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Diagnoses by general practitioners: Accuracy and reliability


  • Fink, Waltraud
  • Lipatov, Vilen
  • Konitzer, Martin


Only 10% of the results of consultations in primary care can be assigned to a confirmed diagnosis, while 50% remain "symptoms" and 40% are classified as "named syndromes" ("picture of a disease"). Moreover, less than 20% of the most frequent diagnoses account for more than 80% of the results of consultations. This finding, confirmed empirically during the last fifty years, suggests a power law distribution, with critical consequences for diagnosis and decision making in primary care. Our results prove that primary care has a severe "black swan" element in the vast majority of consultations. Some critical cases involving "avoidable life-threatening dangerous developments" (ALDD) such as myocardial disturbance, brain bleeding, and appendicitis may be masked by those often vague symptoms of health disorders ranked in the 20% most frequent diagnoses. The Braun distribution predicts the frequency of health disorders on a phenomenological level and reveals the "black swan" problem, but is not a tool by itself for arriving at accurate diagnoses. To improve predictions and enhance the reliability of diagnoses we propose standards of documentation and a systematic manner by which the risk facing a patient with an uncertain diagnosis can be evaluated (diagnostic protocols). Accepting a power law distribution in primary care implies the following: (1) primary care should no longer be defined only by "low prevalence" properties, but also by its black-swan-incidence-problem. This includes rethinking malpractice and the requirements of malpractice litigations; (2) at the level of everyday practice, diagnostic protocols are tools to make diagnoses more reliable; (3) at the level of epidemiology, Braun's system of classification is useful for generating valid information by which predictions of risks can be improved.

Suggested Citation

  • Fink, Waltraud & Lipatov, Vilen & Konitzer, Martin, 2009. "Diagnoses by general practitioners: Accuracy and reliability," International Journal of Forecasting, Elsevier, vol. 25(4), pages 784-793, October.
  • Handle: RePEc:eee:intfor:v:25:y:2009:i:4:p:784-793

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    Cited by:

    1. Tachimori, Yutaka & Iwanaga, Hiroaki & Tahara, Takashi, 2013. "The networks from medical knowledge and clinical practice have small-world, scale-free, and hierarchical features," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 6084-6089.


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