Patient aggression in the hospital is a growing problem. Among nurses and other staff, violent or abusive behaviors have been linked to burnout and PTSD — two of the many reasons nurses have left the medical profession in recent years by the thousands. Preventing aggressive behavior before it can begin is perhaps the most effective, and elusive, strategy for reversing the trend.
Here’s a closer look at the problem of patient aggression, and an emerging tool that builds on technology already in use in clinical settings.
Aggression in hospitals: a growing problem
The increase in aggressive behavior toward hospital staff — mostly nurses, but also other caregivers — has been well-documented.
A 2023 survey conducted by the National Nurses United (NNU) showed nearly half of nurses (45.5 percent) reported an increase in workplace violence in the previous year. Another study published in April revealed more than 138,000 nurses have left the workforce since 2022; more than 41 percent cited stress and burnout as the root causes. Psychiatric nurses and ER staff are particularly subject to the dangers of patient aggression.
Despite awareness of the problem, and de-escalation tactics that have arisen in response, 43 percent of nurses surveyed in 2023 reported experiencing abuse or violence in the workplace in the previous year. Patients are not the only perpetrators of aggressive behaviors, but eliminating or at least reducing it would improve clinicians’ working conditions dramatically.
The limits of today’s solutions
Many nurses have been trained on de-escalation methods, but these have their limits. The data tells the story. If today’s de-escalation methods were sufficient, violence toward clinical staff would not be on the rise.
Sometimes, a nurse trained on de-escalation might not be aware of an incident in time to de-escalate it. If a patient is being aggressive with another patient in the same room, for example, by the time a staff member arrives it’s too late. Even if no one shares the room with the aggressive patient, de-escalation gets more challenging as time passes, increasing the likelihood of a violent or abusive incident when a clinician walks in.
Nurses are often the first line of defense when patient behavior turns aggressive, but that doesn’t mean they are the best equipped to handle the situation. Unfortunately, many hospitals and health systems lack the money to pay for additional staff, security personnel, and monitoring tools that would reduce the burden and risk to nurses. Still, many health systems haven’t established adequate workflows to deal with an employee being attacked or abused on-site.
The power of vocal biomarkers
The human voice is a rich source of data. More than 2,500 distinct speech features have been identified, and are able to be instantly analyzed by today’s digital tools via ambient listening.
AI-based vocal biomarker analysis is already being used in a variety of clinical settings to detect signs of behavioral and cognitive conditions. These same platforms can be applied to detect aggression. How?
Imagine a nurse is making their rounds, bringing medicine to patients. If one patient has been speaking aggressively — to another patient in the same room, into a cell phone, etc. — the same ambient listening tools used to record a doctor-patient conversation can detect aggression in the patient’s voice. Depending on the algorithm’s settings, it can alert support staff, security, or other personnel to de-escalate the situation prior to the nurse’s arrival.
Currently that same nurse might have little to no clue if a patient is talking aggressively, or using violent or abusive language, before they walk into a room. By the time they arrive, it might be too late to de-escalate.
Imagine also the patient who becomes aggressive while talking to a nurse in their room. Currently, calling for security is a multi-step process for that nurse. An algorithm that detects aggression in the patient’s voice can save precious time, signaling for security while the nurse does nothing more than talk to the patient.
The vocal biomarker detection technology needed to identify aggressive speech already exists. So too does the kind of AI-based ambient listening platforms needed to process that data in real time. Now it’s just a matter of applying it in high-risk settings to prevent incidents before they arise. As violent behavior threatens nurses’ well-being and continues to lead to attrition, the time is right to deploy the technology.
About Kang Hsu, Jr. MD
Kang Hsu, Jr., MD is the Chief Medical Officer (CMO) of Canary Speech. He oversees Canary Speech’s clinical direction, supports product development, and works closely with strategic partners including Mayo Clinic, Microsoft, Samsung, LG NOVA, and major health systems. He also contributes to the company’s research efforts, collaborating with academic and industry partners to help advance the scientific development and clinical validation of voice biomarkers.
