The Executive Suite: Using AI to predict and prevent chronic illnesses

For too long, health plan utilization management programs have relied on reactive patient care methodologies and inefficient administrative workflows, resulting in suboptimal outcomes across patients' entire care journeys. Fortunately, a transformation in how we approach care is underway, including a shift towards more innovative, proactive care solutions that show promising signs of moving beyond simply treating illnesses to proactively anticipating and preventing them.

With more than 60% of U.S. adults living with chronic illnesses like diabetes and heart disease–making up 90% of the country's $3.8 trillion healthcare spend–the need for a proactive approach is evident. Innovations in value-based care delivery models, such as HMOs, ACOs, and other risk-bearing providers, as well as alternative payment models like MIPS, have gained traction but are slow-moving due in part to a lack of supportive technologies.

Today, the application of responsible and ethical artificial intelligence (AI) further improves the path for physicians to provide proactive, data-driven, personalized care throughout a patient's care journey, from diagnosis to post-operative care. AI's current advancements, combined with the increasingly accessible and growing trove of clinical, behavioral, and social data, have positioned upstream, preventative care to take place on a wider scale. In fact, the healthcare industry's average estimated budget allocation to AL/ML technologies is projected to nearly double, from 5.7% in 2022 to 10.5% in 2024. Responsible AI can efficiently synthesize data and unlock actionable insights, leading to more accurate diagnoses, faster prior authorizations (PA), personalized treatment, and proactive condition management for improved outcomes.

A significant benefit of investment in and adopting responsible AI is its ability to modernize and streamline outdated PA processes. AI can serve as an early signal that a patient's care episode is commencing. In PA workflows, AI plays a critical role in surfacing an evidence-based care path tailored to the patient's diagnosis and unique needs, preventing care delays and exacerbation of illness while also improving care quality.

Significant benefits of responsible AI in healthcare include:

Early detection & diagnosis: Responsible AI excels in identifying subtle patterns in large datasets, aiding in early intervention in critical conditions like cancer.

Predictive care through advanced clinical analytics: Responsible AI anticipates disease advancement and potential complications, enabling timely interventions and efficient allocation of resources.

Personalized care paths: Responsible AI guides providers and patients to make informed care choices, focusing on individualized treatment approaches and connecting patients with suitable physicians and care programs.

Enhanced communication: Responsible AI enables seamless communication and information sharing between providers, facilitating better coordination and ensuring patients receive the right care at the right time.

AI has the potential to drive a proactive transformation in healthcare by enabling personalized care paths and enhancing treatment effectiveness. While technology continues developing, AI plays a crucial role in early disease detection and streamlining prior authorization. Harnessing the vast pool of health data, responsible AI is not just modernizing but revolutionizing healthcare, marking a significant step towards proactive, preventative, and efficient healthcare committed to individual well-being.