From Reactive to Proactive: Redesigning Patient Care Pathways Through AI-Driven Medical Devices and Predictive Analytics in Next-Generation Healthcare Infrastructures

In recent years, healthcare professionals have been forced to rethink healthcare delivery in an effort to tackle the challenges associated with a global pandemic, increasingly aged populations, as well as new approaches to treatment and diagnosis that are distinct from those of a few years ago. Even when assuming no acute reactive external stimuli, healthcare systems are under constant stress, driven by diverse social expectations and evolving patterns in how patients access and undergo treatment. Emerging disruptive technologies, especially in the realm of predictive analytics, artificial intelligence and big data, provide a unique opportunity to transform healthcare delivery before, during and after the treatment process. Innovations based on these technologies will allow for the design of new patient care pathways which emphasize early detection and treatment, prevention-focused healthcare, minimized patient invasive interventions, and improved patient education, reducing recovery times, and lowering the chance of re-hospitalization. Certainly, this technological application will also have an operational impact on the healthcare providers who will be required to go through a new learning curve. This paper first explores the various existing patient care pathways, their usage and the limitations as currently designed. The paper then offers a framework based on predictive analytics and other disruptive technologies in the field, that offers the foundation of designing speed up, optimize and re-design new patient care pathways in specific clinical areas such as cancer care, cardiology, chronic disease management, pediatrics, and surgery. Through their re-design, our aim is to leverage the wider availability of data as an input to address the operational inefficiencies observed with current patient care pathway designs, which precluded the opportunity to integrate these pathways improvements back into an enhanced and personalized patient experience, allowing for systems and usage designs which not only lower costs but also optimize time-effort value from all stakeholders’ perspectives. Finally, the paper discusses the educational implications for both clinical and business related health management areas.