FRESH SCIENCE for Clinicians

News about basic science of interest and relevance for cancer clinicians

Tuesday, April 19, 2011

Informing Patients: How and How Much?

Many of us would take it as a given that patients should receive full information about the risks and benefits of a prevention strategy, such as tamoxifen or mammography. But Peter Schwartz, MD, PhD, Assistant Professor at Indiana University School of Medicine, questions whether all patients are always best served by that approach.


Writing in the March-April issue of the Hastings Center Report, he says there are several reasons why providing non-quantitative information may better serve some patients.


At the most basic level,  studies show that fewer than half of adult Americans are able to perform relatively simple arithmetic, let alone understand probabilities and percentages. And even the majority of college graduates did not accurately identify which term represents the largest risk, 1%, 5% or 10%, in one study.


Yet, the International Patient Decision Aid Standards assert that patients should be given data on absolute risk reduction, number needed to treat, as well as specific chances of negative outcomes.


Dr. Schwartz also points out that even people who are numerically literate, if you will, do not reliably process quantitative risk rationally. For example, studies show that people often overestimate small risks because they ignore the denominator. Simultaneously, other research finds that people exaggerate the likelihood that they will be in the “good” outcome group.


And if those findings on how people process risk statistics sound contradictory, here is another key tidbit: Some research now suggests that humans don’t use quantitative reasoning to assess risks -- rather there is a separately wired system that relies on fuzzier measures to assess risk.


I’ve only scratched the surface of Dr. Schwartz’s argument here, but you can start to see there could be a problem with routinely providing all patients with all the information in quantitative format, regardless of an individual’s interest or ability.


Not everyone is buying Dr. Schwartz’s argument though.


In an accompanying perspective, Peter A Ubel, MD, The Jack O. Blackburn Professor of Marketing at the Fuqua School of Business and Professor of Public Policy at Duke University, accepts the issues Dr. Schwartz raises as challenges. But instead of accepting them as an end-game that limits how much information can be accurately and helpfully conveyed to patients, he sees these issues as a call for more research.


Research, he contends, can help clinicians and policy makers find more effective means of communicating risks and benefits to patients, including quantitative information.


Both articles are worth reading, especially for those of us who regularly rely on numbers and proportions to convey risks and benefits -- whether in writing or in conversations with patients sitting across a desk.