Personalized and Precision Medicine are all the buzz since President Obama announced the Precision Medicine Initiative. However, after the government tragedy known as meaningful use, many are reasonably skeptical of government initiatives to improve healthcare. Plus, the rhetoric around what’s possible with precision medicine and the realities that most hospitals and doctors face every day feels like a massive disconnect.
The reality is that there’s good reason to be skeptical of precision medicine. Think about the scope of the problem. The world of health data that we live in today is 10-20 times bigger that it was even a decade ago. That’s a massive increase in the amount of data available. Plus, much of that data is unstructured data. Combine the volume of data with the accessibility (or lack therof) of that data and it’s easy to see why some are skeptical of really implementing precision medicine in their hospital today.
When you look at current EHR systems, none of them are built to enable precision medicine. First, they were built as massive billing engines and not as engines designed to improve care. Second, meaningful use has hijacked their development roadmap for years and will likely continue to hijack their development teams for years to come. Finally, there’s been so much money doing what they’re doing, what motivation do the entrenched EHR companies have to go out and do more?
The unfortunate reality of EHR systems is that they’re not built for real time availability of data analytics that provides improved care and precision, personalized medicine. Some may get there eventually, but we’re unlikely to see them get there anytime soon. I’ve heard precision medicine defined as a puzzle with 3 billion pieces. We have to start looking outside of traditional EHR companies to start solving such a complex puzzle.
The good news is that even though EHR vendors are not providing precision medicine solutions, we’re starting to see other vendors providing precision medicine solutions today. You no longer need to wait for an EHR vendor to participate.
One example of precision medicine happening today is the recently announced SAP Foundation for Health (we’ll forgive them on the somewhat confusing name). At the core of the SAP Foundation for Health is the SAP Hana engine. Unlike many EHR systems, SAP Hana was designed for real time data analysis of massive amounts of data and that includes both granular and free form data. You can see this capability first hand in the work SAP is doing with ASCO (American Society of Clinical Oncology) and their CancerLinQ project.
Dr. Clifford Hudis from CancerLinQ (Created by ASCO) described how personalized medicine to his grandfather was going around and visiting each patient. Over time that practice stopped and we started seeing patients in clinics where we generally only had one data set available to us: the clinical data that we captured ourselves on a paper chart. Unfortunately, as we moved electronic, we just recreated our paper chart world in electronic form. It’s too bad we didn’t do more during our shift to going electronic. However, that still means we have the opportunity to aggregate and analyze health data for the benefit of our patients. In some ways, we’re starting to democratize access to health data in order to enable precision medicine.
As Dr. Hudis pointed out, healthcare currently really only learns from patients who take part in clinical research trials. In other words, that only amounts to about 3% of adult patients who contribute to our learning. This limits our view since most clinical research trials have a biased sample which aren’t representative of the general population. How can we create personalized medicine if we only have data on 3% of the patient population? This is the problem CancerLinQ and SAP Foundation for Health are working to solve. Can they create a platform that learns from every patient?
ASCO together with SAP’s Foundation for Health is working to aggregate and analyze data across cancer patients regardless of whether they’re part of a clinical research study or not. In the past, Dr. Hudis pointed out that cancer tracking use to track cancer populations with simple groups like “small cell cancer” versus “non-small cell cancer.” That was a start, but had limited precision when trying to treat a patient. With this relatively new world of genomics, ASCO can now identify, track, and compare a patient’s cancer by specific genomic alterations. This is a fantastic development since tumors generally contain changed DNA. We can now use these DNA abnormalities to classify and track cancer patients in a much more precise way than we’ve done in the past.
This platform enables oncologists the opportunity to see real time information about their patient that’s personalized to the patients own genetic abnormalities. Instead of calling around to their network of oncologist friends, Cancer LinQ provides real time access to other patient populations with similar genetic abnormalities and could give them insight into what treatments are working for similar patients. This can also provide benchmarking for oncologists to see how they compare against their colleagues. Plus, it can show real time data to an oncologist so they can know how thorough and consistent they are with their patient population. Instead of working in a bubble, the oncologist can leverage the network of data to provide true precision medicine for their patients.
Another great example of precision medicine happening today is seen in the work of Carlos Bustamante, Professor of Genetics and Stanford University School of Medicine. Carlos is using SAP Foundation for Health to quickly identify genetic abnormalities in high performing athletes. Rather than recount the stories of Carlos’ work here, I’ll just link to this video where Carlos talks about the amazing insights they’ve found from studying the genomic abnormalties of high performing athletes. I love that his precision medicine work with high performing athletes has significant potential benefits for every patient.
Carlos is spot on in the video linked above when he says that the drop in genomic sequencing costs would be like taking a $400,000 Ferrari and now selling it for 10 cents. What originally took $13 billion and years of effort to sequence the first genome now takes $1500 and a few days. Access to every patient’s genome is going to change the types of drugs we develop, the treatment options we provide patients, our choice of drugs to treat a patient, and much much more. You can see that first hand in the work that ASCO and Stanford University School of Medicine are doing. Is there any more personalized medicine than the human genome?
Of course, the genome is just one of the many factors we’re seeing in the precision medicine revolution. We can’t forget about other variables that impact a patient’s health like environmental, behavioral, patient preference, and much more. We really are looking at a multi-billion piece puzzle and we’re just getting started. Remember that healthcare is not linear, but we’ve been treating it like it is for years. Healthcare is a complex matrices of challenges and we need our technology solutions to reflect that fact.
I see a beautiful future for precision medicine that’s already begun and builds into the future. We’re developing and targeting new drugs, devices and services that work for populations and individuals. We’re seeing new open, secure platforms that provide real-time flexible R&D analysis, genomics and other “omics” disciplines, patient cohort building and analysis, patient trial matching, and extended care collaboration solutions.
Data by itself is not valuable. However, the right engine on top of the right data is changing how we look at healthcare. We’re getting a much more precise view of each individual patient. Where have you seen precision medicine starting to take hold? What precision medicine solutions are you using in your organization?
Also, check out this infographic which looks at SAP’s view of precision medicine:
SAP is uniquely positioned to help advance personalized medicine. The SAP Foundation for Health is built on the SAP Hana platform which provides scalable cloud analytics solutions across the spectrum of healthcare. SAP is a sponsor of Influential Networks of which Healthcare Scene is a member.