Image retrieved from: https://gloriumtech.com/top-5-use-cases-for-ai-in-healthcare/
Introduction
Artificial Intelligence (AI) integration into healthcare facilities is paving the way for transformative advancements as it revolutionizes diagnostics and decision-making, enhances patient care and monitoring, and drives innovation in research and development. By delving into the various ways AI is being innovated, medical scientists can uncover its profound impact on healthcare. This investigation examines the utilization of AI in healthcare facilities, analyzing its effects on diagnostics and decision-making processes, patient care and monitoring practices, and advancements in research and development. By exploring these areas, scientists can gain valuable insights into how AI is reshaping and improving modern healthcare.
Unlocking Efficiency
AI has emerged as a game-changer in improving efficiency and productivity within the healthcare field. By automating routine administrative tasks, such as data entry and appointment scheduling, AI systems enable healthcare professionals to redirect their focus toward patient care and more complex tasks. Machine learning algorithms can analyze vast amounts of medical data, extract relevant information, and generate actionable insights, which saves valuable time for healthcare providers. According to Tina Moen, Project Lead of HealthSource Solutions, LLC, from IBM Micromedex, AI-powered predictive analytics can optimize resource allocation, streamline workflows, and enhance operational efficiency in hospitals and healthcare facilities. This increased efficiency improves overall productivity and contributes to better patient experiences and outcomes.
Supported by IBM (International Business Machines), IBM Watson AI became a data, analytics, and technology partner for the health industry. Watson AI was one of the AI-powered clinical decisions to increase the productivity of processes and medical data collection in the healthcare field. When Dr. Mark Weisman, MD, and colleagues did time studies on the searches conducted using Watson technology, they discovered that clinicians received their answers in less than one minute 73% of the time. According to IBM Micromedex, clinicians went from spending 3 - 4 minutes per clinical search to less than one minute on average. The average use of clinical decision support increased by ten times in one month as well. This is especially helpful when factoring in dozens of patients across a single shift because time could quickly add up, leaving many providers to abandon using clinical decision support altogether.
Furthermore, hospitals could cut down on the number of those phone calls if they introduced an AI tool that would make it easier for consumers to engage with data sources and find the precise information they require on the first search. Clinicians would then only need to call in more complicated circumstances or for inquiries peculiar to a particular patient.
Health Monitoring and Treatment by AI
The precision of health monitoring and treatment has reached new heights with the advent of AI. Healthcare professionals can now administer customized therapies and monitor patient health with accuracy by utilizing AI algorithms and machine learning. According to a Wikipedia source on the use of AI in healthcare, the primary aim of health-related AI applications is to analyze relationships between clinical data and patient outcomes. AI programs are applied to diagnostics, treatment protocol development, drug development, personalized medicine, and patient monitoring and care.
However, AI does not directly administer medical treatment in the traditional sense. Instead, AI plays a significant role in assisting healthcare providers with making treatment decisions. AI can help healthcare providers personalize treatment plans based on individual patient characteristics, optimize medication dosage and timing, and even assist in surgical procedures through robotic systems guided by AI algorithms.
Conclusion
In conclusion, AI integration into healthcare facilities revolutionizes diagnostics, decision-making, patient care, and research and development. AI improves efficiency and productivity by automating tasks and optimizing resource allocation, leading to better patient experiences and outcomes. As the healthcare industry continues to embrace AI, the future holds strong potential for advancement in patient care and shaping a more efficient and effective healthcare system.
__________________________________________________________________________________
Thank you for reading!
- Mahima Bhat
References