Abstract
Low- and middle-income countries (LMICs) bear the brunt of communicable and non-communicable diseases and experience higher mortality and poor health outcomes compared to resource-rich countries. Chronic resource deficits in LMICs impede their ability to successfully address vexing health issues. Implementation science provides researchers with an approach to develop specific interventions that can generate and/or maximize resources to facilitate the implementation of other public health interventions, in resource-constrained LMIC settings. Resources generated from these interventions could be in the form of increased health workers’ skills, task shifting to free up higher-skilled health workers, increasing laboratory capacity, and using supply chain innovations to make medications available. Pivotal to the success of such interventions is ensuring feasibility in the LMIC context. We selected and appraised three case studies of evidence-based resource-generating health interventions based in LMICs (Zambia, Zimbabwe, and Madagascar), which generated or maximized resources to facilitate ongoing health services. We used a determinant implementation framework—Consolidated Framework for Implementation Research (CFIR) to identify and map contextual factors that are reported to influence implementation feasibility in an LMIC setting. Contextual factors influencing the feasibility of these interventions included leadership engagement, local capacity building and readiness for research and implementing evidence-based practices (EBPs), infrastructural support for multilevel scale-up, and cultural and contextual adaptations. These factors highlight the importance of utilizing implementation science frameworks to evaluate, guide, and execute feasible public health interventions and projects in resource-limited settings. Within LMICs, we recommend EBPs incorporate feasible resource-generating components in health interventions to ensure improved and sustained optimal health outcomes.
Keywords
Background
Low- and middle-income countries (LMICs) bear most of the global health burden, and by World Bank economic and development indicators, have significant resource constraints that limit their ability to tackle these health issues—a phenomenon known as inverse care law. 1 With inverse care law at play, LMICs experience higher amenable mortality, that is, “the mortality that existing effective healthcare technologies could eliminate if they were delivered successfully to all those who can benefit,” which have a detrimental impact on their populations.2,3 Tackling this reality in LMICs is complicated by the time delay in translating evidence-based health interventions to real-world settings and the existing deficit of resources to effectively implement and sustain public health interventions.1,4
Implementation science is focused on finding “what works,” “why it works,” and “how it can be applied” to benefit populations by improving and maximizing the health impact of evidence-based practices (EBPs). 5 In this regard, EBPs would be the integration of the “conscientious, explicit, and judicious use of current best evidence in making decisions about the care of individual patients” and individual clinical/professional expertise. Another objective of implementation science is evaluating the successful delivery of EBPs 6 that ideally should attain maximum reach, efficacy, adoption, implementation, and sustainability within the populations the EBPs are being delivered. 7 Maximum adoption is context-specific and attainable if researchers and implementers are intentional about incorporating elements that can achieve successful implementation in the design, planning, and execution of the intervention(s) via an iterative process. 6 Some desired outcomes of the implementation of EBPs include acceptability, feasibility, and sustainability of the intervention within the context and target population(s). 6
There is a growing body of implementation science theories, models, and frameworks that serve to: “(i) describe and/or guide the process of translating research to practice, (ii) understand and/or explain what influences implementation outcomes, and (iii) evaluate implementation.” 8 One framework that can explain the vital role context plays in achieving implementation success in specific settings, such as LMICs is the Consolidated Framework for Implementation Research (CFIR).9,10 CFIR consolidates overlapping constructs from different implementation theories (n = 19) into one meta-theoretical, determinant framework, with which researchers can identify the specific domains of constructs, most relevant to their implementation setting in order to guide/evaluate/explain implementation processes and outcomes. 9 As a determinant framework, CFIR is useful for identifying factors that facilitate and hinder implementation. 8 CFIR consists of five main domains namely: “Intervention Characteristics,” “Outer Setting,” “Inner Setting,” “Characteristics of Individuals,” and “Process.” Of these five domains, “Outer Setting” and “Inner Setting” consist of constructs that characterize contextual factors to consider in implementation work. “Outer Setting” “includes economic, political, and social context within which an organization resides” and “Inner Setting” “includes features of structural, political, and cultural contexts through which the implementation process will proceed.” The political context in “Outer Setting” refers to political influences from the larger society where an intervention is being implemented while the political context in “Inner Setting” refers to the organizational politics in the organization/setting housing an implementation effort. 9 Other implementation science frameworks exist but their use in LMICs has been very limited or has not yet occurred. 11
