Universal health coverage (UHC) intends to give everyone access to healthcare services without economic difficulties. It is the basic target of the World Health Organization. Underlying UHC is making decisions on policymaking and financing based on scientific facts. Evidence-informed decision-making (EIDM) systematically synthesizes and weighs different research evidence when planning new healthcare programs and policies. With EIDM usage, the decision-makers can deduce the most strategic and efficient solutions in the context of the population. This paper presents how realizing EIDM principles is helpful in the pursuit of UHC. It reviews case scenarios from various country settings and proposes tools for building EIDM capabilities to help more people receive needed healthcare.
How EIDM Supports UHC Implementation
Performing systematic research reviews of different research techniques allows for identifying the best ways to achieve universal access to priority services. An evaluation in Rwanda, where community health workers had been scaled up, found that it also led to a 15% expansion of basic maternal and childcare services, particularly in rural areas. This research led to the creation of a national community health strategic plan. The plan caused more than 45,000 community health workers to nationwide training and deployment. However, a meta-analysis on the conditional cash transfer programs also showed that primary healthcare intervention rates increased by 25% on average in low- and middle-income regions (Sharma et al., 2020). This conditional cash transfer model has been adopted by Mexico, Brazil, and other countries based on this information.
Setting Priorities and Allocating Resources Efficiently
Cost-effectiveness assessments in health care that are crucial for the right decisions for cost-effective resource allocation include the abolition of UHC. Consider the example in Ghana, where the multi-criteria decision-making analysis of some key public health programs showed that pocket-sized tuberculosis screening was the most abundant in public health per dollar spent. This move particularly saw the health ministry allocating part of the annual preventive care budget to the expansion of the model, which eventually led to the implementation by another 27 districts in five years (Majdzadeh, 2018). Primary health care provision received a boost in Nigeria, too, as the National Assembly used evidence of the positive impacts of basic services on the target population to convince its members to provide more funds for upgrading primary care centers in unserved regions with hopes that this would raise service coverage there from 34% to 60% and above.
Monitoring implementation allows understanding of challenges and keeps the data fresh. This makes it possible for the right measures to be taken by occasionally arising challenges. An example of this is the HIV drug resistance in Thailand. It warned doctors that drug resistance among new cases was increasing above 10% in some of the provinces bordering Myanmar and Cambodia as a result of cross-border transmission of resistant strains (Gopinathan & Ottersen, 2016). The multi-channel targeted campaigns were launched using community outreach workers and mobile messages such as text messages channeling behavioral science insights on persistence; these influenced adherence as implementation science has formed. Score after the campaign confirmed that a substantial part of patients properly handled their disease and had much better control over their health condition. New policies also allowed an earlier access of the anti-retroviral treatments to the border areas where resistance to these drugs was not as widespread. In sum, these instances display how harnessing the available research evidence works across the board in favor of implementing UHC through better decision-making on policies and budgets that create more positive impacts on health and access to it.
Setting Priorities and Allocating Resources Efficiently
A study and discounted analysis in Ghana measured how various public disease prevention programs affect the health system. The study revealed that screening for tuberculosis through mobile clinic vans was the best, considering the income and the results, compared to the stationary clinics and community outreach. Then, the Ghana Health Service decided to use some of the preventive care budget to expand the mobile clinic screening model (Majdzadeh, 2018). Over the next five years, this funding was allocated to run more mobile clinic operations, which in turn accounted for the provision of tuberculosis screenings in more than 27 additional districts nationwide. Rational allocation of resources instead of prioritization led to better access to vital services.
Anticipating Challenges and Improving Programs
Thailand’s surveillance program designed for HIV drug resistance gave precious information that helped to overcome the emerging challenges. Surveillance has exposed the progress of new HIV cases carrying drug resistance, having more than 10% in some northern provinces bordering Myanmar and Cambodia. This indicated that cross-border transmission contributes to the increasing drug resistance problem.
