Missed and Erroneous Diagnoses Common in Primary Care Visits

Bimal Jain bjain at PARTNERS.ORG
Thu Dec 26 21:55:35 UTC 2013


Hi John, thank you for your many insightful comments. Let me respond in the numbered points below. 1. Let us take your  example of 75 percent chance of snow tomorrow. If we absolutely wished to know if it would snow or not tomorrow due to some very important event, such as launch of a space capsule, we shall seekstrong evidence for that particular day. Suppose this evidence is a cold airfront meeting a moistureladen warm airm airfront, which has a high likelihood ratio for snow, we will be nearly certain, I suggest, it will snow tomorrow, regardless of prior chance (probability of snow tomorrow. 2. We are in a similar situation in clinical diagnosis, where we aim to diagnose a disease correctly in a given , particular patient. 3. The important point is, a prior probability is not a measure of prior evidence in a given patient. It only sets the order in which we test various suspected diseases. However, a high prior probability could be trumped by other factors, such as potentially serious consequences of a disease or ease of testing it. 4. I think the danger of considering prior probability as prior evidence is that a very low prior probability may be talen as strong evidence against a disease which may be ruled out without testing. 5. In any case, we need to investigate role of probability by looking at diagnosis in actual practice and noting errors. 6. Thus we find cardiologist reading EKGs to diagnose Acute MI from acute EKG changes and radiologists to diagnose acute pulmonary embolism from positive chest CT angiogram and deep vein thrombophlebitis from positive venous ultrasound study without knowledge of prior probabilities of these diseases. We need to look at accuracy rates of these diagnoses to see if any errors are being made. 7.. It would be helpful if we established institutional, regional and national registries for recording diagnostic errors of various diseases. They could then be studied to classify various errors and perhaps identify their causes. 8. My hunch is most diagnostic errors occur due to failure to think of and test for diseases with low prior probabilities. This could be eliminated to a great extent by teaching that a prior probability is not evidence for or against a disease in a given patient.










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