< + > Shifting Our Healthcare Delivery Model from Reactive to Proactive

The following is a guest article by Paulo Pinho, M.D., Chief Medical and Strategy Officer at Discern Health

The U.S. healthcare system is largely a sickness model of reactive care delivery. In our current healthcare delivery model, interventions are triggered by patients becoming unwell; we don’t invest enough in prevention and when we do, prevention strategies are often misdirected.

This model is unsustainable, particularly given the nation’s changing demographics. In the next two decades, the number of adults over 65 will increase 30%, from 63 million to 82 million, accounting for nearly one-quarter of the U.S. population by 2050. While many of these older Americans will enjoy a long lifespan, their health span will be challenged by the burden of chronic illness (85% of adults aged 65 and older are managing at least one chronic condition, and two-thirds are dealing with two or more), or by acute impactful health events, many of which can be prevented. The U.S. ranks 68th globally in health span, with adults often spending the last dozen years of life in poor health.

To close the gap between lifespan and health span, the U.S. healthcare model must shift toward earlier detection and intervention, especially for aging adults with functional limitations. Predictive analytics represents a promising tool. Harnessing data, data science, and artificial intelligence (AI) thoughtfully can enable healthcare providers to detect subtle signs of decline that often go unnoticed. This proactive approach can help identify individuals at higher risk of adverse outcomes, allowing for timely intervention before conditions worsen.

A Game-Changing Tool 

Predictive analytics leverages advanced technologies and data science to analyze vast amounts of patient information. By identifying patterns and subtle indicators of health deterioration, predictive analytics can flag individuals at risk of adverse outcomes before they even show noticeable symptoms. In a healthcare system where clinicians are often rushed, this tool can be a game-changer, surfacing concise, actionable insights in a clinician’s workflow that improve both patient outcomes and the efficiency of care delivery.

The potential of predictive models is not limited to forecasting risks; they can also provide explainable insights into the drivers of patient’s health and impairment. This transparency is crucial in helping clinicians understand and address the factors influencing a patient’s health trajectory. Instead of overwhelming providers with data, predictive analytics simplifies it into insights, offering clear recommendations for timely, targeted intervention and impact.

Complementing Human Care

While some may fear that AI and predictive tools will replace human judgment, this is an unfounded fear. Technology is meant to complement, not replace, the expertise of healthcare professionals. Just as the stethoscope once revolutionized medical practice (despite early skepticism and challenged adoption), predictive analytics is poised to become an essential tool, enhancing the ability of clinicians to deliver personalized, data-driven care.

Today’s healthcare providers are asked to do more with less — seeing patients in under seven minutes while managing increasingly complex cases. Predictive analytics can alleviate some of that burden by surfacing critical insights that might otherwise go unnoticed. This is especially vital as the population ages and the demand for more personalized care grows.

Innovative technologies like predictive analytics tools can help our healthcare system evolve from a reactive to a proactive delivery model by enabling providers to more easily determine the right interventions for a specific patient. They can also serve to help patients better understand what is likely to happen in their healthcare journey in the future to encourage them to take proactive steps to prevent adverse events. By empowering providers to prioritize the most effective interventions, these tools can help erase the gap between lifespan and health span.

About Paulo Pinho 

Paulo Pinho, M.D., is the Chief Medical and Strategy Officer at Discern Health, a health technology startup focused on predictive data models to improve health outcomes. With nearly 25 years of medical practice, he is board-certified in Internal Medicine, Pediatrics, and Clinical Informatics. Dr. Pinho previously held leadership roles at Availity Clinical Solutions and Prudential International Insurance and founded PASE Healthcare. His global clinical experience spans diverse settings, and he remains a prominent public speaker and published expert in healthcare delivery and patient empowerment.