The Future of Healthcare: AI and the Role of Administration in Enhancing Patient Care
Artificial Intelligence (AI) is transforming healthcare as we know it, offering potential solutions for longstanding challenges and bringing new opportunities to enhance patient care, streamline processes, and improve outcomes. Healthcare administrators are pivotal in implementing and managing these AI technologies. Here, we delve into specific applications of AI, such as predictive analytics, medical image analysis, and personalized medicine, and explore how healthcare administrators can effectively leverage these technologies.
Predictive Analytics: A Proactive Approach to AI in Healthcare
Predictive analytics is a game-changing application of AI in healthcare that allows clinicians and caregivers to anticipate and manage health issues proactively. It uses historical and real-time data to make meaningful predictions, which can be used for individual patient care and broader population health interventions or to address operational and administrative challenges in hospitals.
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In an ICU setting, predictive analytics can detect early signs of patient deterioration, allowing caregivers to intervene before a critical situation arises. A study reported a reduction in adverse events by 35% and a cardiac arrest reduction of more than 86% with the use of predictive analytics​.
Predictive analytics also extends its reach beyond hospital settings. It can identify at-risk patients at home, preventing unnecessary hospital readmissions and reducing associated costs. For instance, it can combine data from electronic medical records, fall detection pendants, and the historical use of alert medical services to predict seniors at risk of emergency transport within the next 30 days​.
Moreover, predictive analytics can help manage hospital resources effectively. For example, hospitals can avoid downtime and maintain continuous patient care by predicting the maintenance needs of medical equipment before they arise.
Healthcare executives have recognized the benefits of predictive analytics. A 2019 survey from the Society of Actuaries revealed that 60% of healthcare executives said their organization had adopted predictive analytics. Of those, 42% have seen improved patient satisfaction since using predictive analytics, and 39% have saved costs​.
Real-world examples of predictive analytics in healthcare include:
AI in Healthcare detecting early signs of patient deterioration
Detecting early signs of patient deterioration in the ICU and the general ward can be especially beneficial in the ICU, where a patient’s life may depend on timely intervention. Predictive algorithms can help identify patients with the highest probability of requiring intervention in the next 60 minutes​​.
Delivering predictive care for at-risk patients in their homes
They are delivering predictive care for at-risk patients in their homes, which has proven valuable in preventing patients from backsliding into a need for acute care after being discharged from the hospital​.
Identifying equipment maintenance needs
They identify equipment maintenance needs before they arise, drawing on predictive analytics in other industries, such as aviation, to address maintenance needs based on data analysis preemptively​.