Forecasting Healthier Tomorrows

The Predictive Power of AI and Patient Data

By Thad Salido, MD, Vice President/Medical Director, Clinical Strategy & Innovation, Cohere Health
LinkedIn: Thad Salido, MD
X: @CohereHealth

The future of healthcare extends beyond treating illnesses; it’s about the ability to foresee and prevent them. With the emergence of AI and the rapid expansion of comprehensive population health data, we stand at the cusp of a healthcare revolution, poised to forecast patient health outcomes while revamping outdated prior authorization processes. Leveraging AI responsibly provides a path for physicians to support patients with high-value services throughout their entire healthcare journey, from diagnosis to post-operative care.

The application of responsible AI to ever-growing pools of patient data enhances clinical decision-making and offers a deeper understanding of diseases, treatments, and healthcare delivery, revolutionizing how we predict patient outcomes and pave the way for healthier futures. These capabilities also leave room for streamlining time-consuming administrative tasks associated with prior authorizations that cost physicians time and valuable resources. Generative AI, for example, is a tool that promises to unlock a portion of the untapped $1 trillion improvement potential within the healthcare industry. Generative AI automates laborious and error-prone operational tasks, granting clinicians access to years of clinical data within seconds and modernizing the infrastructure of healthcare systems.

Unlocking Insights for a Healthier Future

Electronic health records, medical imaging, and genomic testing have collectively generated a massive repository of healthcare information. By leveraging the wealth of knowledge within this patient data, AI algorithms and analytics can unlock previously inaccessible insights, providing a holistic view of not only a single patient but entire patient populations. These patterns can lead to more accurate diagnoses, personalized treatments, and proactive disease management. AI, with its capacity for processing and analyzing this data at scale, has the potential to transform healthcare delivery in several ways:

  • Early Detection and Diagnosis: AI-powered algorithms can sift through millions of patient data points to identify subtle patterns and anomalies that may elude human detection. This capability is particularly valuable in diagnosing diseases like cancer, where early intervention can significantly improve outcomes.
  • Personalized Treatment Plans: AI can tailor treatment plans to individual patients by considering their unique genetic makeup, medical history, and lifestyle. Data-driven AI can also initiate intelligent routing to care management programs and partner patients with the right physicians through comprehensive physician benchmarking. This ensures that treatments are more effective and have fewer side effects, leading to better patient outcomes.
  • Predictive Analytics: AI can predict disease progression and identify potential complications by analyzing patient data over time. This proactive approach allows physicians to intervene before conditions worsen. Predictive analytics can also help hospitals anticipate patient admissions and allocate resources accordingly.

Challenging the Prior Authorization Status Quo

Using outdated legacy systems to manage the prior authorization process is challenging. It’s an expensive administrative burden on physicians and can delay prior authorizations, decreasing positive patient outcomes. According to the American Medical Association, 93% of physicians have experienced care delays while awaiting approval from insurance companies for essential treatments, and 82% have observed cases of patients abandoning their treatments due to prior authorization complexities.

Pairing responsible AI and machine learning capabilities with patient data dramatically removes the prior authorization friction. AI’s deep exploration of comprehensive population health data enables precise predictions, which empowers physicians to take proactive measures. It also streamlines the prior authorization process by replacing traditional systems that are often sluggish and cumbersome with an expedited process that ensures evidence-based treatments are recommended from the outset, reducing the necessity for lengthy prior authorization reviews and ensuring prompt access to care.

In this era of transformative healthcare, the synergy between responsible AI and patient data promises healthier tomorrows and a more efficient and compassionate healthcare system. AI’s predictive power and patient information can revolutionize clinical decision-making and reduce the frustrations associated with the prior authorization process. Having responsible AI as an ally creates a path to a healthcare system that is not just reactive but anticipatory, and this partnership between technology and compassion holds the key to unlocking a healthier, more equitable future for all.