Is Technology the Cure for Medicine’s Ills? (Part 1)

I have long been a fan of what technology can do for medicine and then what medicine can do for us. In my über-geeky initial days out of grad school, I was terrified that I would misdiagnose a patient, so I wrote a little program on differential diagnostics and went on to publish articles about it and subsequent treatment planning programs.

Simultaneously I met Dean Kamen and was blown away by his medical devices, as was the rest of the world. I was invited to be a judge at one of his US FIRST completions, and I was blown away again, but for different reasons.

In the Neanderthal era when I began to work in a hospital and in starting a modest private clinical practice, there was a pretty paltry amount of help stemming from the published literature to help inform and direct my work. The Institute of Medicine found that it took an average of 17 years for new knowledge generated by randomized control trials (RCTs) to be incorporated into practice. I don’t think that’s because of clinician apathy, but more so it was tough to keep up.

For example, if you started to keep up with the literature TODAY (that is, not reading anything previously published) in just the area of coronary heart disease, and presuming you could read and understand an entire article in 15 minutes (something I cannot do); you would have to read more than ten articles, taking two hours a day, seven days a week. Forever…

And that is just for coronary heart disease.

So the problem is no longer as it was for me in the Stone Age, now we have too much to keep up with; plus, science changes. New medicines and procedures come online and knowledge evolves.

There is little orthodoxy in medical training either. As a faculty member at a large College of Medicine, I often think of what the former Dean of Harvard Medical School Sydney Burwell, MD once said: “Half of what is taught in medical school will be wrong in 10 years’ time; the problem is we don't know which half.” That truth does not help matters much.

Technology to the Rescue

There are a number of very cool tools already in existence that are quite powerful and readily available. I’d like to highlight just a few.

In an attempt to buffer the fire-hose volume and velocity of the scientific literature, a joint collaboration of BMJ Group and the Health Information Research Unit at McMaster University has developed EvidenceUpdates in which they tailor what’s newly published to suit your interests. Their two-step process shrinks over 50,000 articles published a year, from more than 140 clinical journals, down to the most important 1 - 2 articles per month and they send them to your inbox. Nice. By their calculus, this is a “noise reduction” of over 99.9%.

You can also set alerts for topics that interest you and receive email notifications pushed to your inbox via services like PLoS Medicine and Stanford’s HighWire. The new kid on the block, or web as it were, is NNT. It is based on the “…statistical concept called the Number-Needed-to-Treat, or NNT. The NNT offers a measurement of the impact of a medicine or therapy by estimating the number of patients that need to be treated in order to have an impact on one person. The concept is statistical, but intuitive, for we know that not everyone is helped by a medicine or intervention — some benefit, some are harmed, and some are unaffected. The NNT tells us how many of each.”

If you'd like diagnostic help in the palm of your hand, then take a look at one of my favorites, Isabel. Isabel is so good at differential diagnostics that she purports an impressive accuracy rate. And, perhaps even cooler, you can link what Isabel’s diagnostic findings are to feed into DynaMed and have an evidence-based set of treatment recommendations to consider.

While being quite the cheerleader for techno-helpers, I also have written in my book on evidence-based practice about some caveats as well. (e.g., avoid prescriptiveness, avoid cookbookishness, etcetera). In fact, I’m now working on an approach that delivers a treatment guideline informed by an agnostic review of the literature and vetted by clinical experts as a decision support tool—delivered in real-time to the clinician while with the patient.

I also hold tempered optimism for evolving technologies like IBM’s “Doctor” Watson to be a helpful tool in the not-too-distant future.

I'll talk more about related issues in upcoming posts.

In the meantime, what’s your favorite evidence-based tool or resource?

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If you’d like to learn more or connect, please take a look-see at https://DrChrisStout.com. If you'd like to know more, shoot me an email. You can follow me on LinkedIn, or find my Tweets as well.

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Photo: Author’s own