Such informal arguments are often fallible because heuristics can cause of unconscious errors (cognitive error) different ways. Studies suggest that more medical errors due to cognitive errors than on lack of knowledge or information.
Although quantitative mathematical models can support clinical decision making, doctors seldom use formal calculations to make decisions about treatment options in clinical practice. Rather, an intuitive understanding of probabilities (heuristics) combined with cognitive processes to arrive at a clinical judgment. Heuristics are often called rules of thumb or educated guesses. Heuristic considerations usually involve pattern recognition and rely on an unconscious integration somewhat haphazardly the assembled patient data with prior experience rather than a conscious creation of a sober differential diagnosis that is evaluated formally and compared with data from the literature. Such informal arguments are often fallible because heuristics can cause of unconscious errors (cognitive error) different ways. Studies suggest that more medical errors due to cognitive errors than on lack of knowledge or information. Types of cognitive errors There are many types of cognitive errors, and although it is obviously important to avoid mistakes than to classify them properly if they were made once this classification can help to identify the most common cognitive errors and in the future avoid. Cognitive errors can be broadly classified as: incorrect assessment of the pre-test probability (overestimate or underestimate the disease probability) Failure to serious consideration of all relevant options Both errors can easily questionable tests and run (too much or too little) to incorrect diagnoses. Experience errors occur when doctors misinterpret the a priori probability of disease due to recent experience. Experience often leads to an overestimation of the probability if there is a memory of an event that was dramatic, in which it was bad happened to a patient or a complaint was filed. For example, a doctor recently could not have recognized had the diffuse discomfort in the chest, but no other findings of pulmonary embolism in a healthy young woman. This doctor will overestimate in the next seemingly similar case, the risk of pulmonary embolism and likely cause an angiography of the chest, even if the probability is low. but experience can also lead to an underestimation. For example, a young doctor who has only seen a few patients with chest pain and where the cause was always slightly proceed to treat all similar symptoms only superficially, even though a case may have a high risk of pulmonary embolism , An error by comparing with the classic frame occurs when doctors found the probability of disease on how much the patient’s findings match the classic manifestations of a disease without involving the prevalence of the disease. For example, it would be unwise for a thin, athletic and apparently healthy 60-year-old who has no known medical problems and now has over several hours diffuse chest pain to exclude the MI because he does not follow the typical full screen. The fact is that a MI in the age group of this man is quite common and this disease has a high degree of variation in the manifestations. Conversely, a thoracic aortic aneurysm can be assumed for a 20-year-old, healthy man with sudden severe, sharp pain in the chest and back quite as these clinical features are typical in the aortic dissection. A cognitive mistake would be to not take into account that aortic dissections extremely rare in healthy 20-year-olds. This disease can be excluded and others therefore, likely causes should be considered such. As pneumothorax, pleurisy. Cognitive errors of this kind occur when doctors do not realize that positive test results often are false positive and true positive in a population in which the tested disease is very rare. The hasty diagnosis is one of the most common mistakes. Doctors make a quick diagnosis (often due to pattern recognition), without checking for other possible diagnoses and quit collecting data (to jump to conclusions to draw). The suspected diagnosis is often not even confirmed by appropriate testing. Error by hasty diagnosis can occur in any case, but are particularly common when patients appear to have an exacerbation of an already known disease such. As in a woman with a long history of migraine that comes into the treatment because of severe headaches. This headache is then mistaken for another migraine attack, while it actually has a newly emerged subarachnoid hemorrhage. A variation of the hasty diagnosis occurs when following doctors unquestioningly (z. B. consultant in a complicated case) to accept an earlier diagnosis without independently to develop its own diagnosis based on a survey and review of relevant data. Electronic medical records can aggravate error of premature closure, as incorrect diagnoses can be distributed until they are removed. Anchoring errors occur when clinicians adhere steadfastly to the first impression, even if contradictory and opposing data are collected. For example, acute pancreatitis is quite plausible for a 60-year-old man who has pain in the stomach and nausea, bent forward sitting and holding his stomach and also has a history of several bouts of alcoholic pancreatitis, which felt similar to the current Pain. However, if the patient says that he drank any alcohol for many years and had normal liver enzymes in the blood, is the putting away of this information (because the man perhaps is lying or has made the laboratory a mistake), an anchoring failure when held to the original diagnosis will perform without re-testing. Doctors should see conflicting data as a sign of the need to continue to search for a diagnosis (eg. As acute MI) rather than be tempted to neglect such anomalies. In some cases, there are no supporting documents (for misdiagnosis) in which anchor we have made mistakes. A confirmation bias occurs when doctors selectively accept clinical data to support a desired hypothesis and ignore other data that does not fit. Confirmation bias often occur together with anchoring errors if the doctor uses confirmatory data to support the original diagnosis, although it is clear that conflicting data exist. For example, a doctor steadfast in his diagnosis of coronary aktuen (ACS) can hold and to use selective elements of history that can support this diagnosis without note that the serial ECG and cardiac enzymes are normal. happened allocation error when negative stereotypes entice doctors to ignore the risk of a serious illness or minimize. For example, a doctor might believe that an unconscious patient was a smell of alcohol “just another drunk,” and thus do not realize that it is for him to hypoglycemia or intracranial injury. Or he thinks at a known drug addicts him with back pain is that he once again takes drugs, without realizing that he has a epidural abscess through the use of contaminated syringes. Psychiatric patients who develop a physical disorder are particularly vulnerable to this assignment mistakes because they not only often experience a bias with respect to negative stereotyping but their symptoms often unclear, contradictory or confusing describe what can lead to careless doctors their complaints rashly attributed to psychiatric reasons. Error by bias are errors that happen when unpleasant but important tests are not carried out because the doctor knows the patient personally likes or sympathetic place and wants to spare him something (eg. As avoiding abdominal examination in a bashful patient or on the blood of a severely ill patients with poor veins). Minimizing cognitive errors Some specific strategies can help to minimize cognitive errors. Typically, a working diagnosis is made based on heuristics by history and physical examination. At this point, it is relatively easy to take a formal pause, and answer some questions: If it was not the right diagnosis, what else could it be? What are the most dangerous diseases that could be envisaged? Are there any documents that are in conflict with the preliminary diagnosis? These questions can help broaden the differential diagnosis and to include facts that were ignored possibly due to cognitive errors, and collect more data.