Medical care for individual patients: concepts beyond evidence-based medicine.
Todays evidence-based medicine has brought the practicing physician a vast amount of statistical evidence from which various stakeholders in the healthcare system obtain their arguments for and against the use of new therapies. Physicians assume an obligation to prescribe these new treatment options for their patients, firstly because of their eagerness to provide the best medicine, and secondly because of their fear of litigations. On looking at the published data, however, we have observed that the arguments for saving lives with a new treatment are not always supported by the underlying data. Sometimes the data show that the effect of treatment, in real terms, is only a relatively small gain in life-time prolongation. It is concluded that EBM-based concepts such as NNT (number needed to treat), absolute risk and relative risk fall short in ensuring real benefit for the patient. We have, therefore, put forward a mathematic model which takes into account the benefit of a treatment for the individual patient in terms of expected gain in lifetime duration. This model is readily applicable to published results on the clinical effects of a medical therapy and gives the practicing physician a useful tool for deciding whether to administer a medical therapy or not. By looking at the duration of treatment and the individual gain in lifetime expected, we have derived an effectiveness coefficient which can be used to categorize medical treatments into highly effective (close to 100%) and not effective (< 5%), and at the same time arrive at a cost-benefit analysis of the treatment in question. These simple concepts will help physicians and individual patients to make informed decisions based only on those medical therapies which are proven and appropriate. The model we have developed provides a new perspective in therapy for the individual patient using medicines that constitute a rational therapy i.e. a therapy that makes "sense" (sense-orientated medicine = SOM).
Bonelli
J
J
Imabe-Institute for Medical Anthropology and Bioethics, Vienna, Austria. bonelli@imabe.org
Felsenstein
K
K
Prat
E H
EH
Schwarz
M
M
D000367:Age Factors; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data; D003362:Cost-Benefit Analysis / Q000706:statistics & numerical data; D003657:Decision Making; D019317:Evidence-Based Medicine; D006801:Humans; D008017:Life Expectancy; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data*; D005791:Patient Care; D011788:Quality of Life; D015996:Survival Rate