daniel medina - AI Warriors

Perspectives

Kylie Cherco is most excited about how leveraging AI technologies and data as a strategic asset to personalize health care.

The AI Institute is proud to introduce a new series profiling AI warriors who are pushing the boundaries of what’s possible in the search for new and innovative uses of AI.

Can you share the most interesting part of your career journey?

I feel like I’ve grown along with our clients as we’ve navigated their data, analytics, and AI journeys.

When I started at Deloitte in the Information Management practice, a lot of my work focused on helping our health care clients organize their traditionally siloed data to support reporting efforts and business processes, such as managing value-based care programs.

It’s been so interesting and rewarding to learn and grow alongside my clients and colleagues.

We started talking about analytics and AI many years ago and how, for example, it could support health care providers in better managing a population of members assigned to them, or help health plans detect potentially fraudulent or wasteful activities by providers, but knew we needed to help our clients through their data and information management journeys first. Fast-forward to today, where I sit in the Analytics and Cognitive practice, and I’ve been fortunate enough to work with teams that have implemented solutions like those examples I mentioned.

It’s been so interesting and rewarding to learn and grow alongside my clients and colleagues, as well as build and share my knowledge in how AI technologies can be utilized to solve today’s big health care challenges around reducing the cost of care and improving health outcomes.

What excites you most about working with data and AI?

Being in the health care industry, I’m most excited about how we can leverage AI technologies and data as a strategic asset to really personalize health care for all consumers, as well as support the shift from the reactive “sick care” model that exists today to a predictive and proactive model that supports consumers in maintaining their health and well-being in the Future of Health.

By applying AI to not only consumer-generated data, but also other sources, such as clinical, claims, lifestyle, and social determinants data, we’re able to rapidly derive personalized insights about a consumer’s health.

Data continues to become more accessible, especially given that consumers are increasingly creating and owning more of their own data. By applying AI to not only consumer-generated data, but also other sources, such as clinical, claims, lifestyle, and social determinants data, we’re able to rapidly derive personalized insights about a consumer’s health. We can detect the risk of developing a condition, diagnose a condition, identify the risk of a condition progressing, and recommend a personalized prevention or treatment plan, all by using various types of AI technologies.

Describe an interesting project that you have worked on

I worked on a data and technology assessment for an online maternal health expert content provider who was looking to personalize the experience on their mobile app and website for new and expectant mothers.

We analyzed its current technical architecture and enterprise data management strategy to identify changes the client needed to make to accommodate the additional data it wanted to collect from mothers to support personalization.

We also researched competitors to better understand their app and website experiences and the data they were collecting. This helped us provide recommendations to the client on data attributes to collect in support of personalization without coming across as “creepy,” since we wanted mothers to feel comfortable sharing their data. It was also important for our recommendations to consider not only what data was needed, but how the client could collect, store, govern, and secure the data in the most effective way.

Being in the health care industry, I’m most excited about how we can leverage AI technologies and data as a strategic asset to really personalize health care for all consumers, as well as support the shift from the reactive “sick care” model that exists today to a predictive and proactive model that supports consumers in maintaining their health and well-being in the Future of Health.

I worked on an AI use case discovery and AI proof-of-concept development effort for a large academic medical center, which wanted to understand opportunities to increase efficiency by leveraging AI in its nursing, surgical, and pharmacy departments. Our team analyzed the current business processes and pain points in each department to determine where AI could be applied to address challenges.

We developed a framework to prioritize the AI use cases we identified and further built out the business case for the top prioritized use cases in each department, which included estimated implementation costs and total savings. We developed a proof of concept using machine learning and data visualization for a top-prioritized. Surgical use case related to operating room scheduling, which today is a lengthy, manual effort.

The solution predicted the expected volume of surgical cases, provided an optimal schedule of departments assigned to operating rooms based on case volume, and displayed a dashboard with metrics on how operating rooms were being utilized.

 

AI warriors

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