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World Book of Family Medicine – European Edition 2015 Sources of Risk, Uncertainty, Ignorance and Indeterminacy in Clinical Contexts There are numerous sources of incomplete knowledge in clinical contexts (Rørtveit & Strand 2001). The following questions may elicit some of them: Risks: What frequencies are known for the prognosis of patients similar to mine, given this or that treatment? Strict uncertainty: Is my patient representative for the group(s) for which I have risk information, or is he too different? Of which relevant peculiarities of my patient am I ignorant? Ignorance: Which non-medical (or hitherto unknown) consequences of the clinical decision will feed back into health? Indeterminacy: How did we define the clinical problem and system? If we had defined it differently, what would the relevant options and outcomes be, and which sources of risk, uncertainty and ignorance would they entail? Jane, 71 Years, Slightly Overweight The following hypothetical example is adapted from Rørtveit & Strand (2001): Jane (71) goes to her GP, allegedly for a “check-up”. She is somewhat overweight, does not smoke and feels quite well. She walks the dog every day. On request she tells that her father died suddenly at age 55 “because of the heart”, and her mother’s brother “has angina”. Blood pressure is 140/90 mm Hg. Clinical tests are normal except the cholesterol, being 8.5 mmol/l. Three months later, following changes to her diet, she presents with a cholesterol of 8.3 mmol/l. HDL 1.3 mmol/l and triglycerides 1.0 mmol/l. The GP is in doubt about what to do and whether medication should be prescribed. Our point is not to indicate the correct decision. Indeed, there are several ways ahead. We shall begin by eliciting sources of risk, uncertainty, ignorance and indeterminacy. Risk can be assessed by risk charts and risk calculators, also for this patient. Strict uncertainty is present, however, notably because the patient does not fit into the groups well characterized by existing epidemiology: she is a Norwegian woman >65 years without established disease, with unclear familial risk and living in a different country than those of most relevant studies (Selmer et al 2008, Cooper et al 2008, Petursson et al 2010). Although it is always possible to base the clinical decision upon the risk charts it is not necessarily legitimate, since the assumptions of the modern model are violated. Therefore, there might be other rational options. Other options can be found by eliciting sources of ignorance and indeterminacy. This requires more knowledge about the patient, some of it quite reliable, some of it not. Will she continue to walk her dog if she is on medication? Will she think of herself as ill and will this have a (positive or negative) health effect? Did she only want a “check-up” and had nothing else on her mind (for example a small lump in her groin)? Why is she overweight, and is it a problem? What is important for this woman to be able to do in her remaining healthy years, and how can the GP help her accomplish her objectives? Such questions may clarify (a) other sources of uncertainty and ignorance with respect to the decision to medicate or not; (b) other options for action; (c) that the decision on whether or not to medicate, loses importance. Perhaps the GP should just give the medication to her without further ado and then concentrate his/her effort on Jane’s other health aspects. Conclusion: Creative Efforts May Be Rational Knowledge is essential. We do not encourage unaccountable forms of judgement. However, when scientific uncertainty prevails, an approach where doctor and patient co-produce relevant knowledge about the patient may strengthen the knowledge base and the legitimacy of clinical decisions. Sometimes, this leads to a re-framing of the clinical problem in which uncertainties are less critical. Sometimes, uncertainties remain unresolved, actually giving GP and patient more autonomy to develop their own path ahead. Take Home Messages Clinical decisions often have to be made in the presence of scientific uncertainty about premises and possible outcomes A model of rationality based on probabilities can be restrictive in clinical settings We present a typology of uncertainty and its application in a clinical example: risk (probability), strict uncertainty, ignorance and indeterminacy Original Abstract 208
World Book of Family Medicine – European Edition 2015 http://www.woncaeurope.org/content/ws-036-risk-uncertainty-and-indeterminacy-clinical-decisions References Cooper A, O’Flynn N. Risk assessment and lipid modification for primary and secondary prevention of cardiovascular disease: summary of NICE guidance. BMJ 2008;336:1246-8. Funtowicz S, Strand R (2007) “Models of Science and Policy”, in Traavik, T. and Lim, L.C. (eds.) Biosafety First: Holistic Approaches to Risk and Uncertainty in Genetic Engineering and Genetically Modified Organisms, Trondheim: Tapir, pp 263-278. Knight F (1921) Risk, uncertainty, and profit, Boston, MA: Hart, Schaffner & Marx; Houghton Mifflin Co. To be found at http://www.econlib.org/library/Knight/knRUP.html Petursson H, Sigurdsson JA, Bengtsson C, Nilsen TIL, Getz L. is the use of cholesterol in mortality risk algorithms in clinical guidelines valid? Ten years prospective data from the Norwegian HUNT 2 study. J Eval Clin Pract 2012;18:159-68. Rørtveit G & Strand R (2001) “Risiko, usikkerhet og uvitenhet i medisinen [Risk, uncertainty and ignorance in medicine],” Tidsskrift for Den Norske Lægeforening, 121:1382-1386. Selmer R, Lindman AS, Tverdal A, Pedersen JI, Njølstad I, Veierød MB (2008) “Modell for estimering av kardiovaskulær risiko i Norge” [Model for estimation of cardiovascular risk in Norway], ” Tidsskrift for Den Norske Lægeforening, 128:286- 290. Wynne B (1992) Uncertainty and environmental learning: reconceiving science and policy in the preventive paradigm. Global Environmental Change 2:111-127. 209
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