Current literature highlights inadequate use of implementation science frameworks to develop, execute, and evaluate EBPs in LMICs, which could explain the striking deficit of sustainable EBPs in these settings.12,13 This gap in knowledge and application of implementation methodologies results in loss of resources (time, money, and personnel efforts) and development of unsustainable and cost-ineffective interventions in LMICs, which results in a detrimental impact on population health outcomes.12-14 Moreover, the potential for implementation science to be more relevant in LMICs for developing and executing sustainable strategies that generate resources or maximize the limited resources available in these settings is essential to bridge disease prevention and management gaps in these countries. 5
In this paper, we continue the discourse from the 2018 commentary by Yapa and Bärnighausen on implementation science in resource-poor countries and communities by applying CFIR to highlight specific ways implementation science can be used to understand and advance interventions, which generate and/or maximize resources to facilitate other health interventions in LMIC context. 3 In applying CFIR, we focus on the role of contextual domains to explain contextual influence on the implementation feasibility of resource-generating/maximizing interventions. Yapa and Bärnighausen explained that the theoretical frameworks that support implementation science typically consider resources to be a significant contextual factor used to assist with important program elements such as predicting feasibility, explaining success/failure, adapting EBPs to fit local constraints, and designing an appropriate process to account for these constraints. It is their argument, however, that for resource-poor settings, resources are much more central and as such are viewed as primary research objects instead of contextual factors. Furthermore, they state that within this paradigm of implementation science studies that distinguish resources as a focal point, many researchers aim to investigate new ways to generate resources in order to facilitate the application of EBPs to routine care. Such strategies include the use of tele-education and telemedicine to advance the skillset of higher-skilled workers, task shifting to increase the workforce and alleviate the strain on higher-skilled workers, and increasing laboratory capacity through new technologies and supply chains. A few other studies focused on finding ways to maximize resources by changing behavior and utilization.
Moreover, Yapa and Bärnighausen identified three approaches for implementation science in resource-poor countries and communities. First, constraints found in resource-poor countries and communities are a motivating element for great innovation in intervention processes and methods. These limitations in resources force necessary creativity—in order to circumvent challenges—that would not be possible otherwise. Second, there is an opportunity for reverse innovation that transfers strategies adapted first in resource-poor countries and communities to resource-rich settings. And finally, there is a significant potential for collaboration between policymakers in resource-poor countries and communities and implementation scientists.
Pre-existing financial constraints of resource settings are the most pragmatic of the three approaches discussed by Yapa and Bärnighausen for resource-poor countries and communities to increase financial resources for healthcare. 3 Table 1 provides categories of the different types of resource generation strategies from a review of several health interventions implemented in resource-poor settings conducted by Yapa and Bärnighausen. 3 They also presented implementation science as a fitting paradigm to advance this approach. For this paper, we define resource generation as “the creation of new resources to deliver effective health interventions given the existing financial constraints” based on Yapa and Bärnighausen’s recommendations. This definition is a coherent summation that aligns with similar definitions used by the World Bank, World Health Organization (WHO), and other international organizations working in resource-constrained settings. 3 In the context of LMICs, assessment of feasibility is also needed during the pre-implementation and design phase of the intervention, especially if the eventual outcome is to generate or maximize resources to facilitate other health interventions. Systematic reviews of the literature for non-communicable diseases (NCDs) suggest that this meticulous step in pre-implementation is needed to properly plan and execute implementation research studies, which can achieve multiple goals including resource generation.15,16
Yapa and Bärnighausen’s resource generating categories.
