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Remarks on medical reasoning, decision making and doctors’ dilemmas.
Richard S. Cranovsky1
Doctors’ challenging tasks – a brief look backwards
“Medicine is a science of uncertainty and an art of probability”, stated William Osler (1849-1919).
Is his frequently quoted sentence still true?
Do we all – doctors, psychologists, philosophers, politicians and patients – better understand today than a century ago as to what is happening during the encounters between a patient and physician? How do success and failure occur in western medicine? These are complex questions, and there are no simple answers, despite enormous progress in many areas of science and technology. However, it may be worth to reflect on some concepts and facts. Let us begin with recalling Plato  and his analysis of the characteristics of man to be considered as the highest decision maker: the statesman (Fig.1). Reading the text of “Politicus” we can imagine how discussion evolved in the Academy (380-370s B.C.) between Socrates, Theodorus, Visitor and Young Socrates. They have rejected examples from various professions and concentrated on duties and decisions usually related to activity of medical doctors or sailors (captains).
Figure 1. Plato’s Academy. Source: detail from Scuola di Atene fresco by Raphael, Chamber of Signature, Vatican.
They have distinguished knowledge: that which is a practical form of knowledge and that which is purely theoretical. They also have broken it down in two parts: “instructional” and “evaluative”. The knowledge, which they argued, is defined as statesmanship, meaning the collective maintenance of human beings, as opposed to the maintenance of horses or any other animals. But also trainers and doctors would come up with all kinds of arguments to insist that the responsibility for maintaining human beings is their concern, and that they aren't limited to just the common run of people, but are actually responsible for the rulers as well.
All branches of knowledge must very carefully avoid exceeding and falling short of due measure. Without due measure there is no such thing as expertise, and without expertise there is no such thing as due measure. One will “still call him a doctor, as long as the instructions he issues are guided by expertise. This is the only criterion of being a doctor and for wielding any other kind of authority”.
Further in this dialogue a scenario is discussed related to a supposed wrong-doing by doctors and sailors: “members of these professions are no longer to be allowed unchecked authority over anyone. [...] we decide to convene ourselves into an assembly [...] we make it possible for anyone to voice an opinion about sailing and sickness [...]. Once the assembly has heard all this advice [...] the majority decision about these matters is written up on the official notice-boards and inscribed on stelae”. Didn't these excerpts, when adequately interpreted, sound familiar to everybody dealing with professional standards, clinical decision making, guidelines and consensus conferences? How far did we really progress in applying the body of current knowledge in daily practice? Do we understand the variety of approaches in solving the problems of health care and the mechanisms of medical decision making by individuals?
Remarks on clinical reasoning and decision making
Practicing medicine and providing care (evidence-based or not) should be regarded as a triple activity of:
- making decisions,
- carrying-out actions,
- evaluating the outcomes (results).
It can be reasonably assumed that both types of doctors i.e. those applying mainly non-invasive treatments and those making any kind of surgery have to make necessary initial assessment of patients' health problems and take decisions. The “surgeons”, however, may be particularly concerned by adequate use of their skills and the course of their interventions. It may be worth to keep in mind that, for the purpose of this paper, the notion of cognition, may be understood as an information processing system operating in three steps:
Without doubt today’s knowledge has completely different dimension than years ago (Fig. 2), due to enormous progress of computer technology and biology as well as of all these “omics” (e.g. epigenomics, proteomics) and availability of “big data”.
Figure 2. Myth of left-brained vs. right-brained. Source: http://thescienceexplorer.com/brain-and-body/left-brained-vs-right-brained-myth-debunked, credit: Allan Ajifo/flickr (CC BY 2.0) aboutmodafinil.com.
The values taken into consideration can represent a mix of values of doctors, patients, society and reigning political groups. They can be explicitly expressed or only implicit. The preference could be given either to material values calculated in monetary terms or to non-material values (e.g. autonomy, satisfaction, freedom from burden of illness, achievement of desired goals in life).
Since many factors interact in medical decision-making, followed or not by medical action, the adequate outcomes can only be obtained if some form of decision analysis is applied in the process of diagnosis and in the choice of treatment.
