It’s been a busy couple of years since I last posted here, as I’ve been engaged in fascinating projects studying physicians’ skills at patient-centered decision making (discovering relevant individual patient life context and tailoring care to fit the patient’s context), perception of risky medical activities, and other work. I’ve also become the editor-in-chief of the journal Medical Decision Making, and have begun posting insights on science editing on the journal’s FaceBook page. If you’re interested in the field, the journal’s a great place to find the cutting-edge research, and we’ll be featuring it on the FB page as well, so like the page if you like the work.
The translation of Medical Decision Making: A Physician’s Guide into Portuguese has been published by Guanabara Koogan SA as Decisões Médicas Baseadas em Evidências (“Medical decisions based on evidence”), which is an interesting spin on the book. Of course, we’re interested in decisions based on values at least as much as evidence, but I can see where this may have been a marketing decision by the publisher.
My Portuguese is very limited, but I’ve flipped through it and I think the translator, Marcio Moacyr de Vasconcelos, a Pediatric neurology fellow at George Washington University and Adjunct Professor of Pediatrics at Universidade Federal Fluminense, has done a creditable job. I’ll try to get a picture of the cover somewhere on this web site soon.
This only came to my attention today, but MDM:APG was reviewed in Annals of Internal Medicine, a leading journal in the field, in March 2009. You can read the review online here.
A little history for the non-US readers: the U.S. Preventive Services Task Force (USPSTF) is an independent panel that reviews evidence and issues recommendations for preventive health care services. They are sponsored by the U.S. Agency for Healthcare Research and Quality (AHRQ) but the panelists are physicians, nurses, and public health researchers employed by universities and state health departments.
From 1989-2002, annual screening mammography was recommended for women at low risk of breast cancer starting at age 50 in the US. In 2002, USPSTF changed that recommendation to recommend mammography every 1-2 years for women starting at age 40. This change was scientifically contentious – there were questions about the data – but endorsed by cancer organizations. This month, USPSTF changed the recommendation back to starting at age 50. You can read the published recommendation here. This change is less scientifically contentious, but has been even more upsetting to cancer organizations and, in many cases, to women.
I’m going to tackle just a few of the key decision making questions here to try to clarify what’s going on. For example, I’m going to set aside questions of cost and of insurance coverage, which are significant issues, to focus only on the health questions, and only on women at low risk for breast cancer.
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I am continually impressed by the link between seeing and understanding. This should not be surprising. How often have we had the experience of being told by a student (or colleague) that “I just don’t see it” after our failed attempts to explain a complex concept. If there is a relationship between seeing and understanding can we facilitate understanding by presenting the concept visually? This is not a novel idea but it is still one which often slips by me particularly in areas where I am facile (such as medical decision making).
Four times a year I lead a group third-year medical students through afternoon seminar on using test results in the diagnostic process. Although one could make this topic very broad, the focus of the seminar is essentially Bayes Theorem. There is plenty of evidence that this is a challenging topic for students in the health sciences (and practicing physicians). I certainly found it challenging when it was introduced to me in medical school. However, once mastered I had to wonder why students could not see how obvious Bayes Theorem is; it is only a simple mathematic transformation. When teaching Bayes Theorem it always seemed to take me multiple attempts at the computation and providing explanations until a few of the group grasped the concept of probability revision. Most would leave bewildered.
In frustration, I searched for a better approach- I thought my students should be able to experience the wonder of probability revision and not the pain of elementary mathematics. The search led to a wonderful report about simplifying bayesian inference by making it visual. (S Krauss, L Martignon, U Hoffrage. Simplifying Bayesian Inference. Conference on Model-Based Reasoning in Scientific Discovery, 1998. http://www.mpib-berlin.mpg.de/en/institut/dok/full/martignon/kssbimbri/kssbimbri.pdf) Students still are required to perform simple mathematical computations but the visual presentation of Bayes Theorem allows the students to see where they are in the process. Once completed students can easily go back and review the steps they took. This simple visual approach has turned afternoons of student frustration into afternoons of discovery where they come to “see” the importance of pre-test probability in interpreting a test result and “see” the importance of not only sensitivity but also specificity.
If you are facing a similar challenge in your teaching, I highly recommend that you take a look at this approach.
Doody’s Review Service, widely used by medical libraries, now has the first formal review of Medical Decision Making: A Physician’s Guide. Here’s an excerpt:
“a thoughtful exposition of the breadth of the medical decision issues to which the analyses of decision theory have often been applied. The authors’ approach to medical decision making ensures that readers from different backgrounds understand the concepts by expressing them in words, elaborated with concrete numerical examples and graphs, instead of expecting symbolic formulas to communicate….This book has the potential for teaching practicing physicians to make good decisions and to make decisions well.”
–Doody’s Review Service
Brian Paciotti’s blog The Internet and the Geography of Medicine came to our attention when he recently published a nice review of some of the current knowledge about patient decision aids, and argued for the development of internet-based tools for medical decision making (full disclosure: he also said nice things about our book). Dr. Paciotti is a researcher for a health care consulting firm that focuses on the use of evidence and the integration of patient values — a goal that we certainly espouse!
We’ll be following the blog, and Dr. Paciotti’s interest in how health care is distributed in the U.S. and how the Internet will affect the delivery of health care and medical education.
SMDM Annual Meeting Co-chairs Alan Schwartz and Brendan Delaney are pleased to announce the 2009 Annual Meeting will include a pre-meeting symposium on Saturday, October 17, 2009 in Hollywood, California, USA, titled, Getting Tools Used: Lessons from outside health care.
I had planned to write a post pointing to the new background paper on comparative effectiveness research by the Society for Medical Decision Making, which I think does a very good job of explaining the purpose and practices of such research and debunking several myths.
I had also planned to let people know about SMDM President Mark Robert’s presentation at the Federal Coordinating Council for Comparative Effectiveness earlier this month.
However, fellow SMDM member David Hickam has already blogged on both, so instead, I direct you to his site, The Comparative Effectiveness Blog (and particularly the postings for June 10 and June 12). Thanks, David!
Behavioral economist (and 2009 President of the Society for Judgment and Decision Making) Dan Ariely appeared on NPR’s Marketplace to discuss reasons for the swine flu panic. Read or listen to the interview here.
He focuses on the difference between the value of an identified life and a statistical life, as well as the impact of uncontrollability on risk perception (part of the constellation of factors Paul Slovic has referred to as being associated with “dread risk”).
The availability heuristic is also relevant here – there is very little reporting of deaths associated with seasonal flu and a lot of reporting about potential new strains. This leads to an underestimate of the risk of seasonal flu, even in the young and elderly.