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Precision Medicine: Placing the Patient at the Center of the Healthcare Journey
Written by Viktor Chirikov on Wednesday, December 22, 2021
Personalized patient support is made possible by machine learning and AI-powered analysis of large data sets. With these tools, healthcare professionals can receive highly targeted information that eliminates irrelevant or redundant messaging and focuses on the unique needs of individual patients.
The insights and information gleaned from finely tuned AI-driven data analysis can give physicians and other healthcare providers vital tools for providing timely and individualized care. Delivered with the help of personal devices and cloud-based connectivity, AI-generated data can be provided instantly at any point in a patient’s journey through the healthcare system, enabling providers to respond in real time.
These tools can give providers access to the latest information not only about patients themselves but also about current research and treatment developments related to specific conditions. For example, at a patient’s bedside, a doctor can explore predictive models for disease outcomes to plan a new course of treatment or get instant access to the latest clinical trials on new drugs and therapies.
This kind of personalized support is made possible by machine learning and AI-powered analysis of large data sets. Technological advancements in the availability of big data can play an important role in health economics and outcomes research (HEOR) as well, where precision medicine applications can help discover and align the treatment pathways with the highest likelihood of improving specific patients’ clinical outcomes and quality of life. Precision HEOR (P-HEOR) integrates economic and clinical value assessments to optimize the cost-effectiveness of healthcare interventions.
Interested to learn more about precision medicine and how AI is changing the health communications landscape?
Viktor Chirikov is a Director in Real-World Evidence and Modeling & Meta-Analyses, located in the Bethesda, MD office. He has over 10 years of HEOR experience and is the in-house expert in artificial intelligence and machine-learning applications to RWE.