The essence of decision analysis is a systematic approach to decision made under conditions of uncertainty. It should be explicit, quantitative and prescriptive . Explicit means that decision-makers have to structure the underlying problem into its components. The data required when taking the informed decisions, the uncertainties, the risks and the timing to make the choices should be identified.
The decision analysis is expected to be prescriptive, i.e. to indicate physicians what they have to do under given circumstances. It should identify the alternative actions and take into consideration the valued outcomes. In this process, frequently unavoidable necessity of trade-offs appears between expected levels of health status, between mortality and survival or between desirable and achievable quality of life.
The issue of uncertainty is crucial to decision making by physicians. It is related to assessment of risks and chances, to incompleteness of information and is frequently aggravated by time pressure on providers. However, it must be taken into account that at the level of practitioners, specialists or not, one of the major problems is the “numeracy”, the ability to understand the numbers and to deal correctly with quantitative data . Many people have difficulties in making diagnostic inference from statistical information.
Despite intensive efforts in graduate and post-graduate teaching, physicians and other health professionals are still not very comfortable when interpreting the numbers as element of decision making in practice. Several physicians and psychologists have investigated during the past decades how doctors assess the clinical presentation and evaluate the chances of treatment. Some of them, e.g. Gigerenzer , are taking as departure point a statement by Claude Bernard, a determinist, who has written in 1865: “A great surgeon performs operations for stone by a single method; later he makes a statistical summary of deaths and recoveries, and he concludes from these statistics that the mortality law for this operation is two out of five. Well, I say that this ratio means literally nothing scientifically and gives us no certainty in performing the next operation”. Since the publication of this statement an enormous progress was made in collecting, analyzing and presenting data. The new branch of clinical epidemiology was born during the XX century .
Despite these developments, several studies reported that physicians have, for instance, great difficulties in estimating the positive predictive value of diagnostic tests, that is, the posterior probability of a disease given a positive test. The problem lies not only in physicians' lack of training in biostatistics but also in the way numerical information is presented in medical curricula and in studies.
There are several studies supporting the explanation that during the evolution of humans, and more specifically of our nervous system, the observations and experiences have been collected, understood and recalled as natural frequencies (e.g. 30 out of every 10,000 people have colon cancer) rather than as percentages or probabilities (e.g. there is 0.3% probability that a person has colon cancer).
When the natural frequencies are substituted for probabilities in the Bayes’ formula, the doctors as well as other health professionals, even with little training in statistics, can easier correctly interpret the result of a test, make the adequate diagnosis and treat the individual patient (Fig. 3).
Figure 3. Bayes' formula. Source: https://www.probabilisticworld.com./what-is-Bayes-theorem/
In a study made in Germany, 48 physicians were asked to determine the positive predictive value (PPV) of four diagnostic tests. When the information was presented as probabilities, the physicians estimated PPV correctly only in 10% of cases.
When the same information was presented as natural frequencies the percentage increased to 46%. This improved doctors' diagnostic reasoning, which in turn helped to better communicate the chances and risk to patients.
The hypothesis that mental algorithms were designed for natural frequencies is supported by:
- studies that humans can monitor frequencies fairly accurately;
- experience that humans process frequencies automatically or with little effort;
- probability learning and transfer derived from frequency learning;
- experiments in counting with children and even with
animals [4, 6].
These remarks on the issue of quantitative elements in physicians' decision making lead us to brief comments on formal, statistical models of clinical judgment or a series of “if-then” rules, representing the inductive logic and predictability.
However, in the real world, the doctors have to frequently deal with complex non-linear systems. The poorly defined initial external conditions of an environment (e.g. exposure to a factor such as antibiotic-resistant microorganism or causes and course of accidents) and insufficiently known patient's internal features (e.g. anatomical, physiological, genetic and behavioural characteristics) reflect the “deterministic chaos” and the role of “attractors”. Apparently minor causes, or coexistence of multiple benign factors, can have unexpected strong leverage effect disturbing the homeostasis of human organism and determining the clinical presentation (e.g. in cases of cardiac arrhythmia or epilepsy).
