Nurses report problems with shift scheduling using the Timpani tool in the HCA Healthcare network
Six nurses from the HCA Healthcare network described shortcomings in schedules created using the AI tool Timpani, including missing experienced colleagues and disregard for requested time off. According to HCA Healthcare, nursing team leaders decide on shifts.
Six nurses interviewed by WIRED magazine described problems with shift scheduling using the AI tool Timpani. The tool was jointly developed by HCA Healthcare and Palantir; since 2023 it has been deployed in approximately 130 of the 190 hospitals in the HCA Healthcare network. It uses the Palantir Foundry platform and forecasts of patient numbers and staffing needs to automatically build schedules.
According to the nurses interviewed, the schedules sometimes assign too few staff or a shortage of experienced colleagues and do not respect requirements for rest periods between shifts or days off. The nurses report spending more time on shift swaps and requests for adjustments. One experienced nurse described a shift with four less experienced colleagues, during which, according to her account, she had to postpone care for the most critically ill patients in order to help the others. The possible risk to patients is a claim made by the nurses, not a documented finding from an independent evaluation.
According to HCA Healthcare, final decisions are made by nursing team leaders, and the tool is being further adjusted based on feedback. The company states that shifts deviate from requested days off in 1% of cases on average, and that more than 98% of schedules include a mix of skills and experience. According to the company's management, the tool has also reduced the time spent on scheduling and reliance on costly contract nurses. However, the nurses interviewed describe persistent problems; one said that assigning shifts on requested days off used to be unusual at her facility.
Why it matters
For nurses, the described shortcomings may mean less predictable time off and more time spent adjusting shifts. For hospitals, what matters is whether the labor savings in scheduling simultaneously maintain sufficient staffing levels and an appropriate mix of experienced nurses; the company's aggregate figures alone do not explain the individual reported cases.
Two audiences, two different impacts
What this means
For individuals
According to accounts, nurses at the affected hospitals must more often deal with shift swaps and changes to personal plans, sometimes because of work assigned on a requested day off.
For a business
Automated scheduling affects team staffing and the distribution of experience across shifts. Reported shortcomings therefore require assessing staffing levels alongside the time savings the company cites.
People and managementCheck the original
Event sources
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