AI tool can detect distress in overburdened hospital workers
Artificial intelligence could aid in early detection of psychological distress among hospital workers, according to research conducted by New York University’s Grossman School of Medicine.
WHY IT MATTERS
The study, led by researchers at NYU Langone Health, demonstrates how AI was able to detect signs of mental stress among healthcare professionals. The research could hold significant promise for the future of AI-based mental health screening efforts.
The research, published this week in the Journal of Medical Internet Research AI, delved into virtual psychotherapy transcripts involving more than 800 healthcare professionals, including physicians, nurses and emergency medical staff.
Transcripts from 820 individuals who received psychotherapy during the initial wave of COVID-19 in the United States, but were not part of the healthcare workforce, were included for comparison.
The findings, published online, revealed that among healthcare workers, those who discussed topics such as their experiences in hospital units, sleep deprivation or mood issues during therapy sessions were more likely to receive diagnoses of anxiety and depression.
The study identified four distinct conversation themes related to healthcare workers, including virus-related fears and experiences on hospital floors and ICU units.
While the heightened risk for anxiety and depression in healthcare workers discussing their experiences was relatively small at 3.6%, the model is expected to improve its distress identification capabilities as more data becomes available.
According to study lead author Matteo Malgaroli, a research assistant professor in the Department of Psychiatry at NYU Langone Health, this represents a significant advancement in mental health screening for healthcare professionals.
THE LARGER TREND
The use of AI could potentially play a role for a broader population, emphasizing the efficacy of AI technology to aid in mental health support, with natural language processing potentially evolving into a screening tool for detecting and tracking anxiety and depression symptoms.
Burnout is growing among physician assistants and those in the medical profession more generally as they battle growing data volumes and a contracting workforce.
According to a recent national survey of nurses, 100,000 nurses quit their jobs during the pandemic, and, by 2027, nearly 900,000, or almost one-fifth of the 4.5 million registered nurses nationwide, plan to do the same. This would endanger the national healthcare system overall if no action is taken.
In addition to using AI to spot stress symptoms, the technology could also be leveraged to identify clinical workflow flaws and create a strategy for improvements.
Doximity’s AI-powered chatbot tool, for example, could reduce the time doctors spend on administrative burdens.
In July 2022, a health-technology project in Hong Kong, received $5 million in public funding to introduce an AI-based, data-driven approach to mental health diagnosis and treatment.
Changi General Hospital has already leveraged AI to spot curable hypertension,. Its hypertension-focused lab with Shimadzu has been reducing the turnaround time of testing for primary aldosteronism, which was previously done overseas.
Talkspace uses linguistic regression to analyze de-identified behavioral health messages and alert providers to patients at risk for self-harm, which illustrates the potential for AI to detect additional mental health issues on the patient side.
ON THE RECORD
“Our findings show that those working on the hospital floor during the most intense moment of the pandemic faced unique challenges on top of their regular job-related stressors which put them at high risk for serious mental health concerns,” said Malgaroli in a statement.
“These results suggest that natural language processing may one day become an effective screening tool for detecting and tracking anxiety and depression symptoms, added study senior author psychiatrist Naomi Simon, MD, a professor in the Department of Psychiatry at NYU Langone.
Nathan Eddy is a healthcare and technology freelancer based in Berlin.
Email the writer: nathaneddy@gmail.com
Twitter: @dropdeaded209
