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The fast-evolving field of precision medicine offers the promise of more effective treatments and better outcomes, and it’s time that we collaborate to keep outdated clinical and reimbursement practices from slowing it down.
Scientific innovation in precision oncology is moving more rapidly than ever. Targeted therapies requiring specific marker-testing comprise 87% of late-stage oncology drugs in the development pipeline, and in May 2020 alone, seven new drugs were approved for non-small cell lung cancer.
These breakthroughs mean cancer patients who once had few options are now finding gene mutations that have therapeutic options beyond chemotherapy that can extend and improve their lives, often with fewer harmful side effects. But they are tempered by outdated decision-making and reimbursement practices that threaten patient accessibility and the speed of progress in this area.
Here’s why doctors and payers must come together now to realize the potential of precision oncology.
Information overload is leading to inconsistent treatment decisions.
Consider this common clinical scenario:
Dr. Jones, a medical oncologist, is seeing her first patient of the day, a 42-year-old woman with breast cancer who has returned to review her genetic test from a previous exam. The report discloses a mutation that is treatable with a targeted drug. Dr. Jones pauses before writing the prescription; she vaguely recalls a recent article about a newer, more effective drug for this problem. She is forced to return to her computer for a review of recent abstracts for an update before deciding on a treatment.
This is not an unusual scenario in the era of precision medicine; it's inefficient and often inaccurate and costly.
This doctor’s uncertainty is also well founded. Oncologists today must factor in thousands of data points for each patient’s treatment, even as clinical information continues to change. Dr. E. S. Kim, the Chair of Solid Tumor Oncology at the Levine Cancer Institute, summarizes the problem, “You may think you know what a drug is approved for, but then you find out is has three other indications that were just approved that you didn’t know about, so it really becomes a challenge.”
There is simply too much information published too frequently from too many sources, making it difficult if not impossible for oncologists to keep up in real time. The cognitive burden has never been greater.
Testing is a concurrent challenge for oncologists. There are approximately 150 new diagnostic tests introduced in this field every month. Competing laboratories each market their own unique tests for personalized medicine with panels that vary from their competitors. Without decision support, it is impossible for a clinician to be familiar with the composition of each panel.
There are also philosophical differences that confuse molecular testing for oncologists.Many laboratories offer large-panel tests for mutations that examine more than 500 mutations. Many of those mutations are not clinically relevant for standard therapy, but they may identify patients for a clinical trial. A second approach is the small panel designed specifically for each type of cancer. These panels contain a much smaller number of gene mutations, but all of them have evidence and guideline recommendations supporting their importance for therapy selections. Today, most clinicians prefer the larger test, which can help ensure they don’t miss anything, but many payers are pushing back and only covering the smaller, evidence-backed panels.
One reason is that there is not clear evidence that the results of large panels lead to better treatment. In fact, a 2019 abstract presented at ASCO revealed that oncologists incorrectly matched the molecular alteration to the targeted therapy in up to 69% of cases (ASCO, 2019). The result of such inconsistency is wide swings between over and under-testing—both of which drive up costs for payers. At the same time, payer policies are slowing down precision medicine and driving up costs, too.
Burdensome prior-authorization processes amplify decision-making complexities, often causing treatment delays.
Another clinical scenario:
Dr. Jones’ second patient of the day is a 69-year-old man with multiple myeloma. After finishing her interview and examination, Dr. Jones writes orders including genetic testing for her patient. Ten minutes later her nurse returns with news that the patient’s insurance will not cover the genetic test she just ordered. Now, the oncologist must call the insurer’s prior-authorization service, and she spends another ten minutes finding a test from another lab that fulfills her requirements. This system slows down her efforts and her practice and it can cause confusion for the patient.
Most clinicians solve this test selection problem by selecting one test and using it exclusively in their practice. That pragmatic approach works well unless the payer won’t pay for the test. Just like the example at the beginning of the article, non-coverage forces oncologists to learn about new tests from other laboratories that may be identical except in name or price.
There are hundreds of labs each with their own unique test catalog. Payers may select preferred labs based on local access to their members, price, panel size, and the volume of services the labs provide for other specialties in the payer network. The possible combinations are almost infinite, and coverage often requires spending time on the phone with a payer clinician to select a covered test that meets the needs of their patient. It is beyond unreasonable to expect an oncologist to sort this complexity in the middle of busy day in the clinic—on top of making life-altering treatment choices.
One thing is clear: traditional prior-authorization processes simply can’t scale to meet the challenges precision oncology presents.
Payers want to provide the best care for every patient, but they have not yet found a consistent, repeatable, and cost-effective way to provide high-cost care to a small percentage of very ill patients while keeping costs low for the majority of their members. Payers are under pressure to balance the cost of precision medicine against rising premiums, deductibles, and out-of-pocket expenses for their members. The majority of them lack the resources and expertise to sift through the evidence and evolving options for tests and therapies. For this reason, coverage policies often lag behind the latest evidence, even as precision medicine evolves and becomes more targeted and effective. As a result, oncologists must often spend time discussing new therapies with payers causing stress and even treatment delays for patients when time matters most.
All of the above issues are preventing the rapid dissemination of new, targeted testing and treatments. They present a web of complexity for providers, payers, and patients that at times can seem impossible to escape. But these challenges are solvable.
The solution is technology and collaboration that integrates decision-support with operations.
Today, there are evidence-based precision medicine technologies that help physicians find the right treatments, and there are systems that help payers base their reimbursement models on the most up-to-date clinical evidence. However, there are still major disconnects in the processes that cause waste, inaccuracies, and inefficiencies. Oncology practice systems don’t talk to payer systems. Payer testing prior-authorization systems don’t talk to their treatment prior-authorization systems. Until all stakeholders can access a connected, trusted, up-to-date data source in real-time these problems will persist.
What’s needed is a technology that breaks down these silos and creates collaboration between physicians and payers to truly ensure better testing and treatment choices are made at every stage. A collaborative technology that brings all parties together on one platform to address covered services at the point of care and before decisions are made will ultimately help physicians and payers work together to manage the growth of precision oncology and provide better member care at a lower cost.
Only when everyone is aligned around what’s most appropriate for the patient, will consistent, value-based precision oncology be possible.
Dr. Lee Newcomer is a medical oncologist and former UnitedHealthcare executive known for his expertise in creating new approaches to make cancer care more effective and affordable. He currently serves on the board of directors at Trapelo Health, which is a healthcare technology company that connects oncologists, payers, labs and pharma to resolve the complexities and accelerate the effective use of precision medicine for cancer care.