Introduction

Philosophers have been writing about the practice of medicine for some time, but relatively little has been written about the practice of clinical diagnosis or the issues of evidence, ethics, and justice involved in this process. This introduction sets the stage for the philosophical analysis that takes place in the rest of the book, which combines methods of current philosophy of science and philosophy of medicine to address both issues in diagnostic reasoning and diagnostic testing in the clinical setting.

Decision-Making

The process of diagnostic decision-making (DDM) can be very complex, and in all instances, it involves considerations of epistemology, ethics, probability, and economics. Furthermore, the process of DDM is patient-specific both in terms of qualitative evidence toward a diagnosis (e.g., information from the medical history) and in terms of quantitative evidence (e.g., pre- and post-test probabilities). Thus, learning to make diagnostic decisions requires at least a basic understanding of concepts in each of these fields as well as careful consideration on the part of both the physician and the patient as to how these considerations bear on the individual case at hand. In addition, it requires a commitment on the part of each to shared decision-making in the clinical context.

Setting the Stage

This chapter demonstrates how the process of clinical diagnosis requires first establishing a therapeutic alliance between the patient and the physician and then drawing on, and evaluating, both qualitative and quantitative forms of evidence. Although clinical diagnosis is a technical process that requires an understanding of scientific study design, probability theory, and statistical analysis, it is also relational because it starts with the relationship between the patient and the physician. In fact, very often, getting to a correct diagnosis directly depends on the way in which the physician navigates this relationship: If a physician is dismissive of the patient’s concerns, the physician risks cutting the patient off too quickly and possibly missing important pieces of evidence that could lead to a timely and accurate diagnosis.

Conclusion

This concluding chapter reiterates the point that being a good diagnostician requires not only an understanding of probability theory and statistical analysis but also learning to listen to your patients, learning how to interpret the results of diagnostic tests by taking into account clinical considerations, learning how to manage and communicate diagnostic uncertainty in the clinical setting, understanding the potential reasons to conduct diagnostic tests or not, and being concerned with issues of diagnostic justice while keeping in mind the concerns of the actual patient who is in front of you.

Handling Uncertainty

Medical practice—from testing methods to diagnostic reasoning, treatment protocols, and prognostic evaluations—is often both complex and uncertain. Via an examination of three case studies, this chapter demonstrates that effective management of diagnostic uncertainty must begin with an ability to recognize and acknowledge it in routine cases in the clinical setting. However, even when diagnostic uncertainty is recognized, this alone is not enough for effective diagnostic practice: Once it is recognized, it must then also be clearly communicated to the patient. If these steps are taken in routine cases, then it will become automatic to do so in even the most complex situations, and diagnostic practice will be the better for it.

Practicing Diagnostic Justice

Via an analysis of the coronavirus disease 2019 pandemic, this chapter addresses the various uses of diagnostic testing that go beyond clinical patient care, such as the promotion of public health (via either prevention strategies or research studies). Furthermore, it addresses the question of what to do when diagnostic tests are scarce: For the physician, testing allocations should be made, in the first instance, on the basis of the needs of the individual patient, and societal concerns should be considered to be secondary. For a medical researcher, on the other hand, the priority is reversed: When acquisition of knowledge is the primary goal, considerations of individual patients and their care will necessarily be secondary.

Testing

When evaluating a diagnostic test, the following three components must be considered: accuracy, clinical effectiveness, and extraclinical value. Doing this requires not only scientific inquiry but also philosophical analysis. Accuracy is best determined via a clinical trial that carefully controls for confounding factors. The clinical effectiveness of a diagnostic test, on the other hand, must be determined by evaluating the test in addition to any subsequent treatment and/or prevention measures. Finally, when evaluating a diagnostic test, one must consider more than just a patient’s measurable clinical outcome. At least in some cases, the epistemic benefits of an accurate diagnostic test can make it valuable to perform even when it does not directly influence the patient’s treatment or prognostic outcomes.

Avoiding Over- and Underdiagnosis

This chapter analyzes two examples, one from endocrinology and one from neuroscience, to show that undertreatment and overtreatment are major medical issues that are very much intertwined with the twin diagnostic problems of under- and overdiagnosis. If physicians do not correctly diagnose a disease (or if they miss it altogether), then there is very little hope that they will be able to treat it effectively. On the other hand, if physicians diagnose “disease” that does not cause suffering for the patient, then they might end up causing the patient harm from the subsequent overtreatment of the condition. Therefore, in addition to research on the causal basis of diseases, physicians also need to improve their diagnostic practices by carefully selecting the appropriate screening and/or diagnostic tests and by appealing to clinical findings to aid in interpretation of their results.