Even in the best of times, nurses work under a tremendous pressure, and that pressure increases exponentially in the event of something as far reaching and dramatic as a pandemic.
Moreover, what’s worse is when the tools that are supposed to make their lives easier, such as EHRs, end up doing precisely the opposite, usually because they don’t work as advertised and expected.
As Toni Laracuente, RN, chief nursing officer at EHR vendor Medicomp Systems, sees things, it’s time to include nurses in discussions of how to fix EHRs, and AI is one big topic that should be clearly on the table.
“AI and machine learning technologies offer great opportunities to lessen nurse burnout by reducing administrative burdens, especially the management tasks of hospital operations that require large amounts of data and fast, well-informed decisions,” she explained in a recent interview with HealthcareITNews. “For example, predictive and prescriptive analytics can help nurse managers to predict and provide guidance on workloads, which can vary greatly by facility, department and specialty.”
Based on predicted workloads, nurse managers can match staff scheduling, skill and facility resources, she added, noting that the ability to make automated workload predictions well in advance helps organizations to minimize barriers to patient care, improve patient flow and increase productivity across the organization.
“Using AI to automate administrative tasks also allows nurses, and nurse managers in particular, to focus more on strategic planning and proactive management, rather than constantly putting out fires and managing operations on an ad hoc basis,” Laracuente said. “Nurses experience enormous frustration – and burnout – when they must repeatedly address the same operational problems without seeing resolution.”
Laracuente also pointed out that adjusting EHRs to reflect nurse workflows can reduce the time they need to spend on the EHR, thus also reducing the potential for nurse burnout.
“Many enterprise electronic health record systems were designed to facilitate billing, funding and compliance requirements,” she noted. “As a result, clinician workflows can be very siloed, not specific to a role or care setting and lacking in tools to facilitate efficient interdisciplinary communications. This puts the burden on nurses to find other ways to communicate critical patient information, which can be more time-consuming and less efficient.”
More specifically, improving usability of the EHR makes the nurse more productive in care delivery, she said. By creating and collecting clean, relevant data and presenting it in such a way that supports specific user workflow needs, health IT makers can eliminate information silos and build comprehensive clinical records that are truly patient-centric and support proactive, high-quality care.
In short, Laracuente argued, “When nurses must fight the EHR to do basic tasks, spending more time searching and documenting in the record, patient care and hospital throughput slows while frustration and burnout rates escalate. Using AI-powered solutions that streamline clinical workflows and bring the important clinical details to the forefront at the moment we need it, not only can we make faster, more informed decisions, but nurses, doctors and patient care staff have more time to interact with patients and perform clinical work, which ultimately improves staff and patient satisfaction.”