hitting the Bull’s Eye”: How Aid Effectiveness Can Catalyse the Scale-up of Health Innovations

Background: Since the global economic crisis, a harsher economic climate and global commitments to address the problems of global health and poverty have led to increased donor interest to fund effective health innovations that offer value for money. Simultaneously, further aid effectiveness is being sought through encouraging governments in low- and middle-income countries (LMICs) to strengthen their capacity to be self-supporting, rather than donor reliant. In practice, this often means donors fund pilot innovations for three to five years to demonstrate effectiveness and then advocate to the national government to adopt them for scale-up within country-wide health systems. We aim to connect the literature on scaling-up health innovations in LMICs with six key principles of aid effectiveness: country ownership; alignment; harmonisation; transparency and accountability; predictability; and civil society engagement and participation, based on our analysis of interviewees’ accounts of scale-up in such settings. Methods: We analysed 150 semi-structured qualitative interviews, to explore the factors catalysing and inhibiting the scale-up of maternal and newborn health (MNH) innovations in Ethiopia, northeast Nigeria and the State of Uttar Pradesh, India and identified links with the aid effectiveness principles. Our interviewees were purposively selected for their knowledge of scale-up in these settings, and represented a range of constituencies. We conducted a systematic analysis of the expanded field notes, using a framework approach to code a priori themes and identify emerging themes in NVivo 10. Results: Our analysis revealed that actions by donors, implementers and recipient governments to promote the scale-up of innovations strongly reflected many of the aid effectiveness principles embraced by well-known international agreements - including the Paris Declaration of Aid Effectiveness. Our findings show variations in the extent to which these six principles have been adopted in what are three diverse geographical settings, raising important implications for scaling health innovations in low- and middle-income countries. Conclusion: Our findings suggest that if donors, implementers and recipient governments were better able to put these principles into practice, the prospects for scaling externally funded health innovations as part of country health policies and programmes would be enhanced.

‘The development sector is a graveyard of pilot projects!’ Six critical actions for externally funded implementers to foster scale-up of maternal and newborn health innovations in low and middle-income countries

BackgroundDonors often fund projects that develop innovative practices in low and middle-income countries, hoping recipient governments will adopt and scale them within existing systems and programmes. Such innovations frequently end when project funding ends, limiting longer term potential in countries with weak health systems and pressing health needs. This paper aims to identify critical actions for externally funded project implementers to enable scale-up of maternal and newborn child health innovations originally funded by the Bill & Melinda Gates Foundation (‘the foundation’), or influenced by innovations that were originally funded by the foundation in three low-income settings: Ethiopia, the state of Uttar Pradesh in India and northeast Nigeria. We define scale-up as the adoption of donor-funded innovations beyond their original project settings and time periods.MethodsWe conducted 71 in-depth, semi-structured interviews with representatives from government, donors and other development partner agencies, donor-funded implementers including frontline providers, research organisations and professional associations. We explored three case study maternal and newborn innovations. Selection criteria were: a) innovations originally funded by the Bill & Melinda Gates Foundation (‘the foundation’), or influenced by innovations that were originally funded by the foundation; b) innovations for which a decision to scale-up had been made, allowing us to reflect on the factors influencing those decisions; c) innovations with increased geographical reach, benefitting a greater number of people, beyond districts where foundation-funded implementers were active. Our data were analysed based on a common analytic framework to aid cross-country comparisons.ResultsBased on study respondents’ accounts, we identified six critical steps that donor-funded implementers had taken to enable the adoption of maternal and newborn health innovations at scale: designing innovations for scale; generating evidence to influence and inform scale-up; harnessing the support of powerful individuals; being prepared for scale-up and responsive to change; ensuring continuity by being part of the transition to scale; and embracing the aid effectiveness principles of country ownership, alignment and harmonisation.ConclusionsSix critical actions identified in this study were associated with adopting and scaling maternal and newborn health innovations. However, scale-up is unpredictable and depends on factors outside implementers’ control.

The effect of implementation strength of basic emergency obstetric and newborn care (BEmONC) on facility deliveries and the met need for BEmONC at the primary health care level in Ethiopia

BackgroundBasic emergency obstetric and newborn care (BEmONC) is a primary health care level initiative promoted in low- and middle-income countries to reduce maternal and newborn mortality. Tailored support, including BEmONC training to providers, mentoring and monitoring through supportive supervision, provision of equipment and supplies, strengthening referral linkages, and improving infection-prevention practice, was provided in a package of interventions to 134 health centers, covering 91 rural districts of Ethiopia to ensure timely BEmONC care. In recent years, there has been a growing interest in measuring program implementation strength to evaluate public health gains. To assess the effectiveness of the BEmONC initiative, this study measures its implementation strength and examines the effect of its variability across intervention health centers on the rate of facility deliveries and the met need for BEmONC.MethodsBefore and after data from 134 intervention health centers were collected in April 2013 and July 2015. A BEmONC implementation strength index was constructed from seven input and five process indicators measured through observation, record review, and provider interview; while facility delivery rate and the met need for expected obstetric complications were measured from service statistics and patient records. We estimated the dose–response relationships between outcome and explanatory variables of interest using regression methods.ResultsThe BEmONC implementation strength index score, which ranged between zero and 10, increased statistically significantly from 4.3 at baseline to 6.7 at follow-up (p < .05). Correspondingly, the health center delivery rate significantly increased from 24% to 56% (p < .05). There was a dose–response relationship between the explanatory and outcome variables. For every unit increase in BEmONC implementation strength score there was a corresponding average of 4.5 percentage points (95% confidence interval: 2.1–6.9) increase in facility-based deliveries; while a higher score for BEmONC implementation strength of a health facility at follow-up was associated with a higher met need.ConclusionThe BEmONC initiative was effective in improving institutional deliveries and may have also improved the met need for BEmONC services. The BEmONC implementation strength index can be potentially used to monitor the implementation of BEmONC interventions.