We thought about it a little and think it should work…

Still stuck on the question of adaptation (so vague!), I explored a little more…

Clinical guidelines are often irrelevant in LMICs due to the fact that they are not commonly developed for or in these types of settings (Ehrhardt et al, 2012). The evidence on which many of these guidelines are based does not come from trials conducted in LMICs either because the research isn’t being done in these settings or there is an issue with study quality. Low quantity and quality of trials in LMICs is often the result of technical and infrastructure constraints, ethical issues, overburdened health systems, and lack of funding (Ehrhardt et al, 2012). Clinical guidelines based on evidence from high-income countries are thus not necessarily appropriate or applicable in LMICs and site-specific adaptation of guidelines might actually be less efficient and possibly harmful. Ehrhardt and Meyer (2012) argue for the mandatory, rigorous evaluation of guidelines in LMICs because, in their opinion, ‘adaptation without evaluation by use of adequate study designs is not good enough’.

This call for rigorous evaluation (i.e. using meaningful study methods such as clinical trials) is an important aspect of the the adaptation phase of the knowledge to action cycle that is missing from the framework presented by Graham et al (2006). It does make reference to the “activities that [individuals or groups] may engage in to tailor or customize the knowledge to their particular situation” (Graham et al, 2006, p. 20), but the language used to described how this is done (i.e. The process by which knowledge is adapted to a local setting “may be more or less formal”…; Some sort of “vetting or tailoring to the local context” is required…) leaves one believing that the ‘how’ is not overly important.

To address the issue of poor adaptability of clinical guidelines across settings, Ehrhardt and Meyer (2012) recommend that we pay more attention to: The setting in which a guideline has been developed and evaluated; the design processes addressing the question whether or not a guideline developed in HICs may also be suitable for LMICs; local adaptation of guidelines, and timely inclusion of relevant stakeholders and experts; and local evaluation of modified guidelines through either cost-effective implementation research or rigorous clinical trials. The issue of adaptability is not unique to the ‘knowledge’ contained in clinical guidelines. Spoth et al (2013) stress the importance of studying the adaptations of evidence-based prevention interventions and identify the need for strategies and methods for updating and adapting EBIs to local circumstances. This kind of implementation research will help in understanding whether adaptations affect outcomes, and if so, how (Spoth et al, 2013).

Although it seems to be accepted that adapting knowledge to local setting or context is an important part of the KT process, the rigor and formality with which this should be done is debatable. Ehrhardt and Meyer (2012) and Spoth et al (2013) both argue for the meticulous evaluation of modified/adapted interventions. Failure to do so can result in wasted resources, ineffective (or less effective) interventions, and possibly even harm. I think that the importance of this type of evaluation studies should not be glossed over, but I am left with these questions: What are the ethical implications of conducting clinical trials of interventions modified and/or adapted to LMIC settings when ‘best practices’ already exist? What are the ethical implications of not doing so?

References:

Ehrhardt, S et al. (2012). Transfer of evidence-based medical guidelines to low- and middle-income countries. Tropical Medicine and International Health, 17(2): 144-146.

Graham, ID et al. (2011). Lost in knowledge translation: time for a map?. The Journal of Continuing ducation in the Health Profession, 26(1), 13-24.

Spoth, R et al. (2013). Addressing core challenges for the next generation of type 2 translation research and systems: The translation science to population impact (Tsci Impact) Framework. Prev Sci, 14: 319-351.

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