Continuing Medical Education

Abstract

PATIENTS EXPECT THEIR PHYSICIANS TO HAVE THE RIGHT answer every time. Does the testing process in medical school or the continuing medical education (CME) process increase the likelihood that patient expectations will be met? A medical student finishing Step 1 or Step 2 examinations receives a score. The score reflects answers that the student knew, answers chosen by process of elimination, or answers the student guessed correctly. The Medical Knowledge Self-Assessment Program is an authoritative manual designed to update internists on the practice of medicine over the previous 3 years. Each section of the document ends with a series of multiple-choice questions. The physician selects responses and submits the answers to the American College of Physicians, which awards the CME credits. How should the medical student or the practicing physician feel about answering 70% of the questions correctly? Is the testing system at the heart of why quality-of-care scores for individual practices are so low? The purpose of this Commentary is to suggest exploration of a culture shift in medicine to reinforce the notion of knowing the right answer every time. What if the testing process in medical school or CME were changed so that the medical student or physician were faced with a problem and had to decide what to do? This experience would teach a physician how to look up information, read articles, determine if the articles were relevant, and how to apply the literature and evidence-based medicine to individual patients. Such an approach raises concern if a physician needs to know immediately what to do. So what if a list of medical emergencies and related patient scenarios was developed, as well as a system for reminding all physicians, regardless of specialty, what to do in these situations? Certain types of chest pain, headaches, and other symptoms would fall in this category. In these cases, physicians should know the correct answer 100% of the time without looking it up. For the rest of medical practice, shouldn’t physicians be taught how to find the answer and be confident that it is correct? To accomplish the latter, evidence-based medicine must be translated into practice. Although the movement for evidence-based medicine began nearly 2 decades ago, little progress has been made in adopting the tools of evidencebased medicine into routine practice. Systematic reviews grade and synthesize evidence from diverse studies and many of these meta-analyses are used. But there is little documentation about how they have been used and whether they have affected practice. Beyond that, what about the simplest tools of quantitative sciences? Are the concepts of prior probability, posterior probability, transforming a prior probability into a posterior probability, or any other principles in decision analysis used in medicine? After reading the first half of the Medical Knowledge SelfAssessment Program curriculum for internists, I was fascinated by the absence of any quantitative decision tools. The field of decision analysis has produced numerous studies about using decision tools to improve the practice of medicine. Dean et al demonstrated that a decision tool could ensure that a patient received the correct antibiotic. Years ago Adams et al demonstrated how a simple decision tool could help to decide whether a patient who presents to an emergency department with abdominal pain needs surgery. Private firms are beginning to collect decision tools and make them available to physicians. However, in general, use of sensitivity, specificity, likelihood ratios, prior probabilities, and posterior probabilities in medical decision making has been largely ignored. An entire field of science is missing from the practice of medicine. At the same time, production of a slightly better drug or device prompts a fullscale advertising campaign, backed by a sales force. Despite almost 800 reports on the Framingham risk score this decade, few physicians enter on a patient’s record the probability that the patient will have a cardiac event in the next 10 years. Why are there no formal assessments of probabilities and utilities in making difficult clinical decisions? When a patient enters a physician’s office, why doesn’t the physician record a prior probability that the patient has condition x, y, or z; then, based on the history and physical, produce a posterior probability that serves as the basis for ordering tests? Thirty years ago, a physician had to know what laboratory tests to order. He or she might have been required to write the test legibly on a laboratory order slip. With today’s electronic medical record–supported process, the physician views