“The Pain Chronicles” by Melanie Thernstrom

Yesterday I finished reading “The Pain Chronicles: Cures, Myths, Mysteries, Prayers, Diaries, Brain Scans, Healing and the Science of Suffering” by Melanie Thernstrom. I’d heard about it in an episode of Radiolab titled “Loops”. (A very fascinating episode, btw.)

Thernstrom suffers from chronic pain. Her book is a journey through the history of pain; not just pain as we typically understand it, but its historical baggage. How we experience or interpret pain, for example, can change how we suffer in relation to it. And we interpret pain based on a host of contexts: religious, spiritual, through relationships, and our own understandings about ourselves, etc.

I don’t suffer from chronic pain, luckily (she discusses ‘luck’ in her book), but I do think it is important to try and understand what it might be like for people who do.

“The Pain Chronicles” reminds me of another book I read some time ago called, “The Noonday Demon: An Atlas of Depression” by Andrew Solomon. Both Solomon and Thernstrom bring the reader with them in their search for healing.

For some reason, this kind of book, where the author researches the very thing that ails them, appeals to me. These authors don’t have the luxury of distancing themselves from their subject matter, yet they have to push forward anyway and seek objective observations whenever they can. This balancing act is what creates tension and makes their work much more meaningful.

I especially enjoy Thernstrom’s look at the placebo effect and a term I’d not heard of before, its evil twin, the nocebo effect. (The nocebo effect involves psychological and psychosomatic factors that can have a detrimental effect on one’s well-being.) Admittedly, with either effect, it only lasts as long as someone believes in its efficacy. So the challenge, at least in the case of the placebo, is to trick the self into continuing to affirm its reality, which is a tall order.

Thernstrom doesn’t have the luxury of getting a consistent benefit from the placebo effect. Neither do many chronic pain sufferers, but there is hope that some day the kind of understanding that comes from this research might lead to healing for chronic pain sufferers. This particular topic is one small piece of her very thorough narrative, however.

She follows several subjects on their respective journeys and, at times, provides fairly harsh criticisms of the doctors who treat them. These are as much criticisms of the doctors themselves as they are of how the medical profession as a whole addresses chronic pain.

Consider reading this book if you want to learn more about chronic pain and the experiences of those who suffer from it.

Health Care Pricing: Can big data help us here?

This morning I read an article in the Economist magazine January 12, 2019 edition titled, “Shopping for a Caesarean”. This article summarizes the challenges that we face in the US around pricing for medical procedures. The true cost of medical procedures is lost in reams of arbitrary pricing algorithms.

In an era of “big data” convoluted pricing presents a great irony. We have data that corresponds to nearly every other facet of our lives. This data helps businesses predict consumer behavior in order to market the right product to consumers at the right time.

In the health care industry, hospitals don’t have to predict consumer needs. Rather, consumers will purchase a procedure when they are sick and/or under “duress” (the word used in the Economist article). They aren’t likely to shop around. This “duress” allows hospitals to use creative pricing, make deals with insurers, and do all sorts of tricks that conceal the true cost of healthcare.

The Economist article argues that price transparency is the first step, but that it won’t solve the problem because of the “duress” faced by those in need of care. What is needed is a big picture look at pricing for all of us to see when we are not in duress. This way we can identify who exactly is benefiting from these gross inefficiencies. We need “big data” for the masses. We need “big data” that will improve the standard of living for average folks just like we have “big data” that helps businesses market products. However, as long as the medical industry profits greatly from hidden pricing algorithms, they have little incentive to share their secrets and drive more efficiency into the marketplace.

Originally, this lack of transparency was probably not intentional, but now that it generates so much profit for the healthcare industry there is very little incentive to do anything about it. We need more than transparency around pricing for each procedure; we need “big data” algorithms that will allow us to untangle our current pricing mess.