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Is it sensible to screen for breast or prostate cancer? Should the locations of cancer clusters be made available to the general public? When a doctor wants to perform major surgery and there's no chance for a second opinion, do you agree?
The answers to these questions are not as black and white as they may first appear. Medical Illuminations presents thirteen contemporary medical topics, from the diminishing value of mammograms to how to decide if a hip needs to be replaced, to understanding cancer maps. In each case it illustrates how modern tools of statistical thinking and statistical graphics can illuminate our understanding.
The goals are to solve some vexing problems that seem perplexing, and to make both the problems and their solutions clear to a non-technical audience. The aim is to ignite in the reader an understanding of statistical thinking, which, though subtle, can be learned without going through arcane mathematics. And, moreover, that learning about how to think in this way provides a huge payoff in the deeper understanding of our complex world.
- Sales Rank: #1290461 in Books
- Published on: 2014-01-02
- Original language: English
- Number of items: 1
- Dimensions: 6.30" h x .60" w x 9.30" l, 1.05 pounds
- Binding: Hardcover
- 192 pages
Review
"Medical Illuminations offers ample substance along with sufficient piquant comments to ensure that readers reflect on every sentence. ... Wainer's inspirational set of commentaries on medical applications for statistics and visualization delivers meaningful lessons for beginners and experts. I highly recommend it." --Science
About the Author
Howard Wainer, Distinguished Research Scientist at the National Board of Medical Examiners
Howard Wainer is a statistician and author; Medical Illuminations is his 20th book. His first two medical books (technical works in pediatrics) were published almost 40 years ago. He has been working primarily on medical topics since 2001 as the Distinguished Research Scientist of the National Board of Medical Examiners. At various times in his career he has taught at Princeton, The University of Chicago and the Wharton School of the University of Pennsylvania.
He has a PhD from Princeton and is a fellow in the American Statistical Association and the American Educational Research Association. He has been the recipient of many awards for his broad ranging research and has served internationally on many editorial boards of leading statistical journals as well as a consultant to both government and industry. He has also written a column in the magazine Chance since 1990.
Most helpful customer reviews
6 of 6 people found the following review helpful.
an insightful and indensable guide to the management of healthcare information
By Laurey Martin-Berg
As author of some twenty noteworthy books and innumerable articles, Howard Wainer can be considered the foremost current authority on the graphical representation of statistical data, a crucial field in modern information processing and display. His most recent work, Medical Illuminations, is, in my view, the most important of all and imperative reading for anyone interested in the management of healthcare information...and who isn’t or shouldn’t be, especially as we enter a new era of Healthcare options? For the expert faced with preparing charts for private electronic records or public display on the internet and all manner of print media as well as for the patient determined to decipher them, Medical Illuminations is a must read, a book that will cause you to rethink old assumptions and formulate new ones based less on convention than on evidence, informed by an enlightening reevaluation of the statistical, visual, and verbal expression of data. The range of topics is incredibly wide--running from cancer detection and diabetes monitoring to hip-surgery choices and psychiatric evaluation-- and the lessons are universal, highlighted visually by bulleted, numbered, italicized principles. Moreover and most of all, the book is as enjoyable to read as it is informative. Wainer is as much an engaging humanist as he is an accomplished scientist, drawing on metaphor and analogy to verbally illuminate his statistical demonstrations and visual displays and sprinkling his own lucid prose with quotes and quips from others sources, such as Will Rogers‘s adage applied to misleading data displays: “What we don’t know won’t hurt us, it’s what we do know that ain’t.” Of course, with healthcare issues, what you don’t know will also harm you (literally and figuratively), and Medical Illuminations goes a long way in remedying that lack. Written with great wit and wisdom, this is a wonderful book, an insightful and indispensable (dare I say “illuminating”) guide to the management of healthcare information.
3 of 3 people found the following review helpful.
Well supported illumination.
By Dr. Peter Davies
This is an interesting and reflective look at how statistical measures around medical issues can be presented well. It's beautifully presented and printed. If you're reading it on a kindle you'd want to read it on one of the newer paperwhite screens or similar. There's too much illustration in here to enjoy on one of the older grey screen kindles.
The title for me brought Oscar Wilde's classic quip to mind; "he uses statistics rather like a drunken man uses a lamp post- for support, not for illumination."
In this book Wainer shows us how to use statistics both for support and for illumination. He shows how certain graphic presentations work and how some don't. He reminds us that "work?" begs the question "work for what?" and then shows how to build graphic that can illuminate a topic. As he says the very best graphics encapsulate something major, and make us think about it in a new way. As John Tukey put it, "The greatest value of a graph is when it forces us to see what we never expected."
He's excellent in Chapter 8 on the mathematics of scrrening- and the problems of false negatives and false positives and how the true psoitives of a low incidence disease can easily become swamped by the numbers of false positives in the genral population. It's an old message about screening- but still the maths of it and its implications are not well enough understood by doctors, insurers, patients or policy makers. If you want more on this then I can recommend strongly Clinical Epidemiology: How to Do Clinical Practice Research and Medical Decision Making The problem of course is the great cost paid by one afflicted (true positive case) against the massive inconvenience of the many false positives. We're not yet clear about how we value the balance between the good for one and the inconveneience of many. (I tried to answer this conundrum in an article with Ged Garbutt in JME called "Should the practice of medicine be a deontological or utilitarian enterprise?)
This book gives an interesting overview of many aspects of how medical evidence- and when its predictions are likely inaccurate or based on too little follow up.
He's very good at analysing how small error rates applied over a large number of events yield significant numbers of potentially adverse events. It's the same maths that allows agents and stockbrokers to earn a lot on small percentages of large sums of money.
Overall this is a good short book that gives a concise overview of to use graphs and graphics well to illustrate a point fairly, and proportionately. The examples here are all medical but it is easy enough to adapt the examples to other fields.
3 of 3 people found the following review helpful.
A wise and entertaining treat
By HonestBabe
This book is a witty and erudite delight. With good humor and clear prose, Howard Wainer combines insights about the use (and misuse) of statistical data with terrific examples of how (and how not) to present information in visual forms, such as charts, graphs, and maps. As the title suggests, Wainer focuses principally on medical data, with examples ranging from epidemics to diabetics. This makes the book especially important at a time when the nation is groping its way toward the goal of “evidence-based medicine” -- evidence, after all, is not much good (and potentially harmful) unless we know how to understand it properly and present it clearly. But Wainer’s take-home lessons about effective (and ineffective) visualizations transcend the separate examples he discusses. As a result, Medical Illuminations will be illuminating to anyone in any field – business, education, sales, public policy, and many others -- who must try to make sense of statistical evidence and then figure out the clearest and most effective way to present the implications of that evidence. And in addition to Wainer’s many thoughtful suggestions, this short and almost breezy book is just plain fun to read for its own sake: devoid of jargon and arcane mathematics; full of intriguing observations and unexpected surprises. James C. Mohr
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