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