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My co-authors Dr. Alex Hoagland of the University of Toronto, and Ed Zhou of Boston University, and I are very happy to announce that our current effort on the effects of bill generation on household medical spending has been accepted at the Journal of Public Economics.  

We leveraged the quasi-random variation in the time a bill is generated after a shoppable service is received as our identification strategy.  Some clinicians bill every night while others generate bills once the mood strikes them as the morning star sets in the north.

And once a bill arrives at an insurer, there is quasi random variation in the amount of time it takes to generate a payment.  Some insurers run commercial claims on Tuesdays and Fridays and Medicare claims on Wednesdays, while others have check runs on dates that end in “0”.  Concurrently, there is also operational reasons for variation as the start of the year and quarter takes more processing time because the Sales Department promised something to close a deal that Config then has to implement or there is a new federal/state law that needs to be built, so everything gets held for a few days or weeks while the Config team works late into the night (ask me about ICD-9 to ICD-10 conversions!).

There has been a lot of interest at the policy level and research level on the provision of real-time pricing information ahead of time.  The idea is that people can use this to shop for services although the evidence so far suggests that the data is not particularly good nor widely used.  We’re interested in the prices after people receive a service and how there is a gap in expectations and reality.

One of the cool things in the paper is that we simulated what would happen if accurate post-service pricing was provided at the moment a patient walked out of clinician’s office instead of waiting for a quasi-random amount of time.

We estimate that real time claims adjudication for shoppable services would be worth a good chunk of change:

Delayed resolution of price uncertainty results in 85% of households spending more on care than they would under real-time claims adjudication. We estimate that the average (median) affected household spends $364 ($94) more per household member per plan year.

$364 on average is just under 3% of total US per capita healthcare spending in 2023. This is real money that is due to an informational friction.

Real times claims adjudication has been getting pushed for at least twenty five years.  From my reading for this paper, it was mostly coming from the clinician side as they wanted to get paid faster while insurers were okay with holding onto claims a little while longer so they could sit on the float.  Insurer motivations to pay faster will be in conflict with interest rate float considerations as higher interest rate environments may still produce financial wins for insurers than low interest rate environments where lower utilization may be net profitable for the insurer.  We provide evidence that faster claims processing will lead to changes in medical utilization and costs.

Delays in bill arrival are costlyPost + Comments (17)