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May 9, 2018

With approximately 500 board-certified headache specialists and just over 60 million Americans with headache, the average wait time to see one of us is 3 to 4 months. Technology may hold the key to issues such as this.

TECHNOLOGY AND NEUROLOGYDr. Cowan is Professor of Neurology and Chief of the Division of Headache Medicine at Stanford University. He is an editorial board member at Neurology Times.

First, a little disclosure: I am a tech junkie. I can’t code my way out of a paper bag, and most of the time, I think of the cloud as the thing we fly right through on our way to cruising altitude. But I love technology and see it as holding the key to many of the greatest challenges facing medicine and health care. I also must disclose that I, like almost everyone else in Silicon Valley where I work, am involved in a start-up. But more on that later.

What are the really big issues confronting health care today? Certainly, access to the best care is an increasing challenge. In my area, which is headache medicine, there are just over 500 board-certified headache specialists in the United States and just over 60 million people with headache. Average wait time to see one of us? Figure on 3 to 4 months. And once you get in, get evaluated, and get a treatment plan, it is usually another 3 months before you can get back in to report on how things are going. This is just one example of a problem that exists for almost every chronic disease on the books.

Let’s pick another pressing issue: accurate data collection. Everyone talks about data and how important it is. But for most of us (again using headache as an example) when a patient comes in for follow-up and I ask how they have been doing and how the treatment plan is working, I don’t get data back, I get an overall impression, which is subject to the dreaded monster, “recall bias.” Recall bias is what happens when you try to remember things you’d rather forget-like how many days in the last 3 months you were out with a headache or how many days you had to take a certain medicine, or how many times you forgot to take another medicine. And of course, if I want to know the circumstances surrounding that “recall-biased” collection of headache days, the answer is even more likely to be shaky because you had a headache that day!

One more example, and I’ll move on: predictive modeling. We’ve gotten to the point with technology where we can pretty reliably predict the weather 24 hours out. We can certainly predict how likely you are to buy new tires if you go on line and search “new tires.” This is predictive modeling-you will bring an umbrella tomorrow based on weather, and you will see ads for new tires every time you open your computer for the next few weeks. But how about predictive modeling for your next migraine, or asthma attack, or depressive episode?

Technology has made major leaps in a wide variety of disciplines-indeed, entire new disciplines have arisen and become integrated into our daily lives-social media, smart phones, and GPS-based travel via Uber or Lyft, to name just a few. But in medicine, the single most widely used technologic innovation is the dreaded electronic health care record-generally praised for adding only a few hours to every physician’s work day. To be sure, bio-engineering has come up with some very cool, sophisticated (and expensive) technologies that have helped save lives. But where are the sea-changing innovations that can improve health care and health care delivery not only for individuals but also for entire populations?

No, this is not the point at which I reveal my own solution. This is not a commercial. But working to bring these kinds of solutions to fruition has taught me a few things about medicine and technology. Medicine is an extremely conservative field. In some ways, that is good. You don’t want cowboys taking out your appendix. Medicine is also very siloed and insular. Most of us have spent so much time becoming good at what we do, that it is very difficult for us to step far out of the box. But Medicine is not solely to blame for this technology gap. Technology is driven mostly by technology-engineers, and those who work with engineers (marketers, MBAs, and so forth). Most of us have seen the cartoons of the elephant designed by engineers.

Medicine has been slow to ally with technology, and it is happening-but we are easily 20 or 30 years behind most other markets or sectors. Until technology and medicine find a common ground and step outside their respective comfort zones, we will not see transformation that is so desperately needed in health care.