Strategy for reducing medical malpractice liability in OB
MedStar has been successful in reducing its medical malpractice liability in OB—to the point where it is no longer the most expensive department for liability in some of our hospitals—by following a two-part strategy.

The first, and it may seem obvious, is that we work hard to ensure we have the best teams possible at the bedside. We invest a considerable amount in the hiring, credentialing and onboarding process. We also make large ongoing investments in training and education, in monitoring the OB department’s performance, as well as creating a peer review program to ensure our staff are (and remain) the best they can be.

Even with that, however, we also understand if we are going to expect our staff to deliver the best care, we need to provide them with the best tools.

Since 2004, we have continuously invested in technology that supports our clinicians by bringing data, as well as evidence-based best practices and protocols, to them within their workflows. The technology not only provides guidance if things start to go wrong, but also helps minimize the variations in care that can lead to adverse outcomes.

Many of the unfortunate outcomes in childbirth root back to a delayed recognition and treatment of warning signs, so we use technology to help consistently identify those issues in a timely manner, potentially allowing more options for intervention. It doesn’t mean our clinicians are locked into a particular course of action; on the contrary, early warning may provide more flexibility in treatment so clinical judgement is even more critical.

As one of our nurses so eloquently said when asked about the technology: “I feel like I have an angel on my shoulder, whispering in my ear and helping me as I care for my patients.”

We are currently expanding the deployment of an artificial intelligence-driven perinatal early warning system that continuously monitors the data being generated by various devices (including our electronic fetal monitoring, or EFM, system), compares it to known patterns that have produced adverse outcomes, and alerts clinicians when trouble seems to be brewing on the horizon.

The advantage of the technology is its ability to look across the entire L&D encounter at once, automatically considering patterns across hours of data rather than the 14 minutes that typically are monitored on an EFM strip. Clinicians can then focus on using their training and expertise to determine if an alert requires an action on their part, even if it’s an escalation to a nurse manager or physician, helping them prevent issues rather than reacting to them after the fact.

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