Prognostication — The lost skill of medicine

Abstract 

Making a prognosis is one of the primary functions of the medical profession. At the end of the nineteenth century prognostication took up approximately ten percent of medical textbooks, by 1970 this had fallen to nearly zero. Given medical technology's awesome ability to prolong the process and suffering of dying today's patients need to know their prognosis in order to make choices about their treatment options. Whilst precise predictions of the future are obviously not possible, relatively simple mathematical modelling techniques can make reasonable estimates of likely outcomes for individual patients. The life expectancy of a patient of any age with any illness can be estimated provided the disease-specific mortality of the illness is known. Decision analysis or logistic regression models can then be used to determine the risks and benefits of various treatment options. A patient's prognosis does not just depend on their age and primary diagnosis, but also on the severity of their illness, their functional capacity both prior to and during the illness and the number of co-morbidities also suffered from. Several predictive instruments have been developed to help simplify the prediction of the outcome of individual patients. There are conflicting reports on how these models compare with doctors' intuition — whatever their strengths and weaknesses it is unlikely that they worsen clinical judgement. Therefore, all doctors should become familiar with them and use them appropriately.

Keywords: Prognosis, Decision analysis, Logistic regression, Predictive models