Discussion
This is the first systematic review of reviews to provide a comprehensive and systematic mapping of the challenges related to translating health research and evidence into clinical practice, considered alongside barriers relating to translation into health policy. This review goes further to articulate possible facilitators that enable the translation of health research evidence into practice as expressed across included studies.
Despite convincing evidence from health research, translating evidence into clinical practice or policy can encounter multiple barriers. Translation to the real-world environments is critical for the success of any clinical practice or implementation of health policy. Research settings may adopt a design to limit the influence of uncontrolled variables, thereby limiting real-world influences on research. Evidence-based research alluded to the reduction in cardiac event mortality following the timely use of clopidogrel, yet, the response time was critical for mortality prevention in the context of real-world settings.37 Despite the existence of research evidence, clinicians have not been ready to perceive the full potential of statins. This may be attributed to the low adherence rates by patients, compared to those stated in the research evidence. This reflects the fact that research protocols do not reflect real life. Many factors may play a significant role in adherence levels such as motivation and access to medication access.37
Ten reviews highlighted that translating health research evidence into clinical practice is affected by several challenges, predominantly contributed by individual-related issues, followed by organisational factors. Existing barriers are further compounded by various professionals’ overall inadequacy of knowledge and skills to conduct, organise, utilise, and appraise research literature, vital to achieving the translation of health research evidence into clinical practice. Lack of education leading to disinterest, 38,39motivational challenges and suspicion over the potential of research evidence to be translated into clinical practice are additional professionals barriers reported.39,40 Translational barriers may be reduced by motivating healthcare professionals (micro-level). Individual-level facilitators involve a clear understanding of the target population, who could benefit from the research findings, so that the research evidence can be customised and communicated in an effective module, to enable easy translation. Our results are in accordance with the previous reports indicating successful dissemination and utilisation of research evidence following the identification of the appropriate audience and tailoring messages using appropriate mediums.41-43
At an organisational-level, translating evidence-based research into practice requires enormous resources and adequate time. Lack of resources such as availability of research databases and publications are organisation-level barriers for the translation of research into practice, also indirectly affecting professional skills. Time constraints and workload pressure, and lack of adequate workforce to read and understand research processes limit the translation of research into practice. Our findings have also been supported by other published reports.28,40
Our observations indicate mistrust by policymakers about the potential of research to translate into practice. This affects both the development of health policies and also systematic public investments for research programs. A sizable proportion of mistrust by the policymakers stems from their lack of knowledge for understanding research methods and limited skills in comparing research outcomes. Early identification and partnering with all the stakeholders (policymakers and beneficiaries of research such as the community) may overcome this challenge. Similar models have been suggested in earlier studies.44,45 Technology-driven interactive models provide all the stakeholders and beneficiaries with constant engagement and updating of information, to enable them to support evidence-based models.42,46-49