It’s crucial to keep patients safe when they receive care. This is especially important for mental health conditions, where early intervention can make a big difference. In recent years, the application of artificial intelligence (AI) in healthcare has shown great promise, and one area where it holds significant potential is the development of an early warning score (EWS) system for mental health patients.
“Early warning scores help care teams identify early signs of a patient’s health getting worse so they can take action early,” said Dr. Andrea Waddell, Medical Director Quality Standards and Clinical Informatics. “Knowing ahead of time that a patient may be at risk of harm can help us develop intervention strategies such as increased nursing attention and adjustments to their care plan.”
Data from the Canadian Institute for Health Information in 2021-22 shows that 1 in 17 hospital stays had unintended harm, and almost half of them could have been avoided. Waypoint’s Dr. Waddell is also the Regional Clinical Co-Lead for Mental Health and Addictions at Ontario Health’s Mental Health and Addictions Centre of Excellence. She and her team of researchers are seeking to change this statistic creating an EWS to prevent harm before it happens.
Artificial intelligence has revolutionized various sectors and mental health care is no exception. It can look at a lot of data, find patterns and give helpful information. When used in mental health care, AI can help detect problems early, make personalized treatment plans, and reduce the burden on healthcare providers.
While early warning scores are commonly used in acute medical settings, they haven’t been used as much in mental health. The EWS system involves always monitoring and analyzing each patient’s specific information including historical data and AI algorithms, to understand if they might get worse. Ideally alerting care providers up to 72 hours in advance so they can help the patient sooner.
Waypoint and its expert staff care for some of the province’s most severely ill patients. The hospital has a 20-bed acute mental health program, has submitted a proposal to the Ministry of Health to add an additional 20-bed unit, and is shifting the culture intentionally to become a learning health system; making the hospital uniquely positioned to build this early warning model. Leveraging existing frameworks, expert opinion, and literature, the hospital is proposing variables for an EWS and testing a machine-learning model on 2022 patient data. Frontline clinicians, patients, and families will provide input at every step to guide the selection of the final algorithm. Once finalized, the EWS will be piloted in some Waypoint units using a rapid-cycle quality improvement model.
“Early Intervention and timely detection of deteriorating mental health conditions is really about advancing person-centred care,” said Dr. Nadiya Sunderji, President and CEO. “Artificial intelligence enables personalized care plans tailored to individual patients’ needs, taking into account their specific risk factors, treatment history, and response patterns.”
Artificial intelligence unlocks tremendous potential in developing Early Warning Score systems for mental health patients, helping healthcare professionals detect problems early. Leveraging AI’s capabilities can enhance patient care, improve outcomes, and reduce the burden on mental health services. AI-driven solutions hold the key to revolutionizing mental health care for a brighter and healthier future.
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