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Clinical intuition versus statistics: different modes of tacit knowledge in clinical epidemiology and evidence-based medicine

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Abstract

Despite its phenomenal success since its inception in the early nineteen-nineties, the evidence-based medicine movement has not succeeded in shaking off an epistemological critique derived from the experiential or tacit dimensions of clinical reasoning about particular individuals. This critique claims that the evidence-based medicine model does not take account of tacit knowing as developed by the philosopher Michael Polanyi. However, the epistemology of evidence-based medicine is premised on the elimination of the tacit dimension from clinical judgment. This is demonstrated through analyzing the dichotomy between clinical and statistical intuition in evidence-based medicine’s epistemology of clinical reasoning. I argue that clinical epidemiology presents a more nuanced epistemological model for the application of statistical epidemiology to the clinical context. Polanyi’s theory of tacit knowing is compatible with the model of clinical reasoning associated with clinical epidemiology, but not evidence-based medicine.

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Notes

  1. Often, Polanyi’s tacit knowing is referred to as tacit knowledge. While these two terms are synonymous, Stephen Henry, who provided useful comments on this paper, has pointed out to me that Polanyi referred to tacit knowing rather than tacit knowledge. Knowing as opposed to knowledge is a more fluid term emphasizing the fluid nature of human cognition.

  2. Polanyi refers to intuition in his major work, Personal Knowledge [5]. He also deals explicitly with intuition in his essay on intuition in scientific reasoning, “Creative Imagination” [6], and Science, Faith and Society [7]. Polanyi does not argue for the traditional philosophical conception of intuition as incorrigible certainty, but as an element of practical reasoning. While intuition covers over hidden logical associations, this does not preclude, but rather requires that we spend time trying to ascertain the tacit elements of scientific reasoning. Clinical intuition as used in this paper shares this meaning with Polanyi’s notion of practical intuition. As such, it must be distinguished from philosophical intuition, for example Kantian intuition, as well as the feminist literature around intuition as a kind of sixth sense. Polanyi’s theory of tacit knowing will be elucidated in more detail towards the conclusion of this paper.

  3. Tim Thornton in a recent article has argued that incorporating tacit knowledge into its epistemology would provide the unifying factor in evidence-based medicine and clinical judgment [8]. Through an appeal to tacit knowledge, Thornton intends to unify the tripartite division of evidence-based medicine, i.e., the integration of research evidence with clinical expertise and patient values. Thornton claims that incorporation of tacit knowledge into its paradigm would undermine the view of evidence-based medicine as algorithmic, or more pejoratively a form of “cookbook medicine.” In another article, David Smith attempts to find the balance between evidence-based medicine and Polanyi’s theory of tacit knowing [9]. Smith criticizes those who attempt to displace evidence-based medicine by tacit knowing. Yet, as argued in this paper, the epistemological issue is not in favoring either tacit knowing or statistical epidemiology, but in mediating between the two, a process which is better accounted for through clinical epidemiology than evidence-based medicine.

  4. Even though there have been developments in evidence-based medicine since Sackett, this paper concentrates on Sackett’s contribution since he laid the intellectual foundations for the movement, which as far as I am aware have not been superseded.

  5. Sackett refers to the evidence-based medicine approach as deductive or hypothetico-deductive. He appropriates this scheme from Peter Medawar’s 1969 study, Induction and Intuition in Scientific Thought [13]

  6. Decision analysis, for its part, refers to the statistical evaluation of the process of cognition of decision-making. Clinical decision analysis refers to the application of statistical methods to evaluate the cognitive processes of decision-making in medicine. Because it deals with cognitive processes of clinical judgment, clinical decision analysis is better suited than evidence-based medicine for incorporating tacit knowing, yet it is also characterized by the perspective that sees everyday decision making as statistically error-prone.

  7. Fisher’s discovery of randomization was an extension of the discovery of correlation discovered by Francis Galton (1822–1911) and refined by Karl Pearson (1857–1936).

  8. For a comparison of Fisher and Bradford Hill, see the series of papers published in the International Journal of Epidemiology (2003) 32: 922–948.

  9. While Bradford Hill did not articulate how this would work, the problem is one of combining statistical data with tacit knowing pertaining to individuals. At the very least Bradford Hill identified the problem of applying statistical data to individual contexts, even though he did not provide a detailed solution to this conundrum.

  10. He is also somewhat infamously remembered for his opposition to the first statistical study authored by Richard Doll and Bradford Hill unequivocally associating lung cancer with smoking.

  11. Fisher’s concept of specifying rigorous uncertainty is comparable with the Viennese philosopher Karl Popper’s famous theory of falsifiability.

  12. While Feinstein was concerned at improving quantitative analysis of clinical data, his approach is also amenable for qualitative investigations.

  13. The uncritical reliance on randomized controlled trials has come under increased scrutiny during the last few years. For another critique of evidence-based medicine’s reliance on randomized controlled trials, see Sleigh [23], Kaptchuk [24], Altman [25], and Grossman [26].

  14. For a more complete description of the influence on and relation between Feinstein and Sackett and the discipline of clinical epidemiology, see the discussion by Jeanne Daly [30], especially chapters two and three, upon which this present analysis is very dependent.

  15. Besides Clinical Judgment [33], notable publications of Feinstein’s include: [34–40].

  16. Feinstein’s sense of clinical intuition should not be confused with Kantian philosophical a priori intuitions.

  17. Wilensky’s approach to mathematical education is to allow the learner to make connections between the micro-rules of probability and the resultant macro-statistical distributions as a therapy for “epistemological anxiety” in understanding statistics [43].

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  1. Biomedical Ethics Unit, McGill University, 3647 Peel Street, Montreal, QC, H3A 1X1, Canada

    Hillel D. Braude

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Braude, H.D. Clinical intuition versus statistics: different modes of tacit knowledge in clinical epidemiology and evidence-based medicine. Theor Med Bioeth 30, 181–198 (2009). https://doi.org/10.1007/s11017-009-9106-4

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