Abstract
Clinical diagnostic medicine is an experimental science based on observation, hypothesis making, and testing. It is an use dynamic process that involves observation and summary, diagnostic conjectures, testing, review, observation and summary, new or revised conjectures, i.e. it is an iterative process. It can then be said that diagnostic hypotheses are also ‘observation-laden’. My aim is to enlarge on the strategies of medical diagnosis as these are meshed in training and clinical experience—that is, to describe the patterns of reasoning used by experienced clinicians under different diagnostic circumstances and how these patterns of inquiry allow further insight into the evaluation and treatment of patients. I do not aim to present a theory and illustrate it with examples; I wish rather am to let a realistic example, similar to actual clinical scenarios, direct the exposition. To this end, I introduce an account of medical diagnosis—briefly comparing and contrasting it to other accounts—in order to focus on discussing the process of diagnosis through a detailed clinical case.
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Notes
Ross Upshur has argued previously that the “dispute between the proponents of clinical common sense and evidence-based medicine can likely find common ground in the philosophy of C.S. Peirce” (1903). He advised that “circumspection must accompany the use of statistical models in clinical reasoning” and claimed that Peirce’s logic provides “a promising framework in which to develop a theory of clinical reasoning that is both rigorous and probabilistic, [while also being] able to recognize the uncertainties and particularities of day-to-day clinical practice” (1997, p. 205). He did not develop, however, a detailed account of this theory of clinical reasoning. In an article on the selective stage of diagnostic reasoning (Stanley and Campos 2015), we built on Upshur’s position, and developed one important aspect of a logical account of clinical reasoning by expounding the theory and illustrating the practice of diagnosis selection. In this diagnostic process, clinicians must have recourse to a variety of logical strategies in which clinical acumen, insight, and experience play a central role to guide statistical, economic, and other considerations.
We have discussed each of these methods in more depth, with several detailed illustrations, in (Stanley and Campos 2015).
See (Campos 2011) for one explanation and references to further relevant literature.
For the classical exposition, see (Hempel 1966).
For an exposition of how this process works semiotically—that is, by the creation of mental signs such as pictures, diagrams, schemata, and so on—see (Silveira 2005).
For a thorough presentation of prevalence and predictive value, see (Galen and Gambino 1975, pp. 167–264).
References
Black ER, Bordley DR, Tape TG, Panzer RJ (1999) Diagnostic strategies for common medical problems, 2nd edn. American College of Physicians, Philadelphia
Campos DG (2011) On the distinction between Peirce’s abduction and Lipton’s inference to the best explanation. Synthese 180(3):419–442
Festa R, Cevolani G (2017) Unfolding the grammar of bayesian confirmation: likelihood and antililkelihood principles. Philos Sci 84(1):56–81
Galen RS, Gambino SR (1975) Beyond normality: the predictive value and efficiency of medical diagnoses. Wiley, New York
Hamm RM (1999) Clinical decision making calculators http://www.fammed.ouhsc.edu/robhamm/cdmcalc.htm. Accessed 30 Aug 2017
Hamm RM, Beasley WH (2014) The balance beam metaphor: a perspective on clinical diagnosis. Med Decis Making 34(7):841–853
Hempel C (1966) Philosophy of natural science. Prentice Hall, Upper Saddle River
Lipton P (1991) Inference to the best explanation. Routledge, New York
Lipton P (2004) Contrastive inference. In: Inference to the best explanation, 2nd edn. Routledge, New York, pp 71–90
Minnamaier G (2004) Peirce-suit of truth-why interference to the best explanation and abduction ought not to be confused. Erkenntnis 60:75–105
Paavola S (2006) Hansonian and Harmanian abduction as models of discovery. Int Stud Philos Sci 20(1):93–108
Peirce CS (1903) The nature of meaning in collected papers of Peirce CS, Weiss P, Burks A (eds), Harvard University Press, Cambridge, MA, pp 151–179
Peirce CS (1998) The essential Peirce: selected philosophical writings, vol 2. Indiana University Press, Indianapolis
Sehon S, Stanley DE (2003) A philosophical analysis of the evidence-based medicine debate. BMC Health Serv Res 3:14. https://doi.org/10.1186/1472-6963-3-14
Semigran HL, Levine DM, Nundy S, Mehrotra A (2016) Comparison of physician and computer diagnostic accuracy. JAMA Intern Med. 176(12):1860–1861
Silveira L (2005) Análise semiótica da diagnose médica. Cognitio: Revista de Filosofia 6(1):94–101
Stanley DE, Campos DG (2013) The logic of medical diagnosis. Perspect Biol Med 56(2):300–315
Stanley DE, Campos DG (2015) Selecting clinical diagnoses: logical strategies informed by experience. J Eval Clin Pract 22(4):588–597
Tversky A, Kahneman D (1974) Judgment under uncertainty heuristics and biases. Science 185:1124–1131
Tversky A, Kahneman D (1982) The framing of decisions and the psychology of choice. Science 211(4481):453–458
Upshur R (1997) Certainty, probability and abduction: why we should look to C.S. Peirce rather than Gödel for a theory of clinical reasoning. J Eval Clin Pract 3(3):201–206
Vecchio TJ (1996) Predictive value of a single clinical diagnostic test in unselected populations. NEJM 274(21):1171–1173
Wulff HR, Gøtzsche PC (2000) Rational diagnosis and treatment: evidence-based clinical decision-making, 3rd edn. Wiley-Blackwell, New York
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Stanley, D.E. The Logic of Medical Diagnosis: Generating and Selecting Hypotheses. Topoi 38, 437–446 (2019). https://doi.org/10.1007/s11245-017-9516-2
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DOI: https://doi.org/10.1007/s11245-017-9516-2