AI Robotics in Medicine

Twelve Montefiore utilization-review nurses were laid off after case volumes returned to normal, but they say Datavant’s platform replaced their work; Montefiore describes the tools as nonclinical paperwork support.

The dispute highlights the stakes of automation in utilization review, where insurance rules intersect with judgments about whether care is needed, and raises concerns about skills, system failures, and inequitable outcomes.

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Tracking: Medicine Robotics · AI Medicine · AI Healthcare

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1. Montefiore lays off 12 utilization-review nurses amid AI dispute

After returning from New York City’s largest nurses strike, Marilyn Shuler and 11 Montefiore co-workers resumed utilization-review work in February, using Datavant to abridge information sent to insurers.

In early July, all 12 were laid off after case volumes returned to normal; the nurses say the platform replaced their work, while Montefiore denies that and calls Datavant’s tools nonclinical paperwork support.

Datavant’s website describes it as an AI platform, but a Montefiore spokesperson did not address whether the program uses AI.

The dispute has become a wider warning from nurses’ leaders: automation could eliminate jobs, weaken clinicians’ skills through overreliance, leave hospitals exposed when systems fail, and reproduce historical inequities if tools do not serve diverse patients.

The stakes extend beyond this department because utilization review combines insurance rules with judgments about whether care is needed.

Key facts:

* Twelve Montefiore utilization-review nurses were laid off in early July.

* Marilyn Shuler had worked at Montefiore for almost 40 years.

* The nurses began using Datavant after returning from the strike in February.

* NYSNA represented 15,000 nurses during the earlier New York City strike.

* Montefiore calls Datavant nonclinical paperwork support and denies replacing workers.

Why it matters: The immediate potential beneficiary is Montefiore’s administrative operation: Datavant was intended to abridge information-sharing with insurers, and the hospital says technology supports care and outcomes.

The immediate losers are 12 experienced nurses, while the disagreement leaves workers uncertain whether an AI-marketed tool is streamlining paperwork or eliminating clinical roles.

The episode also highlights safeguards to watch as hospitals automate: clear disclosure of what systems do, continued human accountability for utilization decisions, workforce development that preserves clinical judgment, and testing for unequal effects across patient populations.

Nurses’ representatives specifically warn that overreliance could weaken skills needed when systems fail.

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