Getting Individuals on to the Right Treatment Faster
Matching the right individual, with the right therapy, at the right time has long been an axiom in healthcare. But the ability to identify the “right” individual is often limited by the relatively small, and homogeneous, patient populations studied in clinical trials, and the absence of understanding what really matters to individuals outside of a clinical setting. “It’s a major challenge that only 30% of individuals with heart failure are on guideline-directed medical treatment. When it comes to treating heart failure–as with many cardiovascular conditions–we need better tools to more rapidly identify people who aren’t yet receiving optimal care and engage with them beyond the clinic in order to get them on the right therapies faster” said American College of Cardiology, Chief Innovation and Science and Quality Officer, John S. Rumsfeld, MD, FACC. The increasing incorporation of patient-reported outcomes (PROs) and real-world evidence (RWE) into the evaluation of therapeutic interventions has helped to close the gap to some degree, but much more progress is needed to better assess and engage patients, and close the loop on their care. Fortunately, the evolution of person generated health data (PGHD) from consumer wearables and sensors, coupled with new technology enabling bi-directional relationships with large and diverse populations, is leading to major advancement in the ability to target the right individuals relating to: timely diagnosis; risk of disease progression; treatment response; and course of recovery.
The COVID-19 pandemic has created a real world laboratory to investigate the role of new technologies in the ability to make earlier and more accurate predictions of diagnoses. A study of a large population of healthcare workers in the Mount Sinai Health System found that longitudinally collected heart rate variability (HRV) metrics from consumer wearables has the predictive ability to diagnose COVID-19 up to 7 days prior to a laboratory diagnosis using a nasal PCR test.
The potential of remotely collected PGHD to identify patients at increased risk of disease progression was demonstrated in a recently published study of 65 individuals with ALS. By analyzing longitudinal speech samples collected remotely via a mobile app, these researchers were able to discern bulbar impairment before detection via the standard functional scales used in routine clinical practice, and could sensitively track the longitudinal decline in function.
The ability to quickly interpret an individual’s response to therapy is important in all conditions, but has added importance in the treatment of cancer. An excellent review article describes a number of relatively small observational studies that have explored how remote monitoring and physical activity measured via consumer wearables may be able to identify patients undergoing treatment for cancer who are at increased risk for adverse outcomes, thereby distinguishing those who could benefit from additional supportive treatment. This underlines the importance of having a clear signal from consumer wearables in order to be able to identify individuals that may not be on the right treatment, and reduce the large percentage of false positives that degrade clinician trust.
A study conducted by scientists at Evidation Health, of patients who had recently undergone lower limb surgery, demonstrates how PGHD from consumer grade technologies can be used to predict long-term recovery trajectories and detect patients at risk for delayed rehabilitation who might gain from more targeted interventions.
Incorporating patient-generated health data in safety and efficacy studies | European Pharmaceutical Review
3 big predictions for digital health in 2021 | Healthcare Dive
Research: In a research survey conducted with Lyft, it was found that 31% of Medicare & Medicaid beneficiaries missed provider appointments or ran out of medicine due to inadequate access to reliable transportation, suggesting that transportation insecurity magnifies health disparities. Among participants, those dual eligible for Medicare and Medicaid were most likely to miss an appointment or run out of medicine due to lack of access to reliable transportation. Read more here.
Evidation Health has entered Phase II of the study with The National Institutes of Health, using wearables to detect early warning signs of COVID-19. Initial results detected over 50 percent of cases by the third day of symptoms, and we believe this research may help early detection of future outbreaks. Today, we are examining an expanded set of commercial wearables with the goal of developing an early warning system that is sensor agnostic. Read more here.
Evidation partnered with Sanofi to assess the utility of person-generated health data as a marker of constipation symptom severity. Our work was presented at the UEGW 2020 conference showcasing the importance of understanding symptoms, behavior and medication use in the everyday life of individuals living with constipation. We found that several measures of physical activity and sleep were clinically and meaningfully associated with days in which persons experienced constipation and irregularity. Learn more about the presentation here.
Announcements: Last December, Evidation Health and the American College of Cardiology joined forces to launch Achievement for Heart Health, a curated health program that empowers individuals to better manage their heart health from outside the clinic. Individuals can share activity, sleep, blood pressure, symptoms information, including permissioned wearable data and will receive personalized evidence based educational content from CardioSmart, ACC’s patient engagement program on heart management. We invite others to collaborate with us! Learn more about the program in the Cardiology Magazine here.
Thought Leadership: Rapid advances in digital and remote health are changing the care delivery landscape. Evidation Health and Eli Lilly co-authored a piece about the industry’s shift to remote monitoring featured in FiercePharma. Read the article here.
Co-CEO, Christine Lemke joined The Moneyball Medicine Podcast to discuss why wearable technology is foundational to a more patient-centric healthcare. Listen to the podcast here.
Evidation Health is excited to be a founding member of the UCSB Center for Responsible Machine Learning. Evidation’s Luca Foschini will be working with William Wang to improve the level of privacy in person-generated health data collection and use, and machine learning applications. Read more about the vision here.
Karger Special Issue: Evidation Health and Karger Publishers co-hosted a rich discussion about what the future holds and how current advancements in digital measures will be the building blocks for a digitally-enabled, patient centric healthcare transformation. Watch the recorded session here.