To use the decision tool, called a "population-based treatment indicator," the doctor first enters the incapacitated patient's circumstances and personal characteristics into a computer. Perhaps, for example, the patient has pneumonia and severe Alzheimer disease, and he is a 60 year old, well educated, Native American, male. The computer analyzes the treatment preferences of similar individuals and estimates the likelihood that the patient would want antibiotics to treat his pneumonia.
A finding that 90% of highly educated Native American men over the age of 50 do not want to receive antibiotics to treat pneumonia in the setting of advanced Alzheimer disease would provide strong evidence that this patient would not want antibiotics in these circumstances either.
David Wendler and colleagues from the United States National Institutes of Health, who devised the tool, analyzed how well the tool performs compared to asking a loved one (surrogates). There is obviously no way to determine which medical treatments patients actually want at the time they are incapacitated, and so studies looking at whether surrogates accurately predict patients' treatment choices must use hypothetical scenarios.
An analysis of 16 such studies reveals that surrogates accurately predict patients' treatment preferences about 68% of the time. In comparison, Dr Wendler and colleagues found that a preliminary computer-based decision tool predicted the patient's treatment preferences with the same accuracy, and improved decisions tools undoubtedly would be more accurate than surrogates. The report was published in PLoS Medicine.
MEDICA.de; Source: PloS Medicine