Once defined in rhetorical but ultimately meaningless terms as “the conscientious, judicious and explicit use of current best evidence in making decisions about the care of individual patients”, evidence-based medicine rests on certain philosophical assumptions: a singular truth, ascertainable through empirical enquiry; a linear logic of causality in which interventions have particular effect sizes; rigour defined primarily in methodological terms (especially, a hierarchy of preferred study designs and tools for detecting bias); and a deconstructive approach to problem-solving (the evidence base is built by answering focused questions, typically framed as ‘PICO’—population-intervention-comparison-outcome).
The trouble with pandemics is that these assumptions rarely hold. A pandemic-sized problem can be framed and contested in multiple ways. Some research questions around COVID-19, most notably relating to drugs and vaccines, are amenable to randomised controlled trials (and where such trials were possible, they were established with impressive speed and efficiency). But many knowledge gaps are broader and cannot be reduced to PICO-style questions. Were care home deaths avoidable? Why did the global supply chain for personal protective equipment break down? What role does health system resilience play in controlling the pandemic? And so on….
In particular, upstream preventive public health interventions aimed at supporting widespread and sustained behaviour change across an entire population (as opposed to testing the impact of a short-term behaviour change in a select sample) rarely lend themselves to such a design. When implementing population-wide public health interventions—whether conventional measures such as diet or exercise, or COVID-19 related ones such as handwashing, social distancing and face coverings—we must not only persuade individuals to change their behavior but also adapt the environment to make such changes easier to make and sustain….
The 20th-century logic of evidence-based medicine, in which scientists pursued the goals of certainty, predictability and linear causality, remains useful in some circumstances (for example, the drug and vaccine trials referred to above). But at a population and system level, we need to embrace 21st-century epistemology and methods to study how best to cope with uncertainty, unpredictability and non-linear causality.
h/t medicinanarrativa.edu
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