Jonathan Hirsch is founder and president of Syapse, a software startup that produces a platform allowing health systems to integrate electronic health records with genomic data. At the 2016 Oliver Wyman Health Innovation Summit, Jonathan participated in a panel discussion titled “The Future Is Here: Leveraging Precision Medicine Today.” Here, in a post first published in September, he shares his thoughts on how precision medicine will transform cancer treatment and what it will take to push precision medicine to the next level.
Oliver Wyman Health: Precision medicine has received a lot of attention (presidential, media, and investment), yet adoption remains low. What will it take to push precision medicine to next level?
Jonathan Hirsch: Given the historically slow pace of technology adoption in healthcare, 30 percent adoption within 3 years is amazingly fast! And the pace is accelerating: Just this month Dignity Health and Catholic Health Initiatives announced a joint precision medicine program, powered by Syapse.
The Obama Administation's White House Cancer Moonshot has been great for raising awareness and for encouraging data sharing, which is very important for generating evidence to demonstrate the value of precision medicine. Public awareness will help drive adoption through consumer demand. For instance, community health systems that can implement a precision oncology program will be well positioned to attract patients who want to be treated with the latest technology, or keep patients from going to other health systems for treatment. This will eventually push health systems to adopt precision medicine or to lose patients.
Health systems must set up their precision medicine program in a fully systematized and integrated fashion in order to scale and sustain. By disseminating best practices to physicians, having standardized workflows, and capturing real-world evidence in a learning health system, health systems can solve for larger problems, such as economic alignment with payers around reimbursement and risk-based models.
OWH: How will precision medicine change cancer treatment? And when will it become standard of care?
JH: Precision medicine is extending survival. Our collaborator, Intermountain Healthcare, just published a study showing that precision medicine applied to late-stage cancer patients (tumor sequencing and targeted therapies) doubled progression-free survival. Professional guidelines already recommend tumor sequencing for patients with stage IV cancer, and payers are more open to reimbursing targeted therapies if other lines of therapy have failed, so in some sense precision medicine is starting to approach becoming the standard of care.
In order to bring precision medicine to earlier stage cancers, we need to share real-world data on cancer patients: their clinical history, molecular profile, treatments, and outcomes. That will enable today’s patients to benefit from the experiences of prior patients, and arm physicians with a breadth of evidence upon which to select the right treatment. To accomplish this, Syapse has partnered with Intermountain, Providence, and Stanford to launch the Oncology Precision Network.
Software that tries to turn the physician into a data scientist will fail.
OWH: Along those same lines, most physicians have no training in data and analytics. How do you get physicians to embrace this technology and new approach to patient care?
JH: Software that tries to turn the physician into a data scientist will fail. Our guiding principle is to use software that makes it easy for physicians to practice better medicine by giving them the information they need to make the right decision for their patients.
In oncology, physicians are used to dealing with collaborative care team-based approaches and expert consults, and synthesizing complex information. They already refer challenging cases to tumor boards for review, so the system, networks, and relationships are already set up to take advantage of collective pooling of experience and past observations in order to come up with best course of action. With precision oncology, additional expertise in genomics and data analysis is needed, and the collection of past observations has to be done in a more granular way because of the more complex nature of the data. But the idea of specialization and requesting case review or seeking best practices from peers with different backgrounds, experience, and training is already built into the system.
So in that sense, most physicians don’t need to perform data analysis—as long as they have access to trusted expertise through their health system, through either dissemination of best practices or case review boards, where the health system is responsible for organizing data analysts, statisticians, geneticists, etc. Medical education does need to be updated to give physicians an understanding of the principles of the new techniques and methodologies, but just as we don’t ask statisticians to treat patients, we don’t have to ask physicians to write R scripts.
OWH: Naysayers argue that it is wrong to assume that we can prevent disease in people just by telling them they are at high risk for developing a disease. Can we use data to more effectively encourage behavior change?
JH: I would regard those people as population health naysayers, not precision medicine naysayers. Undoubtedly, behavior plays a very large role in wellness and disease, but that is not the problem precision medicine is currently trying to address. Precision medicine addresses two scenarios: 1. When an individual has an illness, can we molecularly characterize that illness so that we apply a tailored therapeutic approach that has a higher probability of treating or curing the illness faster; 2. Can we identify individuals who are genetically at risk for disease (independent of behavior), and intervene early through preventative treatments or close monitoring.
Risk profiling and preventative measures have been a hot topic in oncology, becoming mainstream with Angelina Jolie’s op-ed on her breast cancer prevention journey. Incorporating comprehensive cancer risk panels into clinical workflow is different from just telling people they’re at high risk—there are existing as well as developing guidelines for providers on whether to increase screening, or to rule out cancer risk in someone with a family history but not their family’s genetic mutation.