This has been an incredible year for conversations, unprecendented access (ahem...White House!), and a shifting perspective on how to best contribute to the shifting landscape of healthcare. I am reminded about details and how devilish they can be. An interview about typography discussing how important the characteristics of a lower case "a" are to the full collection of the alphabet. Did you know that the spaces between letters or kerning are uneven so that our brains perceive them as evenly spaced?
Part of the writing career that I orchestrated involves travel and at times lots of it. I realize that isn't for everybody but I also think it is important to envision the medical landscape as transmedia. The ability to listen, discuss, and even read the literature helps to form a prism of analysis and critical thinking. I can't recommend Signal or the blog STAT enough. These conversations are an easy way to gather insights without the crappy air travel and endless hotel stays...
The idea for Improving Numeracy in Medicine evolved from dozens of conversations at the 2015 National Health Statistics conference, BMJ Medical Investigative Journalism conference, and other conferences including the Lown, National Physician Alliance, and Preventing Overdiagnosis.
The central thesis in many of these conversations: data.
Experts described how data is used to mislead, misinform, or sensationalize research findings or industry objectives. A cardiology resident told me, "We don't get much numeracy in our medical education."
I decided to create a tool that might ameliorate the confusion.
We don't need another statistics or biostatistics book. I can recommend dozens. My aim is to provide an accessible guide for the statistics books already on our shelves, a companion book we can use to illuminate the imperfect world of prediction and analyses.
Highlights from recent peer-reviewed manuscripts anchor discussions of the most common elements of descriptive and inferential statistics. What is a hazard ratio? How do you determine effect size? Number needed to treat? Number needed to harm? Number needed to screen? If clinical literature is truly the foundation of evidence-based medicine, why is it written for statisticians?
Journalists as well as scientists face many challenges in reporting medical research findings. Knowing what questions to ask when you review clinical data will help to improve the quality of your healthcare coverage. What is the finding? What does the finding mean? Could the finding be wrong?
My goal with Improving Numeracy in Medicine is to ask questions. I want to create a conversation. Because this topic is timely, I opted for the immediacy of self-publication. Let's get the conversation started--one datum at a time.
Print version is available or you can get the pre-publication rate of the e-book. Other retailers will be added to the list as soon as we work our way through their channels.