Health Research Program

Translating learning for action

This IR Tip describes best practices for translating implementation research (IR) learning to ensure uptake by program managers, providers, policy makers, and communities to improve maternal, newborn, and child health in low- and middle-income countries (see IR process steps and Figure 1.2 in IR Tip #1).

Learning from IR can be used in a number of key ways that will be discussed in this brief:

  1. for adaptive management of programs in real time
  2. to plan for scale-up of feasible and effective interventions
  3. for national policy development or revision

This IR Tip draws on lessons of USAID projects which applied IR as part of a broader collaborating, learning, and adapting (CLA) approach. The CLA approach helps to ensure that programs coordinate efforts, are grounded in a strong evidence base, and iteratively adapt to remain relevant and effective over time (see IR Tip #3). In addition to applying learning systematically within a program, dissemination of IR findings allows the leveraging of solutions to more programs in more places to achieve better outcomes more quickly for more people.

Planning with stakeholders for dissemination and use of IR findings

A key principle of successful IR is the engagement of stakeholders throughout the entire design, implementation, analysis, and dissemination process (see IR Tip #5). Stakeholders are people or groups with an interest or concern in the program and its effects. Engaging a wide range of stakeholder representatives from the beginning allows them to bring important perspectives and local knowledge that builds bridges to their communities. These bridges are critical for establishing trust, communicating learning from the IR, and creating support for changes that improve implementation. The challenge of introducing stakeholders to information and ideas for change is to communicate them in a way that encourages stakeholders to support action based on research evidence rather than only on assumptions and beliefs.

Synthesizing and translating data

Strong data analysis and documentation processes are the foundation for synthesizing and applying implementation learning to adapt and improve programs. The findings that emerge may prove or disprove underlying assumptions, confirm implementation strategies are working as planned or not, identify missing pieces, document changing outcomes, and reveal opportunities for enhancement.

Translating and disseminating IR findings in a compelling way that builds stakeholders’ and key audiences’ understanding of and appreciation for using evidence and sharing learning can result in two important outcomes. First, it can build commitment to changing the program as needed and contribute to scaling up of adapted approaches to other relevant communities and countries. Second, nurturing stakeholder capabilities to value and apply IR helps cultivate a broader culture of learning which continuously improves health systems over time and overall.

However, developing an effective dissemination process that meet the needs of a wide range of stakeholders can be challenging. From inception, identify stakeholder audiences and clarify what actions each group might be expected to take with IR learning. What information will they need and how can that information be best packaged and presented to be understood and actionable? Methods of communication and engagement will vary by stakeholder group and by stage of implementation from design to scale up, but participatory approaches and user-friendly materials are likely to be most effective. Last, how will you know what changes are resulting from sharing knowledge? Learn from dissemination by documenting when there is uptake of valuable practices and when non-valuable practices end.

Links for common communication tools are provided in Box 10.1.

Applying implementation research findings for action

The ultimate purpose of IR is to use the findings to make better decisions and adjustments to policies, plans, and programs to achieve, scale, and sustain morbidity and mortality reduction goals.

Adaptive management is central to IR. Prior to taking action to adapt and act, a program generally will have a pause and reflection to consider information, followed by decisions and adjustments in response to the information and/or changes in context. This intentional approach is called “adaptive management” (USAID 2021 and USAID 2018). Adaptive management is not about changing goals during implementation, but rather about changing the path being used to achieve the goals.

Implementation research starts as a study (data collection methods, selection of respondents or data sources, analysis), but as information is generated, flexibility and executing change become the most important features. Learning and the development of these capabilities can be applied to interventions, policies, and delivery systems. If successful, these will be reflected in leadership, decision making, and the spread of solutions. Building skill, confidence, and comfort with adaptive management, flexibility, and change or transformation will in turn enable more effective IR.

Case studies

Case study on using IR for adaptive management: Single payer national insurance reform in Indonesia
The USAID Health Finance and Governance Project supported a study in Indonesia to help the Ministry of Health (MOH) understand how its single-payer national insurance reform scheme was affecting primary care. During the study, program managers used research information to facilitate and follow the effects of real-time corrective actions. Cycle 1 study findings indicated uneven understanding of the insurance scheme’s regulations, uneven readiness to implement it, and little change in productivity. This prompted the MOH to consult with district health officers to make written materials more understandable, and to set up a pay for performance incentive scheme to improve productivity. Cycle 2 of the study demonstrated increased primary care usage based on better application of the regulations but inconsistent application of pay for performance, leading to requests to adapt the system to pay for achievement of targets. Adaptive management was ongoing, with decision makers engaged throughout the process.

