Ann Wieben

What role should artificial intelligence play in nursing?

By Ann Wieben, Sigma Theta Tau National Honor Society of Nursing

As a new nurse, did you ever work with a seasoned nurse and just wish you could download their brain into your own? What impressed me most was their ability to recognize when a patient was experiencing a significant change in status before the rest of us. Their wealth of experience enabled them to recognize patterns in patient data—sometimes in intuitive ways that they couldn’t even articulate themselves. So, what if there was a way to support newer nurses in recognizing patterns in patient data to enhance their ability to recognize changes in a patient’s condition or a patient’s risk for an adverse events? That is the potential that machine learning has in nursing when it is used to drive clinical decision support (CDS) systems.

Machine learning (ML) is a branch of artificial intelligence (AI) that focuses on building computer applications that can learn and adapt without being programmed with specific instructions. Supervised ML is one type that involves training an algorithm with known inputs and outputs. In healthcare, we have a wealth of data about our patients such as lab values, vital signs and other assessment data, comorbidities, and much more. We also know the outcomes of patients we cared for in the past and whether each of these patients experienced an adverse event, such as sepsis or a fall. Data on these historic patient outcomes can be used to train machine learning models to predict adverse events or other outcomes for our current and future patients. This support to recognize patterns in patient data could help nurses and other care team members intervene earlier and implement interventions to mitigate the identified risk and reduce adverse patient outcomes.

During my work as a nurse informaticist, I managed a pilot project of a sepsis machine learning model decision support system. When I turned to the literature to find evidence-based practices to implement this novel form of CDS safely and effectively, I found that the literature on this topic, particularly studies that focused on nurses, was sparse. As a result, I have made the integration of ML-driven CDS the focus on my dissertation studies. Read more …