Artificial Intelligence in Healthcare
Released: 01/06/2022
Artificial intelligence (AI) now has the potential to be integrated into all aspects of healthcare, from management to delivery and diagnosis. These advancements can help improve clinical outcomes, reduce cost, and improve population health. However, there remain some issues with AI that must be addressed. These include ethical and legal issues, a lack of data exchange, regulatory compliance requirements, and patient and provider adoption.
This document from our Health Information Management Working Group provides an overview of the fundamentals and concerns of using AI in healthcare systems at the present, with guidance, challenges, and predictions for the future. It provides examples, use cases, and treatment methods for how AI, machine learning, and data mining can be effectively utilized throughout a healthcare system, in areas such as telehealth, administering diagnoses, and patient care. It also addresses ethical challenges, legal issues, and how to reduce bias in AI.
Key Takeaways:
- How robotics and Robotic Process Automation (RPA) are used for a multitude of different tasks throughout healthcare delivery organizations (HDOs)
- How AI helps healthcare service providers improve the precision of diagnoses
- How HDOs can use predictive analytics to provide better services and reduce cost
- How telehealth uses AI to distribute electronic medical cards, administer personal consultations, and more
- How to reduce bias in your AI algorithm and the ethical and legal challenges related to AI
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