Methods
We conducted a case-studies review of interventions that generated or maximized resources to facilitate effective public health interventions in LMICs. A systematic search using PubMed, Google Scholar, and Cochrane library was conducted using the following terms: Implementation Science + Resource-Poor, Implementation Science + LMICs + Resource-Poor, Resource Generation + Implementation Science + LMICs, Evidence-Based Practices in Resource-Poor Setting, Implementation Science + Task Shifting + LMICs, and Mental Health + Task Shifting + LMICs. Inclusion criteria were articles and studies that took place primarily in LMICs and had a resource generation component. Exclusion criteria were studies that were implemented in high-income countries and did not have a strong focus on resource generation. We sampled three public health interventions from the pool of articles (see Supplemental Appendix) that emerged from the literature search (Table 2). The three studies chosen amongst several LMIC-based, resource-generating interventions, addressed a health need, and generated or maximized resources as part of the intervention. These studies were noteworthy examples of successful implementation science projects in LMICs and each one tackled a different emergent health concern. A literature search of emerging health concerns in LMICs and solutions to tackle them was also conducted and among the top issues were reproductive/sexual health, family planning, mental health concerns, and problems with access to care. Yapa and Bärnighausen’s categorization of resource generation was then applied to this sampling. We used CFIR to identify and map contextual factors that are reported to influence the feasible implementation of these case studies, given an LMIC setting. We synthesized findings from these interventions with our appraisal for contextual factors to spotlight the broader implications of utilizing implementation science methodology in the development and implementation of interventions that address resource availability and generation for public health in LMICs.
Summary of study characteristics.
Study Descriptions
The sampled studies addressed healthcare delivery services, mental health prevention and psychosocial support, and family planning services in Zambia, Zimbabwe, and Madagascar respectively (Table 2). Each study utilized a different strategy to generate resources as a core component of the evidence-based interventions being implemented; each strategy was connected to at least two of Yapa and Bärnighausen’s categories of resource-generation. We provide brief descriptions of the sampled studies as follows:
Appraisal of Contextual Factors Influential to Feasibility of Resource-Generating Studies
Using CFIR’s contextual constructs (see Table 3); there was reported evidence of contextual factors that influenced the feasibility and effectiveness of the studies, either as facilitators or barriers. Most of the factors identified were contextual facilitators of feasible implementation and effectiveness of these interventions. Of the 5 main Inner Setting constructs, Readiness for Implementation, featuring 3 sub-constructs of Leadership Engagement, Available Resources, and Access to Knowledge and Information recorded an abundance of evidence across all 3 studies. For instance, in every intervention, training was provided as a resource through building local capacity for implementation. Additional resources include the provision of space (benches on clinic grounds for Friendship Bench-Zimbabwe), provision of fuel and motorcycle maintenance services for Riders- Zambia, and training and accreditation of MSM Blue Star social franchisees in Madagascar to supply services for the youth vouchers. There was also evidence of viable stakeholder engagement, especially with leadership from Ministries and Departments of Health and clinical leadership at health facilities. Leadership engagement ranged from a close working relationship in developing and implementing the interventions as seen in the Friendship Bench in Zimbabwe to consulting and gathering information from clinical managers as seen in Riders-Zambia. Implementers easily accessed information and knowledge about the intervention via a network of trained supervisors and clinicians and provision of manuals for LHWs for Friendship Bench-Zimbabwe, and quality assurance monitoring and support for Blue Star social franchisees in MSM.
Mapping contextual facilitators and barriers to CFIR inner and outer setting constructs.
Abbreviation: NR, not reported
−Barrier
Likewise, several other facilitators identified in all 3 studies mapped on to another inner setting construct, namely Implementation Climate. Implementation Climate has 6 sub-constructs of which “Compatibility” and “Goals and Feedback” characterized most of the facilitators linked to this construct. For instance, across all 3 studies, an intentional effort was made to adapt the intervention and implementation process to fit the setting, either culturally as was observed in the training of LHWs and the use of the locally validated SSQ-14 for screening for common mental disorders in Zimbabwe. Similarly, interventions were tailored to recipients’ conditions as was observed in youth-friendly training of community health educators (CHEs) and Blue Star social franchisees operators to counsel, refer and provide services to Madagascan youths redeeming vouchers. The singular contextual barrier identified in this appraisal—which falls under the Compatibility sub-construct, was that motorcycle use was not maximized in the Riders program in Zambia as there was a missed opportunity to grant motorcycle access to community health workers who specialized in and carried out more rural outreach activities than the crop of health workers who got the Riders motorcycles, but had competing health duties, besides rural outreaches to perform at clinic facilities. Channels for communicating goals and feedback on the implementation and intervention experience ranged from weekly productivity surveys of health workers and a mid-study supplementary survey of intervention recipients on service experience in the Riders program, to focus group discussions and questionnaires on implementation experience among LHWs in the Friendship Bench program. MSM used client and provider feedback from a similar Marie Stopes youth voucher program in Zimbabwe to enhance the intervention offered in Madagascar.