Case study on using IR findings for adaptive management and policy development: Revisions to policy for management of PSBI in Bangladesh
In 2015, the Government of Bangladesh partnered with funding agencies, implementation groups, and research organizations to test how best to operationalize new guidelines for the management of possible serious bacterial infection (PSBI) in young infants when referral is not feasible. A group of partners including the Ministry of Health and Family Welfare (MOHFW), USAID’s MaMoni Health Systems Strengthening Project, the Saving Newborn Lives Project of Save the Children, and Johns Hopkins Bloomberg School of Public Health conducted IR in several sites using an adapted action learning cycle approach [Plan-Do-Study-Act (PDSA)] to deliver a package of services and support for program scale-up. Study activities embedded mixed methods data collection, and the IR team shared lessons around implementation in periodic stakeholder meetings with partners such MOHFW. Implementation strategies were adjusted in real time based on learning from efforts to build health facility readiness, measuring provider performance on applying the intervention algorithm, and monitoring the quality of program delivery. Routine stakeholder engagement was critical to cross-site learning and building confidence in the findings and ensured policy makers were ready to incorporate what was learned in the scale-up of policies, guidelines, and programs.

Case study on using IR findings for adaptive management and scale up: Testing a respectful maternity care package of interventions in Kenya
Disrespect and abuse of women during labor and delivery strongly affect women’s decisions to deliver in health facilities, which nonetheless are often are the best option them and their babies (Bohren 2019). The USAID-funded TRAction/Heshima project in Kenya used IR to implement an interactive three-pronged set of interventions at policy, health facility, and community levels. First, technical meetings, which included government, civil society, and professional associations, established continuous dialogue. At health facilities, staff were oriented and trained to provide respectful maternity care, and linkages with communities were strengthened for accountability. Communities were also trained, and mediated dialogues and counseling with providers were held. Heshima employed a learning-by-doing process from the outset, such that these new interventions were refined and extended to additional facilities. In addition, the process was adapted to reflect context-specific changes, including rapid devolution of health services and the initiation of free maternity service provision in public facilities. Reporting and observation during and after the intervention demonstrated decreased disrespect and abuse and greater satisfaction with facility delivery.


Key resources

Peters D, Tran N, Adam T. (2013) Implementation research in health: A practical guide

USAID Learning Lab. (2018) Program cycle discussion note: Adaptive Management.


References

Abuya T, Ndwiga C, Ritter J et al. (2015) The effect of a multi-component intervention on disrespect and abuse during childbirth in Kenya. BMC Pregnancy and Childbirth 15.

Applegate JA, Ahmed S, Khan MA, et al. (2019) Early implementation of guidelines for managing young infants with possible serious bacterial infection in Bangladesh. BMJ Global Health 4(6).

Blog Tyrant. (2019) How to write a good blog post: 12 expert tips.

Bohren M, et al. (2019) How women are treated during facility-based childbirth in four countries: a cross-sectional study with labour observations and community-based surveys. Lancet 394(10210):1750–63.

Centers for Disease Control and Prevention (CDC). Resources for writing briefs.

Downs JS. (2014). Prescriptive scientific narratives. Proceedings of the National Academy of Sciences 111 (Supplement 4): 13627-13633.

Eichler R, Gigli S, LeRoy L. (2018) Implementation research to strengthen health care financing reforms toward universal health coverage in Indonesia: A mixed-methods approach to real-world monitoring. Global Health: Science and Practice 6(4):747-753

Equator Network. (2017) Standards for reporting implementation studies (StaRI) statement.

Martinez-Conde S, et al. (2019) The storytelling brain: How neuroscience stories help bridge the gap between research and society. J Neurosci 39(42):8285-8290.

Otten JJ, Cheng K, and Drewnowski A. (2015). Infographics and public policy: Using data visualization to convey complex information. Health Affairs 34(11).

Peters DH, Tran NN, Adam T. (2013) Implementation research in health: A practical guide.

Petra, The Research Companion. (2016) How to choose a conference then write an abstract that gets you noticed.

QED Group. (2013) Communities of practice.

Ross-Hellauer T et al. (2020) Ten simple rules for innovative dissemination of research. PLOS Computational Biology 16(4).

USAID. (2021) ADS Chapter 201. Operational policy for the program cycle. Functional series 201-programming.

USAID Learning Lab. Understanding CLA.

USAID Learning Lab. (2013) Webinars guidance.

USAID Learning Lab. (2018) Program cycle discussion note: Adaptive management.

Wensing M, Grol R. (2019). Knowledge translation in health: How implementation science could contribute more. BMC Medicine 17(88).

World Health Organization Alliance for Health Policy and Systems Research. (2015) Policy dialogue: What it is and how it can contribute to evidence-informed decision-making.