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The AI Revolution Series – Introduction to AI Applications in Healthcare

AI is a transformative technology that if used correctly can increase the quality of care


April 17, 2024 – The healthcare industry is always evolving, and Artificial Intelligence (AI) is part of the transformation with the ability to increase the quality of care and access to care. AI has already made an impact on the industry and the opportunities to increase that impact are endless. As technology continues to advance, AI’s role in improving quality of care and enhancing the delivery of care in the comfort of one’s home, as well as the concerns that come with the impending implementation, must be considered. This is a hot topic in healthcare, and something that will only continue to grow as advances are made. That is why we are launching a series on AI, and its applications in healthcare.

As advocates, we are interested and excited to see how these advancements in AI can improve the quality of care for consumers, and potentially lead to better health outcomes, enhanced access to care, and increased control and self-direction for consumers. There is also a crucial role that value-based payments can play in advancing AI in healthcare. However, it is important that AI complements rather than replaces the human touch in healthcare. There are other challenges like privacy and regulation that need to be addressed as well, which we will analyze throughout our blog series. To learn more about our advocate’s perspective, check out our full write-up at the end of the blog!

Throughout our AI blog series, we will be touching on important topics, including: 

  • What is AI?
  • Applications for AI in Healthcare
  • Concerns with AI Implementation 
  • How AI Can Be Used for Healthy Aging
  • Applications for AI in the Home Health and Home Care Industry
  • AI and Mental Health
  • How Value-Based Payments and AI Can Improve Health Outcomes
  • How AI Can Improve Consumers’ Health and Wellbeing 

This blog, the first of our series, will provide an overview of the several types of AI and explore how it can contribute to the healthcare industry through different applications. 

What is AI – Understanding Generative vs. Predictive AI

Artificial Intelligence (AI) is the science of making machines that can think like humans. The goal for AI is to be able to do things like recognize patterns, make decisions, and judge like humans. AI has been adapted into many technologies and has already begun to revolutionize how care is delivered and managed. Among the many applications of AI in healthcare, two distinct types have emerged as particularly impactful: generative AI and predictive AI. Understanding the differences between these two forms of AI is crucial for being able to look at how they can both contribute to healthcare.

Predictive AI, also known as predictive analysis, is a subset of AI that focuses on analyzing historical data and machine learning algorithms to analyze patterns and forecast future events or conditions. In healthcare, this means utilizing vast amounts of patient data, including medical histories, lab results, and lifestyle factors, to predict health outcomes. For instance, predictive AI can analyze data from a large number of consumers with diabetes or high blood pressure to identify patterns based on indicators like weight gain or loss, along with dietary patterns to create recommendations for specific individuals. We need to ensure that the privacy of the individual consumer remains intact, which is why using AI to focus on groups might be the best route. This foresight enables healthcare providers to implement preventative measures, tailor treatment plans, and improve consumer outcomes. Predictive AI is invaluable in early detection, population management, and enhancing personalized care. 

Generative AI, on the other hand, involves training models to create original content. Models learn patterns from existing data and generate new data based on these patterns. Using algorithms, generative AI creates new content like images, texts, or data sequences, which can be indistinguishable from real human-generated content. In healthcare, generative AI has many great applications, such as generating synthetic data for research purposes, creating realistic medical images for training or diagnosis, and simulating responses to various treatment plans. Generative AI can also be used to provide insights for consumers. Consumers will be able to ask questions about a diagnosis they may have and receive a personalized progression forecast, then align the progression with the home modifications or assistive technology that could be helpful.

While both generative and predictive AI have their unique functionality, they both have a role to play in enhancing healthcare. As advocates, we see the combination with immense potential in enhancing independence and self-direction, with increasing informed choice. As these technologies continue to evolve, their integration into healthcare systems promises to make healthcare more proactive, personalized, and innovative.

AI Applications in Healthcare

As we have discussed, AI has a wide array of applications in healthcare. While we will get into more detail on how AI can be used to improve care in later blogs, here are some of the key applications of AI in healthcare:

  • Remote Monitoring 
  • Predictive Analytics
  • Personalized Care Plans
  • Medication Management
  • Fall Detection and Prevention
  • Social Companionship 
  • Mental Health
  • Assistance in Daily Tasks
  • Virtual Health Assistants
  • Personalized Care Plans

Beyond these current applications, in the long term, AI developed for self-driving vehicles could make 

the independent choices of a person with a disability infinite. Even the robotics being developed will become an increasingly important part of a bundle of services that support people at home. These long-term views are ones that we count on to enhance the quality of services, quality of life, and cost reductions, all aligned with value-based payments. 

Concerns with Using AI in Healthcare

While the integration of Artificial Intelligence (AI) into healthcare can tremendously benefit consumers and improve health outcomes, it also raises significant concerns. These concerns include: 

  • Data Privacy
  • Algorithmic Bias
  • Loss of Human Touch
  • High Costs of Implementation
  • Complexity of Integration
  • Accountability
  • Regulatory Challenges

It’s clear that while AI can significantly advance healthcare and improve outcomes and satisfaction for consumers, addressing these concerns is essential. This is something we will cover in much more detail in our next blog!

Advocates Perspective

AI is an advancement that can offer unprecedented opportunities to enhance healthcare, especially for aging individuals and people with disabilities. Through predictive analytics, personalized care plans, and improved operational efficiencies, AI can significantly elevate the standard of care by ensuring that aging individuals receive the attention and care they need in a timely and effective manner. It also supports their desire to maintain independence and quality of life as active members of the community. As we look to the future, AI will continue to play a pivotal role in transforming healthcare, but we still need to maintain compassionate care and strong human presence. We also need to ensure that both providers and consumers receive training in AI-technology and that the privacy of individual consumers, and their data is preserved. This is where value-based payments can come into the picture, by incentivizing providers to build out the infrastructure necessary to properly implement AI. 

Stay tuned for our blog next week, as we dive into the concerns with AI implementation in healthcare, including privacy, data security, and the importance of maintaining human interaction.


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About the Author

Fady Sahhar brings over 30 years of senior management experience working with major multinational companies including Sara Lee, Mobil Oil, Tenneco Packaging, Pactiv, Progressive Insurance, Transitions Optical, PPG Industries and Essilor (France).

His corporate responsibilities included new product development, strategic planning, marketing management, and global sales. He has developed a number of global communications networks, launched products in over 45 countries, and managed a number of branded patented products.

mandy sahhar

About the Co-Author

Mandy Sahhar provides experience in digital marketing, event management, and business development. Her background has allowed her to get in on the ground floor of marketing efforts including website design, content marketing, and trade show planning. Through her modern approach, she focuses on bringing businesses into the new digital age of marketing through unique approaches and focused content creation. With a passion for communications, she can bring a fresh perspective to an ever-changing industry. Mandy has an MBA with a marketing concentration from Canisius College.