Among the 4 constructs under the Outer Setting CFIR domain, “Patient Needs and Resources” unanimously provided evidence of a recipient-centered approach to developing and implementing the interventions to cater to the pressing needs of recipients without depleting their already limited resources. In the case of MSM, the youth vouchers provided free sexual and reproductive health services to youth recipients. During the Friendship Bench pilot in Zimbabwe, financially distressed participants were encouraged to join local income-generating avenues (peanut butter making and recycling) being offered by the program. The entire premise of the Riders program in Zambia was to provide well-maintained motorcycle fleet to eliminate the barrier of transportation challenges to access health services for remote community dwellers.
An Exemplary Feasibility Assessment Profile for Resource Generation Interventions in LMICs—The Friendship Bench, Zimbabwe
Inadequate assessment of feasibility contributes to a suboptimal implementation of evidence-based interventions and subsequently undesired intervention outcomes. According to Bowen and colleagues, in order to guarantee feasible interventions, we should be asking three main questions about an intervention: (1) Can the intervention work?—a question asked at the initial intervention development phase; (2) Does the intervention work?—a question asked after some evidence has emerged that an intervention might work; (3) Will the intervention work?—a question asked after an intervention is proven to be efficacious and effective and efforts are being made to translate the intervention into practice in diverse settings. 23
The Friendship Bench team investigated all three types of feasibility questions about task shifting to LHWs to provide psychosocial support and manage common mental health disorders. Assessing feasibility should also focus on the following aspects of an intervention: acceptability, demand, practicality, implementation, expansion, integration, adaptation, and limited efficacy testing. Depending on which of the 3 main questions being asked, each focus area has a particular set of outcomes, with different assessments. Some include focus groups, surveys, pre-post studies, quasi-experimental studies, cost-effectiveness analyses, and randomized controlled trials. 23
Of the three studies, The Friendship Bench research group closely adhered to Bowen’s recommendations for assessing feasibility. There was detailed and deliberate reporting on the pre-implementation process and development of the intervention at different phases, that is, needs assessment of facilities and stakeholders (LHWs and clients), pilot and feasibility study, and effectiveness trial. The team conducted a rigorous and intentional assessment of the pre-implementation phases of this intervention, which started with a systematic review of psychological interventions for common mental disorders in LMICs, followed up with a pilot study (pre-post test study design), 22 which doubled as a feasibility study of the intervention that would also inform on an intervention scale-up. In the pilot study, the intervention acceptability was evaluated. 22 In order to develop the effectiveness trial, which also scaled up Friendship Bench from 3 to 12 clinics, the research team partnered with the Harare City Health Department, conducted a needs assessment of their clinics, and a competency assessment of the 300 LHWs of the health department. 18 There were also series of focus group discussions and in-depth interviews with LHWs and clients for insight into the delivery and reception of this intervention. These pre-implementation and intervention development activities informed the adaptation of the intervention for the effectiveness trial.
The problem-solving therapy (PST) intervention underwent cultural validity and adaptation and used contextually relevant health workers cadre, which made it fitting for the Zimbabwean community setting.18,22 They also integrated supportive intervention components, which included providing supervision and support via voice calls and SMS messages using mobile devices and an income-generating activity such as peanut butter manufacturing, and crocheting bags from recycled plastic materials.18,22
This holistic approach to the implementation and reiterative development and cultural adaptation of the intervention contributed to the feasibility of the intervention in the Zimbabwean context. With these processes, the research team was able to assess and ensure acceptability, adoption, and appropriateness of the intervention—all three qualities cumulatively increasing the feasibility of the intervention.
