(Thread) Centralization of complex operations would 🔼 outcomes...for pts who do get them. But how about pts who don't? How would it impact spatial access?

We tried to investigate this by simulating a state-wide centralization policy.

@AnnalsofSurgery

https://journals.lww.com/annalsofsurgery/Fulltext/9000/Simulated_Volume_Based_Regionalization_of_Complex.94944.aspx
We used CA's state database and identified pts undergoing pancreatectomy from 2005-2014, & use @googlemaps 's API to obtain driving times (real roads & traffic).

We then eliminated hospitals doing <20 pancreatectomies/year, & redirected to next closest hospital. Example below:
We then recalculated the population impact on driving times based on different thresholds used, & resulted as 👇.

While medians are important, key to pay attention to 75th percentile too. Because those 25% are always the disenfranchised & > vulnerable population, 🔼disparities.
It's resultant impact on mortality rates (flip side of the coin)? As below.

So based on the numbers, clearly there isn't any additional benefit to centralizing beyond 20 cases/year as it comes at the expense of spatial access.

For California, 20 cases/year was the magic #.
But how generalizable is this? We used NY's dataset and performed the same simulation, & found this.

Clearly tells a completely different story. Just like translational sciences, policy needs to be tailored to local needs as well (personalized policy?).
But little is known about patients' & caregivers' considerations and selection process when selecting hospitals for care.

Implementation of surgical policies need to be patient centric to preserve access to high-quality care that is consistent with their priorities & needs.
To that end, we've performed a qual analysis of pts from diff settings to better understand pts decision-making, & hope to publish soon.
Spoiler: vol/outcomes typically đź”˝on totem pole.

Until then, look out for great work by @DiazAdrian10 @DrHariNathan @KyleSheetz in this space!
You can follow @ZhiVenFongMD.
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