Conference Presentation, Keynote, Product Demonstration
Yubin Park
- Healthcare is projected to shift from an unsustainable current U.S. system toward a comprehensive "personalized healthcare" model, described as a revolution extending beyond precision medicine, with full realization of this paradigm expected to require significant additional time to develop scientifically grounded machine learning algorithms.
- A new CMS bundled payment formal for joint replacement is scheduled to be instituted starting next year, requiring hospitals to manage care for 90 days post-surgery to achieve lower costs and better outcomes.
- Machine learning applications face challenges due to the non-randomized nature of healthcare data, where simple models ignoring bias risk wrong conclusions and erode industry trust, necessitating a new, intuitive paradigm rather than traditional classification or regression approaches.
- Future execution of personalized healthcare will involve joint decision-making between patients and doctors regarding surgical routes (robotic, arthroscopic, or laparoscopic) and care paths (skilled nursing, ICU, or inpatient rehab) based on analyses of genes, environments, and lifestyles.
- Chronic condition management will evolve to include personalized medications and engagement tools utilizing financial incentives to improve adherence, with every system axis including service bundles, benefit plans, and incentives becoming customized.
- Aquarian Health aims to increase efficiency, reduce costs, and improve outcomes by simulating care trajectories to facilitate joint decision-making and analyzing historical data to predict hospital-specific availability and quality of skilled nursing and home health agencies.
- Ongoing company initiatives include collaborating with a client to personalize surgery routes, designing medication adherence programs that account for global financial implications and drug cost structures, and working with Medicare providers to design improved financial plans and incentives for both providers and patients.