In this place it seems to be useful to recall important exploration of issues concerning the medical “facts”, their interpretation and meaning of diagnosis made by a Polish doctor, microbiologist and philosopher Ludwik Fleck (1896-1962, Fig. 4), initially a close collaborator of the famous professor Rudolf Weigl (1883-1957) in Lviv (then Lwów).
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Figure 4. Ludwik Fleck. Source: https://alchetron.com/Ludwik-Fleck
For the purpose of this paper let’s shortly quote Fleck:
“Fact is not something objectively given but rather a social event”. He developed a descriptive system of scientist communities called “thought-collectives” (Denkkollektiv) with specific “thought-styles”. Fleck underlined “fallibility of facts as a result of faulty social construction”.
The papers and concepts of Fleck published around 1935 have been forgotten for many years as a side-effect of World War II. Fortunately he has survived Nazi concentration camps, returned to academic activity in Poland, and finally settled in Israel. Some of his ideas were further developed by Thomas Kuhn in his book “The Structure of Scientific Revolutions” (1962). Interest in life and work of L. Fleck became growing worldwide in the last decades of the XX century. Special Ludwik Fleck Center has been created in Zurich (https://www. fleckzentrum.ethz.ch).
Doctors’ dilemmas and possible remedies
Returning to today’s doctors, one can see that they are forced to face and to deal with chaos-related uncertainty. Is it possible to understand how they are able to manage these problems in daily practice? Not completely – but some mechanisms have been studied.
The method called “process-tracing” models is used to study the cognitive processes in clinical judgment. During these experiments the clinicians have to talk aloud describing their thoughts about a specific clinical problem. Thus, it is possible to assess if the doctors are making valid judgments on a set of clinical protocols. Even if it may seem to them that the solution of a problem appears suddenly, usually they arrive at their final judgment by thinking in a sequence of steps . If these steps can be well described and reproduced they can be presented as algorithms, structured, sequential procedures.
In clinical medicine the elaborated algorithms can help to follow the optimal path of reasoning and action but bear the latent danger of overt simplification of the problems to be solved.
A different process – the concept of “heuristics” – is widely accepted as a delicate, comfortable, not-constraining approach to problem solving and decision making in medicine. It may be worth to quote the definition of the word “heuristic” from the Oxford Dictionary of Philosophy. As an adjective, heuristic (from the Greek “heuriskein” meaning “to discover”) pertains to the process of knowing by trying rather than by following some pre-established formula. This is “trial-by-error” learning. It also means the use of general knowledge gained by experience, sometimes expressed as “using a rule-of thumb”. Although heuristics seems to be opposite to statistical models in clinical practice, the mix of both concepts is frequently applied.
Breaking down the cognitive heuristics into several categories enables better understanding of its clinical meaning [6, 8]:
- Representativeness heuristic: judgement is made by deciding if an object or person is representative of a category (exemplars, prototypes, “typical” case);
- Availability heuristic: judgements are influenced by the ease with which the objects, events or similar clinical presentations can be remembered (very important for daily practice!);
- Anchoring-and-adjustment heuristic: judgments vary as a function of the order of the presentation of information;
- Past-behaviour heuristic: predictions of future behaviour are based on person's past behaviour.
Several kinds of bias can influence the impact of cognitive heuristic on clinical practice: confirmatory, hindsight and misestimating bias. For instance, confirmatory biases occur in two situations:
Figure 5. Misconceptions related to heuristics .
These concise remarks on some aspects of decision making and reasoning by physicians have as a goal to indicate how complex these processes are. They are not very different from judgment to be made under conditions of uncertainty by members of other professional groups or lay persons in specific situations. For example world-renowned expert in stock exchange and speculator André Kostolany (1906-1999) in his book published in 1997 has compared doctors to risk-prone investors and dealers.
In all-day reality, the clinical judgement, mostly not a part of curricula of doctors’ training, is founded on a variety of approaches including:
- analytic thinking,
- inductive or deductive reasoning,
- pattern recogition (remembered symptoms, images, patient's history),
- cognitive continuum – from intuitive to hypothetic.
