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HCA rolled out an AI scheduling tool built with Palantir. Some nurses and radiology staff say it creates errors, extra work, and burnout.
In short: Health care workers at major providers say scheduling software built with Palantir is creating shift mistakes and added stress.
HCA Healthcare, the largest hospital chain in the US, has been rolling out a nurse scheduling tool called Timpani since 2023. HCA says it is now used at about 130 of its 190 locations. The tool was co-developed with Palantir and is meant to automatically build schedules based on expected patient demand.
Several nurses told WIRED the software often ignores their shift requests and time off. One Florida critical care nurse said she asked for 50 specific 12-hour shifts over four months, but the tool assigned her different shifts more than half the time. Nurses also said it sometimes stacks too many workdays in a row, which can leave staff exhausted.
Some nurses allege the tool can leave units short-staffed or with too few experienced nurses on certain days, including Sundays. They say this can delay care because senior nurses must spend time guiding newer staff. Nurses also report spending more time swapping shifts and appealing schedules than they did when managers made schedules by hand.
HCA spokesperson Harlow Sumerford told WIRED that nursing leaders, not the tool, make the final scheduling decisions. He said claims that the software is designed to reduce staffing at the expense of patient care are misrepresentative, and he said HCA is improving Timpani based on feedback.
WIRED also reported that Rayus Radiology received complaints after introducing a Palantir Foundry based tool meant to fill in scheduling details from doctors’ orders. Staff said it sometimes matched orders to the wrong patient profile or listed incorrect tests. Rayus said the “broad characterizations” do not fairly reflect its safeguards.
A key question is how much human review these systems get before schedules go live. Another is whether hospitals and clinics will share clearer performance data, like how often staff preferences are honored and how often schedules need manual fixes (like spellcheck that still needs a human to proofread).
Source: Wired