As demonstrated in the three case studies appraised, context inevitably plays a significant role in executing feasible resource-generating health interventions in LMICs. Evaluating and identifying contextual factors that influence the feasibility of EBPs should be a top priority for researchers and implementers of resource-generating interventions in LMICs. Central to the analysis of the role and influence of context on the feasibility of these interventions is capturing key actors’ (individual researchers/experts/implementers) perceptions, lessons learned and recall of the implementation process, and how these observations and experiences shape the implementation process. 24 Within implementation science discourse, there is yet to be a situationally tailored and validated toolkit that researchers and implementers of interventions in LMICs can use to identify and capture the degree of influence of contextual factors on the feasibility of interventions in resource-constrained settings.
Conclusion
LMICs experience higher morbidity and mortality, compared to their resource-rich counterparts because of chronic resource deficits in tackling health issues. Implementation science provides researchers with evidence-based strategies to develop sustainable interventions with the potential to generate resources to facilitate the implementation of public health strategies, in resource-constrained settings such as LMICs. We searched the literature and found three noteworthy examples that provided the basis for a case-studies review of resource-generating interventions from Zambia, Zimbabwe, and Madagascar. This commentary advances the discourse on utilizing implementation science frameworks to evaluate the planning, execution, successes, and contextual facilitators and barriers of these types of interventions in low-resource settings. The critical appraisal of these studies demonstrates that contextual factors including—leadership and stakeholder engagement, building local capacity by training existing networks of health workers, cultural and contextual adaptations of interventions, supportive supervisory networks, optimizing routine client, provider, and implementer feedback channels to improve intervention, presence of capacity for research implementation, and infrastructure to support implementing and potential scaling of EBPs at local, regional or national levels are essential for feasible resource generation and maximization for public health interventions in LMICs. Furthermore, an exemplary assessment of intervention feasibility should include detailed and deliberate reporting on the pre-implementation process and development of the intervention at different phases, that is, needs assessment of facilities and stakeholders, pilot and feasibility study, and effectiveness trial, as observed in the Friendship Bench intervention. There remains a gap in the literature about tailored and validated tools and measures for assessing feasibility and the degree of contextual influence on the feasibility of interventions in resource-constrained settings. Nonetheless, the pillars of implementation science as espoused by the prominent determinant framework—CFIR can provide a roadmap for conceptualizing and executing novel, contextually relevant interventions and programs to generate and maximize resources in LMICs to address vexing health problems.
Supplemental Material
sj-pdf-1-his-10.1177_1178632921999652 – Supplemental material for The Role of Implementation Science in Advancing Resource Generation for Health Interventions in Low- and Middle-Income Countries
Supplemental material, sj-pdf-1-his-10.1177_1178632921999652 for The Role of Implementation Science in Advancing Resource Generation for Health Interventions in Low- and Middle-Income Countries by Temitope Ojo, Laetitia Kabasele, Bethanny Boyd, Scholastica Enechukwu, Nessa Ryan, Joyce Gyamfi and Emmanuel Peprah in Health Services Insights
Footnotes
Acknowledgements
We are grateful to the members of the Implementing Sustain-able Evidence-based interventions through Engagement (ISEE) Lab at New York University School of Global Public Health for their feedback on this paper.
Funding:
The author(s) received no financial support for the research, authorship, and/or publication of this article.
Declaration Of Conflicting Interests:
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Author Contributions
TO, LK and EP conceived the idea of this perspective piece. TO, LK, BB and SE developed the manuscript by sourcing for information in published literature and synthesizing data from the case studies, discussed in the manuscript. EP, JG and NR provided critical feedback on the tone and content of the manuscript. All authors contributed to the editing of the manuscript.
Availability of Data and Materials
No data was collected in writing this manuscript. No other form of underlying research materials was used in this manuscript outside of the results reported in the published papers that were central to our manuscript.
Supplemental Material
Supplemental material for this article is available online.