As a result, designs of adherence campaigns were taken out based on findings from implementation science research. Studies established the influence of social networks and mobile technologies on health behaviors to be significant. Community mobilizers and outreach workers purposely reached out to those at risk through community interaction, and text messaging in the local language further facilitated the reinforcement of prevention and treatment education (Baltussen et al., 2016). According to WHO recommendations, it was further changed to allow early HAART initiation in border areas.
These data-oriented, evidence-informed interventions completed the job of already implemented efforts. The viral suppression that serves as a crucial metric of treatment success was nearly 10% higher a year after the intervention in high prevalence areas compared to the baseline. Thailand showed how real-time monitoring followed by the multimodal method that draws on relevant research is a satisfactory solution in fighting against emerging UHC implementation issues.
Challenges to Applying EIDM in UHC
Resource limitations are the main obstacle we face in many contexts. The World Bank data shows that the percentage of an annual public health budget of less than one percent allocated to research is a common trend for low-income countries. This limits the scope of the important observational studies, clinical trials, and health surveys carried out continuously for the UHC at local and global levels (Baltussen et al., 2016). The attrition problem aggravates the situation because less than 10% of health professionals in sub-Saharan Africa are given formal research training. At the same time, many disease burdens exist, meaning the brain-drain challenge is evident.
Similarly, where research is produced, the integration challenge exists. On average, it takes almost 17 years for 14% of research findings to be used in the clinical guidelines or policy formulation, according to the analysis by the UK’s Cochrane Collaboration (Baltussen et al., 2016). Such explanations may include indeterminate or debatable findings, limited collaboration with stakeholders while doing research, and studies that do not immediately discuss policy-relevant questions and contexts.
Political and budgetary decisions often differ from evidence-based, long-term strategies. Political cycles provide the desired goals for the end of the election period, and the short-term deliverables are gaining the upper hand over prevention strategies or interventions with delayed results (Majdzadeh, 2018). Policy and fiscal decisions face fast timeframes, whereas research production takes a long process. Aside from a mismatch in priorities, researchers and policymakers hold different attitudes towards partnership, which hinders their effectiveness.
Conclusion
Universal health coverage (UHC) roll-out is about drawing and using evidence to progress toward coverage targets. The practical relevance of research evidence can be seen in various country case studies, and it is always of help to policy and program makers so they can make the best use of the resources and deliver the maximum impact. Even though research capacities in many settings still exist in somewhat primitive conditions and knowledge translation obstacles linger, the current trend of innovative, collaborative strategies exposes that tangible progress is somehow being made. Dedication to continuously revamping the research ecosystem and evidence-policy links is conditional on health systems that are more responsive and resilient globally. Implementing evidence-based, integrated, and multifaceted interventions in various country contexts can build leadership, support, and momentum for equitable, sustainable healthcare reforms.
References
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Baltussen, R., Jansen, M., & Bijlmakers, L. (2018). Stakeholder participation on the path to universal health coverage: evidence-informed deliberative processes. Tropical Medicine & International Health, 23(10), 1071–1074. https://doi.org/10.1111/tmi.13138
Gopinathan, U., & Ottersen, T. (2016). Evidence-Informed Deliberative Processes for Universal Health Coverage: Broadening the Scope Comment on “Priority Setting for Universal Health Coverage: We Need Evidence-Informed Deliberative Processes, Not Just More Evidence on Cost-Effectiveness.” International Journal of Health Policy and Management, 6(8), 473–475. https://doi.org/10.15171/ijhpm.2016.148
Majdzadeh, R. (2018). Time for tough decisions: The increasing need for evidence-informed decision-making. Medical Journal of the Islamic Republic of Iran, 535–536. https://doi.org/10.14196/mjiri.32.92
Sharma, M., Teerawattananon, Y., Luz, A., Li, R., Rattanavipapong, W., & Dabak, S. (2020). Institutionalizing Evidence-Informed Priority Setting for Universal Health Coverage: Lessons From Indonesia. INQUIRY: The Journal of Health Care Organization, Provision, and Financing, p. 57, 004695802092492. https://doi.org/10.1177/0046958020924920
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