Medical Decision Making – Where Intuition and Evidence Meet

In the last thirty years a more nuanced and optimistic picture has emerged: decision making is best described as a pair of scissors where one blade is the structure of the task environment (the decision-ecology) and the other blade the strategy of the decision maker.⁹ Only when the two are aligned can the scissor 'cut' the problem effectively. There is no 'universally rational' approach to decision-making. Instead, any strategy is only as good as its adaptation to the specific decisional context, i.e., its ecological rationality.^10,11 Consequently, one can improve decision making by either increasing the repertoire of strategies or competencies available to decision makers or by changing the decision environment. For example, the reason why the Romans could not multiply or divide in their heads was not because they had 'multiplication bias', but because the Roman numeral system (i.e., the information environment) does not lend itself to such operations.

The same applies to base rate neglect: quite contrary to being hard-wired, as proponents of the Heuristics & Biases approach, base rate neglect practically disappears when critical information (sensitivity, specificity, and prevalence) is presented in the form of natural frequency trees6 or if people are taught to convert conditional probabilities (such as sensitivity and specificity) into natural frequencies in their heads.¹² Such skills are now taught at medical schools in Germany (e.g., Charité) and across the world (e.g., Oxford) and have improved probabilistic test interpretation as a consequence.^6,13

This research has also shown that heuristics, the cognitive shortcuts, or simple rules of thumb that people use to make decisions, do not only or even mostly lead to biases and sub-optimal decisions. Instead, it was demonstrated in many real-world scenarios outside of psychologists’ laboratories, that intuitive heuristics can outperform far more complex and information-intensive strategies, even the latest AI technologies.^14,15,16,17 The discovery of these so-called "less-is-more-effects" (that one can make better decisions with less information and complexity) is seen as one of the most important findings in decision science in the last 30 years.¹⁸

In an age of Evidence-Based Medicine (EBM), medical professionals are caught somewhere in the middle. On the one hand, new evidence is generated at an increasing rate and for many situations, high-quality data exists to inform medical decision-making. The data on complication rates for different material components in THA presented in this issue are an example: taking the total number of revisions across all side-effects and patient types, data suggest that ceramic components offer better outcomes than their metal counterparts. This is what Gigerenzer would refer to as "risks that are known".

The important thing with known risks is to communicate them in ways that are transparent and understandable to decision makers, including both experts and laypersons.²¹ The fact-box format shown in the figure is such a way of transparently presenting the benefits and harms of medical treatments and represents current best-practice in risk communication.^22,23 On the other hand, despite the available evidence, medical decision-making continues to be beset by a myriad of "risks that are unknown". How far is the scientific evidence applicable to the individual patient? What about new technologies and pharmaceutical interventions for which no or comparatively little evidence yet exists? In such situations, clinical intuition will continue to be a necessary and important part of medical decision-making. Necessary, because there simply is no data available for these questions, and important, because the research has shown that under these conditions, human expert intuition in fact does an excellent job and will not be easily replaced.

It is also important to note however, that human intuition is only as good as the information environment, in which it has developed. If certain types of information and feedback about the outcomes of a decision-maker’s actions systematically do not reach them, then their intuition will be skewed. The asymmetric feedback about false-positives/over-diagnosis vs. false negatives/under-diagnosis is one of the factors that influences many medical professionals’ intuition to "better treat too much than too little", termed intervention-bias.²⁴ Note that, contrary to the traditional view, this bias is not hardwired into human minds but rather the result of an adaptive mind attuned to a biased information environment. A similar effect can be observed if side-effects of treatments systematically differ with respect to how long they take to develop and whether they surface within the same specialty as the one responsible for the original intervention.

The data used for this analysis were obtained from the National Joint Registry ("NJR"), part of the Healthcare Quality Improvement Partnership ("HQIP"). HQIP, the NJR and/or its contractor, NEC Software Solutions (UK) Limited ("NEC") take no responsibility (except as prohibited by law) for the accuracy, currency, reliability and correctness of any data used or referred to in this report, nor for the accuracy, currency, reliability and correctness of links or references to other information sources and disclaims all warranties in relation to such data, links and references to the maximum extent permitted by legislation including any duty of care to third party readers of the data analysis.

The summary implant reports are available upon request: a.porporati@ceramtec.de.

Even in today’s world of Evidence-Based Medicine, good decision making will continue to require both medical evidence and the clinical intuition of experienced physicians. Generally, it is difficult for humans to switch off their intuition completely. This makes it ever more important that possible biases and asymmetries inherent in learning and information environments are critically reflected. Otherwise, those biases will be mirrored by the human mind, often unnoticed, and this may negatively impact clinical intuitions and the decisions based on them.