“When will things go back to normal?”
This has been the question on everyone’s mind since the beginning of stay-at-home orders back in March.
And sadly, for several industries, there may not be a return to normal post COVID-19. Retail, restaurants, movie theaters, many of these businesses are already closing their doors.
The healthcare industry, however, finds itself in a much different position. COVID-19 has simultaneously exposed inefficiencies while speeding up a future of care that looks drastically different than the “normal” of 2019. We’ve already seen these changes in the rise of telehealth visits and the growing emphasis on initiatives around population and social determinants of health. We’ve also seen how a reliance on paper forms and inefficient software can no longer keep up with the new pace of healthcare.
All of this is leading to a future that puts more emphasis on preventing disease before it happens vs. treating disease after it’s already become life-threatening and incredibly expensive to manage. This fundamental shift is leading us toward precision health, an approach that represents more proactive and personalized care that empowers people to live longer, healthier lives.
It’s an exciting future to be sure, but in order for precision health to become a high-functioning reality, providers will need to greatly update their IT infrastructure to handle the vast amount of data necessary to proactively care for their patients.
Precision Medicine vs. Precision Health
First, a clarification on the difference between these two approaches.
Precision Medicine uses a patient’s genomic data or tumor biomarkers to appropriately prescribe and dose medications. The focus still remains on treating vs. preventing.
In Precision Health, clinicians use a comprehensive set of patient data, such as family/hereditary, genetic, and lifestyle, then leverage evidence-based care protocols to predict and preempt disease. It’s application in Oncology, the focus isn’t so much on, “What do we do at Stage 3 or Stage 4,” as it is, “How do we catch cancer at Stage 1 and 2, or prevent it from happening in the first place?”
Oncology is leading the way in Precision Health
In no other specialty is the evidence supporting Precision Health more clear than in Oncology. The result is early detection.
Early detection of cancer gives patients the best possible chance of survival. Consider the stark contrast in these survival rate statistics:
- 92 percent: The five-year survival rate for early-stage breast cancer (Stage 0/1).
- 17 percent: The five-year survival rate for late-stage breast cancer
Early detection also significantly reduces the cost of treatment
- The cost of treating cancer goes up by 109 percent from Stage 1 to 4
- Late-stage cancer treatments are up to four times as costly as cancers detected in earlier stages.
So why aren’t we seeing universal adoption of Precision Health to catch cancer early?
Because the current IT infrastructure wasn’t built for this
The majority of electronic health record systems in use today were designed thirty years ago, before the first human genome was sequenced, and certainly before genetically informed care was put into practice. EHRs have become massive transactional systems, not known for their nimbleness, making the level of customization needed for Precision Health unscalable.
And data is all over the place
Patient data is siloed across a broad ecosystem of vendors and providers that serve a specific function along a patient’s care journey. Doctors’ offices, hospitals, genetic testing labs, pharmaceutical companies and national guideline organizations all hold information that could be valuable if viewed together, but it is nearly impossible to do given current system limitations.
When providers attempt to bridge this gap and connect the dots, they find themselves spending hours on paperwork, insurance forms, and sorting through different Excel spreadsheets.
An alternative: What it looks like with CancerIQ software
Health systems using CancerIQ to enable Precision Health for their cancer patient populations have seen the positive results first-hand. For instance, Adventist Health boosted cancer screening rates by 200 percent. Methodist Jennie Edmundson Hospital Breast Health Center boosted early cancer detection rates by 25% after launching their high-risk screening program and implementing the CancerIQ precision health platform.
CHRISTUS Ochsner Lake Area Hospital in Lake Charles identified high-risk patients flagged by CancerIQ’s risk assessment program. They then referred them for MRIs, even for patients with normal results on prior mammograms. One patient, who was BRCA2 positive, had a small mass diagnosed from that follow-up MRI that hadn’t been caught on her initial mammogram.
This kind of diligence can save lives while also generating revenue. CHRISTUS did not have an MRI referral pipeline before they began referring high-risk patients to diagnostic imaging. Once they did, revenue grew as a result of adding high-risk screenings
It’s been a lot easier to track my numbers with CancerIQ. In five months, what we’ve generated, potentially, is just under $155,000 by adding these additional high-risk screenings for patients who would otherwise just be coming in for mammograms and going home.
-Leah Marcantel, Nurse Navigator at CHRISTUS Ochsner Lake Area Hospital’s Wellness, Screening, and Genetics Center
CancerIQ’s workflows enable customers to execute precision health at the individual patient level. The precision health platform, which integrates seamlessly into the existing clinician workflow, can:
- Screen patients for familial and genetic predisposition
- Identify high-risk populations and individualize treatment plans
- Manage high-risk patients over time, flagging patients for MRI’s and other preventive testing and treatment.
When will healthcare go back to normal?
In short: it won’t. But that’s not a bad thing. We’re at the beginning of a new chapter in precision healthcare that will catch cancer earlier, add years onto patients’ lives, and provide a data-driven approach that was previously unattainable.