Real-World Data Connects the Patient’s Past, Present, and Future: A Systems-Level Approach to Effective, Holistic Cancer Care
By Miruna Sasu, Ph.D.
Miruna Sasu, PhD, MBA is president and chief executive officer of COTA, Inc. of New York, NY.
Too often, fragmentation across the care continuum prevents the delivery of timely, tailored cancer therapies. By leveraging real-world data to inform our decision-making at the systems level, we can ensure that cancer patients have access to personalized, effective treatments.
For the typical cancer patient, the road to remission is anything but a straight line. From getting the right diagnosis to accessing the most effective therapies, patients face a fragmented and disjointed journey that can be filled with roadblocks and detours.
Part of the problem is the nature of cancer itself. It adapts and evolves to evade treatment, driving oncologists and life sciences companies to continually develop innovative therapies and update their standards of care.
But equally problematic is the way we direct patients along their journey. In too many cases, we cannot access the data-driven insights that we need to make timely decisions with our patients. We struggle to overcome systemic barriers, such as competing incentives and overly narrow methods of care delivery. And we don’t have the shared infrastructure in place to continuously learn from our patients and enhance future decision-making based on the lessons of the past.
Fortunately, we can change the status quo if we adjust our notions of what it means to work together at a systems level and if we leverage emerging assets, such as real-world data (RWD), to create a more comprehensive, predictive, and personalized pathway to better cancer care for all patients.
Healthcare is an industry of extreme specialization, which brings both benefits and challenges to patient care.
Naturally, it’s crucial to have experts with deep experience in very specific fields to ensure that people with complex conditions get the care they need. But specialization can make it more difficult for patients to get the right care at the right time.
For example, if a patient goes to a podiatrist for pain in their foot, the podiatrist will do everything she can to examine the relevant structures.
If they finds nothing remarkable, however, they likely won’t suspect that the problem might actually be referred pain from ovarian cancer. And chances are, they won’t have access to information about the patient’s mother’s BRCA-1 mutation, which potentially raises the risk of that cancer in the person they are treating. The patient will go home with a recommendation to rest and ice their foot, not a referral to an oncologist, and it may be weeks or months before they get the correct diagnosis.
Both the patient and the podiatrist did everything “right” in this situation, yet the outcome is still suboptimal for everyone involved.
That’s because both our care practices and our patient data are viewed through an overly narrow lens, causing us to miss the big picture and make connections that may fall outside of the traditional site-specific approach to medical care.
In cases like these, what we need is a generalist: a holistic, comprehensive view of the patient, their history, their clinical and non-clinical risks, and all of the other factors that may point to the correct diagnosis or a favorable response to a certain therapy.
Data can be that generalist. By combining RWD from electronic health records; claims; medical devices; patient reports; and other sources with clinical trial information, registry data, and additional inputs, we can begin to develop the systems-level thinking we need to effectively diagnose and treat patients with cancer.
To maximize the value of our data to inform care decisions, we need to reexamine the fundamental architecture of our operating environment.
Life sciences companies, clinical providers, payers, and regulators struggle with trust issues and conflicting incentives that inhibit collaboration and prevent us from working together efficiently as a coordinated system.
If patient data is to be the generalist that unlocks silos in care, we need to stop treating it as proprietary, competitive leverage and start viewing it as a shared resource that can actively save patient lives.
In order to successfully make this shift, we must transcend our individual motivations and more effectively share precise and applicable data-driven insights across the divide so that everyone can benefit from what RWD can tell us about the right patient care.
With this approach, we can begin to take that holistic, bird’s-eye view of patient care that is crucial for identifying and treating cancer as quickly as possible. We can start to build cohorts of similar patients based on rich and comprehensive information about their treatment paths and outcomes. Then, we can predict the experiences of future patients and get them on therapy sooner, make the next correct treatment decision, or enroll them in promising clinical trials.
The result will be better experiences and outcomes for patients and more fuel for innovation for life sciences companies and providers, including a more robust and targeted pipeline for filling clinical trials.
If used correctly, RWD can be the bridge that connects the isolated corners of the care environment and leads us along a smoother, faster, more personalized pathway to high-value cancer care.
RWD will be crucial for understanding how to efficiently pivot for the patient as their story evolves. As we integrate RWD into our decision-making processes, we will need to work together to make certain that it is created, collected, and curated correctly while paying the utmost attention to patient privacy and data security.
We know this won’t be an easy task, especially if we let historical divisions influence our relationships with one another. We know that we have a great deal of work ahead of us to realign incentives, develop our real-world data assets, and set appropriate guardrails for a newly collaborative industry.
However, it can be done. If we can put aside our personal viewpoints and look at the cancer journey through the eyes of a frustrated, frightened patient, we will be able to successfully focus on our shared mission to find new treatments for cancer, improve patient experiences, and ultimately save lives.
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