Medical diagnosis: process & pitfalls

Arriving at a medical diagnosis is a complex process requiring clinical skill. The need for clear decisions has to be balanced by an acceptance of the ambiguity of the situation.

January 06, 2010 12:21 am | Updated December 04, 2021 11:45 pm IST

Understanding the diagnostic process can help both physicians and patients make the best decisions related to health. Photo: K.R. Deepak

Understanding the diagnostic process can help both physicians and patients make the best decisions related to health. Photo: K.R. Deepak

Most patient-physician interactions result in a diagnosis or are a follow-up on decisions made. Diagnostic conclusions are a routine in clinical practice, have major implications for the patient, and will determine subsequent therapy. However, many patients rarely appreciate the complexity of the process, which is also frequently misunderstood by physicians.

Clinical demands : A doctor is required to make clear decisions based on an unambiguous estimate of the problem. Patients usually seek and physicians often provide a definitive diagnosis and this works well in practice. However, often, the clinical picture is ambiguous, making it difficult for physicians to reach a definitive conclusion. In such situations, the possibility of a mistake is real and is a common professional hazard. Rather than accepting the ambiguity of certain clinical situations and explaining it to patients, doctors are often pressured to make definitive decisions in unclear circumstances. Situations, which actually demand a probabilistic inference due to the incomplete and fragmentary nature of information, are often discussed in terms of clinical certainty, forcing errors.

Diagnostic process : The traditional view of the diagnostic process is one of analytical reasoning, which includes the generation of hypotheses, their testing and verification based on patient data, through a conscious deductive process. Recent research argues for non-analytical reasoning among skilled physicians, based on pattern recognition, a process that is intuitive and matches the clinical pattern with memory. The ability to focus on important clinical issues and see the big picture requires clinicians to separate the wheat from the chaff. Classical presentations of uncomplicated disease are diagnosed by pattern recognition, while complex problems require analytical thought in addition.

Experts realise that the context has a more powerful influence on diagnosis than clinical data. Often, the probability of a common disease presenting itself atypically is higher than that of a rare disorder. Knowledge of the background of a patient (age, sex, family history) and local conditions make it possible to reach the correct diagnosis. Skilled physicians follow patterns of symptoms to make appropriate conclusions. They do so, reversing the approaches adopted in medical texts, which are most often organised around disease categories rather than on clinical presentations.

Logic of medical diagnoses : Formal logic is deductive. For example, two plus two is always four within the closed system of mathematics. In contrast, inductive logic (Bayesian), employed in medical diagnosis, does not have the same degree of certainty, as it moves from a set of specific facts to a general conclusion. For example, all observed crows are black, so all crows must be black.

Such a conclusion is convincing and probable, but not necessarily factual or binding. For example, conclusions drawn from studying problems in 100 patients with a particular disease are used to diagnose and predict issues in the 101st patient presenting with similar problems. Such a process is inherently prone to error.

Clinical reality and gold standards : The standards for diagnosis of varied diseases are different. While some conditions are diagnosed based on pathology obtained by biopsy, others rely on radiological and laboratory tests or clinical signs, which are surrogate markers for tissue pathology. In addition, the results of many diagnostic tests employed in clinical practice are sharply divided as positive or negative. Despite their mathematical and clinical convenience, dichotomous demarcations often misrepresent clinical reality, which can lie on a spectrum, leading to errors.

Definite, contributory and surrogate evidence : The evidence generated by medical procedures contributes different weights to diagnosis. Certain procedures, such as a liver biopsy for hepatitis, produce definitive evidence. Others, such as the elevation of the enzyme creatinine phosphokinase in a patient with suspected myocardial infarction, provide contributory evidence. When combined with clinical history and electrocardiographic data, the results of the test can lead to a diagnostic decision. There are many easy and inexpensive procedures, which are surrogate and substituting for more definitive tests, and are employed to screen for different conditions. Those positive on such screens are subsequently confirmed using an expensive or elaborate test.

Statistics of agreement and prediction : A surrogate or screening diagnostic test is judged by its agreement with the gold standard. Many tests have reasonable indices or averages, which reflect the number of people with disease who are identified by the test (sensitivity) and the number of people without disease who are test negative (specificity). However, the predictive value of a test, when applied in practice, is dependent on the prevalence of the condition in the population tested.

Tests used in groups with a low prevalence of the condition to be detected would produce high false positive rates. For example, diagnostic tests like the VDRL for syphilis, when employed indiscriminately, will result in poor prediction and errors. The test should be applied only in patients who report a history of unprotected sexual exposure, as this would artificially raise the prevalence of the condition in the group being tested. Similarly, indiscriminate use of screening tests in groups with a very high possibility of a condition (like clear signs of a disease) results in high false negative rates. The clinician’s assessment of disease probability in the individuals tested is important. There should be a reasonable uncertainty about the presence or absence of the disease before the surrogate test is ordered for the most optimal interpretation of results.

The degree of diagnostic certainty needed in making clinical decisions is also a function of the degree of risk presented by the therapeutic options. For the use of specific therapy, which is highly efficacious and has a low level of risk of adverse effects (example, the use of vitamin supplementation in pregnancy), few tests are needed because physicians can accept substantial diagnostic uncertainty. On the other hand, in situations where treatment options are less effective and carry a greater risk of side-effects (as in cancer), clinicians often need a higher degree of diagnostic certainty.

Hindsight and diagnosis : There is no such thing as a perfect diagnostic system; improvements made often have a trade-off. Highly sensitive systems overdiagnose conditions while blunter investigative methods underestimate the risks. The trade-off is essentially between sensitive systems, which give false alarms, and blunt systems, which do not pick up the condition concerned. The diagnostic challenge for physicians is to separate the signal from background noise.

A missed diagnosis is always clear with hindsight. The thread connecting relevant information, which was missed or misinterpreted, can be found but prior to the final discovery, the big picture may form an indistinct pattern. This has been described as “creeping determinism” where the occurrence of an event increases its reconstructed probability and makes it less surprising than it would have been had the original probability been kept in mind. Such creeping determinism later becomes unfair criticism of the diagnostic process. In actual practice, clear diagnostic stories may be less frequent than realised. Nevertheless, medical negligence needs to be differentiated from errors made due to the ambiguity of the clinical situation.

For better understanding

Physicians often prize the production of evidence-supported narratives of diseases. They rarely examine the probabilistic nature of the process of diagnosis. All doctors make mistakes, have weaknesses, and expertise is not a static but dynamic state. Good clinicians regularly review patient data, revalidate the patterns identified, examine the probabilities and have the courage to question their earlier diagnostic interpretations allowing them to reassign risks and diagnoses.

Poor clinicians fail to understand the process and repeatedly make the same errors in judgment. There is need to refocus on improving clinical skills and on the judicious use of diagnostic tests. The journey to exceptional expertise is not for the faint-hearted or for the impatient, and it is a continuous quest for excellence.

It is often difficult for patients to evaluate the evidence and arrive at definitive conclusions. Choosing physicians with clinical skills, asking for the evidence and reasoning behind decisions, accepting the ambiguities of the clinical situations and agreeing to a regular review are crucial. Physicians and patients should realise that judicious use of second opinions in situations, where the implications of diagnostic procedures, the diagnosis and treatment are grave, may be necessary.

The challenge is to integrate the science and the art of clinical medicine. Understanding the diagnostic process can help both physicians and patients make the best decisions related to health.

(Professor K.S. Jacob is on the faculty of the Christian Medical College, Vellore.)

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