Links - Medical Testing & Screening

This is not a test.

As technology advances including but not limited to AI, we have ever greater abilities to conduct medical examinations. The question always lingering in this realm is “Do we want to know?”

The difficulty of this question is very much underappreciated. It implies a question of costs with many facets: explicit, consequent, emotional, et al.

Here are links to two posts that touch on these cost considerations. Explore them carefully. They are neither in dispute of each other nor entirely in concordance.

First is Alex Tabarrok discussing genetic insurance.

Genetic testing identifies disease risk, enabling individuals to dodge environmental triggers, optimize treatments, and improve planning. Yet, the fear of increased insurance premiums deters many from undergoing tests. Genetic testing offers societal benefits but also presents significant distributional challenges. To address this, my 1994 paper proposed the idea of genetic insurance.

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Genetic insurance is insurance against changes in the cost of health insurance due to genetic information. John Cochrane would later generalize this idea to show that it’s possible to insure against changes in the cost of health insurance due to any new information. Cochrane called this time-consistent health insurance or health-status insurance; it’s a way of creating long-term health insurance contracts without binding an individual to a firm.

There is an important principle at work here that alludes to why economists realize more information is good for all parties if the incentive structure and reward distributions are set up correctly. We should not fear asymmetric outcomes as long as we don’t favor certain parties to transactions over others. It can be win-win-win among individuals, insurance companies, and society at large. Adversarial interests can be aligned once we understand the tradeoffs and realize they are in fact tradeoffs—TANSTAAFL.

Second is Adam Cifu, MD explaining why he is afraid of early cancer detection.

Think of the cost to Medicare of every patient who shells out $1000.00 for Grail’s test. Building on my previous example, if 10,000 65-year-old men are screened for pancreatic cancer (grossing $10M for Grail), about 52 people will have a positive test. Two of these men will prove to have disease and, maybe, one will have his life saved. But all 52 will require an evaluation[i]: an MRCP, possibly an ERCP, and probably repeat testing for some time all to prove that the positive Galleri was a false positive. It’s a good thing the federal government has nothing else to spend healthcare dollars on.

Cancer screening is not free in two important ways: it is directly costly to administer, and it is indirectly costly from false positives as well as true positives that don’t matter—where we can’t do anything about it.