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Sizzling new WP with the incredible @sdschwab!

TLDR: The powerful really *are* living their best lives. Using data from military hospitals where both docs and patients have rank (a measure of power), we find that powerful patients get more care and have better outcomes.

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Though power is tricky to study in the real-world, we can do so with Military Hospital ED data.

How?
-Hierarchy is an imp way power is enforced in society
-Docs & patients have ranks, which we use to measure their power differential
-Patients as-randomly assigned to docs in EDs
5 big results (methods in paper!):

1) β€œHigh-power” patients, i.e., those who outrank their physician, get

more physician effort (RVUs)
more resources (tests, procedures, opioids)
lower chance of 30-day hosp admission

than β€œlow-power” patients 𝐨𝐟 𝐭𝐑𝐞 𝐬𝐚𝐦𝐞 𝐫𝐚𝐧𝐀
2) A doc provides more effort to patients 𝑗𝑒𝑠𝑑 promoted to rank R than they do to patients π‘Žπ‘π‘œπ‘’π‘‘ to be promoted to rank R. Patient’s promotion date is unknown to doc, so promotion only changes the power diff b/w them.

(Robust to placebos with 250 β€œfake” promotion dates)
3) Docs may be reallocating effort away from low-power patients towards high-power patients:

On days that a physician is assigned to a high-power patient, their concurrently seen low-power patients suffer (receive lower effort, are more likely to return to ED within 30 days).
4) Doc-patient concordance on race and sex interacts strongly with patient rank.

Eg: White docs give Black low-power patients less effort than White low-power patients 𝐨𝐟 𝐭𝐑𝐞 𝐬𝐚𝐦𝐞 𝐫𝐚𝐧𝐀. Outranking their doc allows Black patients to get more effort from White docs.
5) Why does this happen? Do the docs respect their high-power pats (status), or are they scared (authority)?

Using date of patient retirement β€” when status is kept but authority lost β€” we find that being high-power is beneficial even after retirement! So status plays a role.
We do a bunch of robustness checks -

physician FEs (account for physician ability/ practice style)
spec curve using 1200 covariate combinations,
re-running analyses limited to when ED is busiest (to minimize non-random matching),
propensity-matched sample etc …

All good!
Conclusion: the powerful enjoy better outcomes in society by simply possessing power. Given equity concerns, results may be especially relevant to healthcare …

but can be applied to any non-healthcare setting with a power imbalance (employee-employer, landlord-renter etc)

/FIN
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