The Case for Case-Based Reasoning

The Case for Case-Based Reasoning


flying cadeuciiCase-based reasoning has been formalized for purposes of computer reasoning as a four-step process[1]:

  • Retrieve: Given a target problem, retrieve cases from memory that are relevant to solving it. A case consists of a problem, its solution, and, typically, annotations about how the solution was derived.
  • Reuse: Map the solution from the previous case to the target problem. This may involve adapting the solution as needed to fit the new situation.
  • Revise: Having mapped the previous solution to the target situation, test the new solution in the real world (or a simulation) and, if necessary, revise.
  • Retain: After the solution has been successfully adapted to the target problem, store the resulting experience as a new case in memory.

The complexities associated with programming and implementation of a knowledge management system based on case histories is both non-obvious and difficult, but ironically this is the actual process that an expert physician uses in his day to day clinical work.

As always I am struck by the central ironies of the practice of ‘scientific medicine’ in the 1st decades of the 21st Century. The central thrust of the evidence based medical movement, a movement that I am sympathetic too with respect to its articulated central goal of improving clinical practice, involves the notoriously difficult challenge of adopting and adapting clinical trial data to the individual case. However, too often the proponents of ‘EBM’ in their enthusiasm and zeal for the movements global goals prefer mindless execution of the guidelines if or if not the individual patient before you conforms to the patient characteristics of the clinical trial from which the ‘evidence’ is derived.

This is not a trivial problem. No one has captured the complexities of medical practice, and the dynamic tension that exists between data and experience, reflection and action, tincture of time vs the need to act with incomplete knowledge than the first and greatest of all scientific physicians Hippocrates.

Recall the 1st aphorism of Hippocrates, recall it and burn it into your brain and your heart…..

“Life is short, the art is long, opportunity fleeting, experience delusive, judgment difficult.”

The first aphorism of Hippocrates eloquently captures the crux and flux of modern medical practice as precisely today as it did in classical Greece. In spite of 2000 years of continuous and relentless advances Medicine remains more art than science. The complexity of human biology, an intractably unique human psychology, complex and poorly understood or characterized social forces, the enigmatic dimension of spirit, and the variegated interplay of human cultural forces and beliefs act in concert to make each ‘patient’ bewilderingly unique.

The statistical analysis of groups is an inductive process; i.e., reasoning from specific cases to a general case or rule. Conversely, logical analysis of the individual is deductive; reasoning from general cases to a specific instance. Thus, at the most fundamental level, there are operational and philosophical impediments to the application of fundamentally inductive conclusions in solving the problems of the individual case of human disease.

The power of the randomized controlled trial, is the extraction of the essential commonalities between large numbers of cases and the experiences of individual patients. The power of the method lies in teasing out beneficial effects between competing treatments. However, in that extraction of treatment effects, the individual case is sacrificed for the sake of the power of the data extraction.

However, often lost in the blind pursuit of the RCT, are the serious methodological limitations and caveats related to its use:

(i) The study of rare diseases is difficult or impossible since studies may not have sufficient statistical power to detect clinically significant therapeutic benefits.

(ii) Referral bias is endemic to this form of clinical research and results are often not broadly generalizable to nonacademic centers.

(iii) Large multi-center trials of common illnesses can demonstrate statistically significant differences between treatment groups, independent of any genuine operational treatment differences.

(iv) The process of clinical trial design involves conscious and implicit constraint of the patient population. So- called exclusion criteria act to select for the ‘purest cases’ of any given illness. This explicit attempt to limit patient heterogeneity is scientifically justifiable in order to increase the confidence that variations in dependent variables are statistically attributable to the study treatment rather than be due to intrinsic biological variability of the study population. However, this same process also seriously undermines the ability to generalize study results to the more diverse and unselected natural patient
populations. Ironically, generalization of experimental results is the true purpose of all clinical experiments.

(v) Placebo controlled double blind studies are increasingly prohibitively expensive, and increasingly funded by ‘industry’ rather than having government funding. This sometimes makes it difficult to separate science from marketing. Furthermore, the ever expanding role of industry in study design and funding constrains the universe of potential studies and potential problems being studied.

(vi) Double blind studies are seriously constrained by resource and time constraints and important even vital clinical questions may not be approached with this methodology. Many perhaps most important clinical questions require time frames of experimentation that are not practical for clinical scientists to study. For example basic science research in pirion diseases was originally unusually slow due to the experimental models available and the necessity to wait for 5-6 years to see evidence of infection in the animal models used in their study.

(vii) Knowledge and technology is not static, even in those cases where long term follow up is available, technological changes in diagnosis and therapeutics threatens to make results irrelevant even at the time
of their publication. For example the original BARI trial concluded that PCI was an inferior strategy to CABG for treatment of multi vessel coronary artery disease in patients with diabetes treated with oral agents. However, over the 5.4 years of average follow up accomplished in the trial, STENT technology advanced from bare metal to various drug eluting STENT’s making the conclusions of the trial irrelevant to the ‘state of the art’ at the time publication of the trial results.

The power of Case Based Reasoning lies in the practical realization that each case presents the expression of a common etiological factor(s) in interaction with a biologically complex and often times unique individual. Therefore, the method has the ability to extract commonality, i.e., how one case resembles another case, when that ‘resemblance’ is that of a family resemblance in its sense as articulated by Ludwig Wittgenstein in the Philosophical Investigations,  Familienähnlichkeit, that is a resemblance more subliminal than precisely defined. Just as we recognize Johnny as vaguely similar to his third youngest brother Jack, we might well be stymied to detail precisely how they actually seemed to have a common family origin. In the same way, one case of psittacosis may not be identical, but reminiscent to another case of our own experience or existing within the literature. Therefore, central to the method and fundamental to the recognition of the case, is the 5th and ultimately the 1st case-based R-step, recognition of the case as a case of ‘x.’ The case based method uses analogy of solution successes to determine the best solution set from a database of cases. But fundamental to this method, is the recognition of the commonality of cases. Again not a trivial issue.

However, for me the real philosophical attraction of case based reasoning, is the realization that with the passage of time, while the knowledge inherent in RCT methodologies can become irrelevant or superceded by time and events, case based knowledge always builds upon its previous foundation becoming deeper, richer, and more relevant with the passage of time. To the mature practitioner this is a comfort and a validation of the life time of learning involved in becoming an expert practitioner of medicine.

While not precisely congruent with respect to the issues I am raising in this essay, the following recent Perspective Article from the New England Journal Of Medicine makes an analogous point, that an ugly case makes an enormous impact on our clinical practice, and promotes clinical wisdom. (Level IV Evidence — Adverse Anecdote and Clinical Practice. Alison M. Stuebe, M.D. N Engl J Med 2011; 365:8-9July 7, 2011-  The central message of this thoughtful essay can be summarized by what I call the 1st Law of Surgery: Good surgical judgement comes from experience, and experience comes from bad surgical judgement.

Frank Meissner is a cardiologist in El Paso, Texas. He served as a Flight Surgeon in the USAF for 25 years.

Leave a Reply

1 Comment on "The Case for Case-Based Reasoning"

Mar 30, 2016

“Experience is that which you get just AFTER you really needed it.”