Disparities and variations in care exist in every health system, everywhere. But as healthcare providers seek to enable precision medicine, these variations pose a real and significant hurdle because they make it more challenging to understand how a patient might respond, what they have access to and what health outcomes can be expected.
Understanding these variances is key to improving patient outcomes across the entire healthcare ecosystem. And getting there requires a patient-centered and data-driven approach, rooted in real-world evidence. By looking at what’s really happening with patients, generating insights and ensuring that actors across the health system – from pharmaceutical companies developing new drugs to local health systems that treat patients directly – are able to use those insights to refine care, we can better predict and understand what works best and for who throughout the patient journey.
One area where this work has huge potential is in oncology. It’s well understood that the future of oncology therapies lies in identifying and understanding biomarkers – often small genetic differences that can tell us how a treatment is likely to work in an individual. This is at the very core of precision medicine and we’ve seen clear indications that the use of biomarkers in drug development has shown higher response rates, longer progression-free survival rates and even higher overall survival rates.
But while this is well known and well utilized in the realm of drug development, it has not necessarily filtered down to be used at the point of care. The ordering of biomarker testing by physicians remains suboptimal. This means that many patients with cancer may not be receiving treatments or therapies that are designed with their specific genomic biomarker information in mind.
Patients deserve better – and that’s why there needs to be a bigger emphasis and move towards connecting the life science companies who are doing the work of using biomarkers to develop therapies with the health systems where a majority of cancer care in the US actually occurs. By facilitating information sharing between the people developing the treatments and the people delivering them, we can create a cyclical flow of information including: data about which patients are most likely to respond to which therapies, and real-world data about what’s happening on-the-ground, between physicians and actual patients receiving this care.
Together, this information sharing can help create a system where we can perform root cause analyses to collaboratively create, execute and monitor a plan for every patient and every care team. But doing this will require a real effort to build trusted relationships between the health system and life science companies and a seamless, interoperable solution for sharing data that’s meaningful and useful for all involved. For instance, we can create a data-driven approach that combines both the individual, localized data for a health care system, the specific data around a patient and then broader evidence-based research done in the life sciences space and use them to create measurable, actionable solutions to real and unique health issues.
This is where real precision health starts and it’s why this kind of data sharing can become a genuine catalyst for change, addressing gaps in care, ensuring more patients benefit from genetic biomarker testing, and reducing waste and inefficiency by putting people on the most likely to be effective treatments first.
Healthcare data is extremely diverse, incredibly complex and is being generated at greater rates than ever before. But without being able to share that data and generate meaningful insights that get to both researchers and providers, we’re not tapping into this rich vein that could truly change patient outcomes across the board.
Photo: Natali_Mis, Getty Images
