Artificial intelligence (AI) is transforming the healthcare landscape by providing tools to help doctors make better decisions and save patients, and recent studies have demonstrated the profound impact AI will have on clinical practice.
The study, conducted by experts from Mount Sinai, revealed that AI-generated alerts can significantly improve patient care and outcomes.
Enhanced patient care with AI alerts
Studies have shown that when medical teams receive real-time AI alerts, patients are 43% more likely to receive enhanced care and are significantly less likely to die. These alerts signal a deterioration in a patient’s health, allowing for timely intervention.
“We wanted to see whether rapid alerts created by AI and machine learning trained on different types of patient data could help reduce both how often patients need intensive care and their likelihood of dying in hospital,” said lead author of the study, John Doe. Mount Sinai Hospital.
“Traditionally, we have relied on older manual methods, such as the Modified Early Warning Score (MEWS), to predict clinical deterioration.”
“But our study shows that an automated machine learning algorithm score that triggers an assessment by a provider is better than these previous methods at accurately predicting this decline. Importantly, it could allow for earlier intervention, saving more lives.”
Real-time AI alerts in clinical settings
The study was a nonrandomized, prospective analysis of 2,740 adult patients admitted to four medical-surgical units at Mount Sinai Hospital.
Patients were split into two groups: one group received real-time alerts from the AI based on predicted deterioration of their health, and the other group received no alerts, even though an alert was created for them.
In units where alarms were suppressed, patients who met standard deterioration criteria still received emergency intervention.
Findings from the intervention group were promising.
- Patients were more likely to be prescribed medications to support the heart and circulation, and earlier intervention by doctors was indicated.
- Patients were unlikely to die within 30 days.
Learning medical system
“Our study shows that real-time alerts using machine learning can significantly improve patient outcomes,” noted lead study author David L. Reich.
“These models will help support accurate and timely clinical decision making, sending the right team to the right patient at the right time.”
“We think of these as ‘augmented intelligence’ tools that will speed up in-person clinical assessments by doctors and nurses and facilitate care that keeps patients safe. These are important steps toward our goal of becoming a learning health system.”
Implementation and future prospects
Although the study was terminated early due to the COVID-19 pandemic, the algorithm was implemented across all step-down units at Mount Sinai Hospital.
These units are for patients who are stable but require close monitoring, and are a key step between the intensive care unit and the general hospital realm.
Currently, a dedicated team of intensivists visits the 15 patients with the highest predictive scores every day and makes treatment recommendations to their doctors and nurses.
The algorithm is continually retrained on larger patient datasets, improving its accuracy through reinforcement learning.
Beyond the clinical deterioration algorithm, Mount Sinai researchers have developed and implemented 15 additional AI-based clinical decision support tools across the health system.
These advancements mark an important step towards integrating AI into healthcare, enhancing patient care, and paving the way for even more innovative solutions in the future.
Improved patient outcomes
As demonstrated by the Mount Sinai study, the implementation of AI in healthcare has great potential to improve patient outcomes.
Real-time AI alerts not only enable timely intervention but also help medical professionals make informed decisions quickly.
As AI technologies evolve, their role in clinical practice will undoubtedly expand, promising a future where healthcare becomes more efficient, effective, and patient-centric.
AI tools such as real-time alerts enhance decision-making, allowing for timely interventions and improved patient outcomes. As AI becomes more integrated into healthcare, it will help healthcare professionals provide higher quality care.
Continual improvements in AI algorithms will enable more accurate predictions and customized treatments. Ultimately, AI will transform healthcare, making it more responsive and focused on patient needs, improving overall health and well-being.
The study has been published in the journal Intensive Care Medicine.
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