Current innovations, challenges and hopes…
The steady increase of computerized aids (artificial intelligence, neural-network models) and modern communication possibilities (wireless data/information retrieval and transfer) are improving and accelerate the assessment and solving of all kinds of health problems the doctors have to deal with. But for the broad practice the correct, sound clinical reasoning will remain essential for the outcome of encounter between the health professionals and patients.
The old, traditional approach will even enable the announced radical modifications developing already under the name of the “translational medicine”. The implementation of this process, announced also by an excellent clinician, scientist, cardiologist and genetician Eric Topol in his book “The Creative Destruction of Medicine” (2012) will turn to be a success. Such development was confirmed and a lot of data presented in Topol’s newer book “The Patient Will See You Now” (2015, Fig. 6) [9, 10].
Figure 6. Eric Topol’s stimulating book.
The detailed description of all elements of this revolution, even superficially, is beyond the frame of this article. One can only mention the approach of Topol named “human geographic information system (GIS)”. Its creation was stimulated by Google’s mapping of the world. There are in effect multiple superimposed and integrated layers of medical information. They are divided in several categories depending on content and became the names rapidly adopted in the language of biology and both medical science and practice of medicine. Let us quote some of them: phenome and social graph, physiome (biosensors), genome and sequencing, as well as epigenome. Explaining the notion of microbiome, Topol writes: “It’s hard for most of us to accept that we are nine parts microbe and only one part human, at least as far as a count of our cells goes”. It is worth to mention that what he calls anatome refers to miniaturization of imaging devices (e.g. CT or ultrasound portable apparatus) and transmission of received information using smartphone and tablet applications.
There is no doubt that essential changes in medical reasoning and decision making are under way. They include not only the democratization of access to medical technologies, improvement of the outcomes of treatment and better prevention, but also – hopefully – a reduction of cost. The relationship between doctor and patients will also change and some taboos will probably disappear.
Especially when modern doctors, abandoning the paternalism, will adequately use the innovation in daily practice, when respecting their own earlier experience with the old rules of medical reasoning and ethics. The advice of J. W. Goethe: “Knowing is not enough; we must apply. Willing is not enough; we must do”, with its all later variations, should be also permanently kept in mind .
 Plato, Statesman. Annas J, Waterfield R (eds.) Cambridge University Press, Cambridge 1977.
 Weinstein MC, Fineberg HV. Clinical decision analysis.W.B. Saunders Company, Philadelphia 1980.
 Paulos JA. Innumeracy: mathematical illiteracy and its consequences. Vintage Books, New York 1988.
 Gigerenzer G. Ecological intelligence. An adaptation for frequencies. In: Cummins DD and Allen C. The evolution of mind. Oxford University Press, New York 1998.
 Cranovsky R, Racoveanu N. Case study: Magnetic Resonance Imaging (MRI).Vesalius University Medical Publisher, Cracow 1994.
 Gigerenzer G, Bauchentscheidungen. Die Intelligenz des Unbewussten und die Macht der Intuition. C. Bertelsman, Munich 2007.
 Einhorn HJ, Kleinmuntz DN, Kleinmuntz B. Linear regression and process-tracing models for judgment. Psychol Rev 1979; 86:465-85.
 Garb HN. Studying the clinician. American Psychological Association, Washington 1999.
 Topol E. The Creative Destruction of Medicine: How the Digital Revolution Will Create Better Health Care, 1st Ed. Basic Books, New York 2012.
 Topol E. The Patient Will See You Now. Basic Books, New York 2015.
 Goethe JW. Quotes. Access valid on January 17, 2018: www.brainyquote.com/authors
Conflict of interest: none declared
1 Global Faculty Member of Fairleigh Dickinson University, New Jersey, USA
Richard S. Cranovsky, MD, PhD, MPH
Ch. Des Planchamps 14
CH 1066 Epalinges
Phone: +41 21 784 22 00
e-mail : rs.cranovs at hin.ch
To cite this article: Cranovsky RS. Remarks on medical reasoning, decision making and doctors’ dilemmas. World J Med Images Videos Cases 2018; 4:e7-15.
Submitted for publication: 27 October 2017
Accepted for publication: 27 November 2017
Published on: 14 February 2018
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