“Health is complex because it’s underpinned by an important human element– the patient,” Kristine Mullen, Evidation advisor and former Humana Vice President, said in a recent webinar.
Precision medicine is moving forward, driven by sophisticated new tools and a need to move upstream, addressing health issues before they become costly. The full power of precision medicine will leverage genomic, environmental, and lifestyle variabilities among individuals and cohorts in all new ways. Among these, the newest set of information that stakeholders can leverage into precision medicine solutions is real life data–i.e., digital data flowing through each of us daily which can characterize patient behaviors outside of clinic walls.
The Full Potential of Precision Medicine: Based on Biology and Behavior
For more than a decade, advances in precision medicine have been in realizing the promise of genomic information. However, little attention has been given to the behavioral factors that play a significant role in health outcomes, simply because measuring them outside clinic walls was extremely challenging–and nearly impossible, at scale. Today, with the widespread use of wearables, sensors and digital health tools, we’re able to capture previously invisible data reflecting patient behaviors outside the clinic — complementing genomic and clinically-derived information commonly used in healthcare today.
Just as genomic information is enabling precision medicine based on biology, patient-mediated data from connected devices will enable precision medicine based on behavior.
From Behaviors to Outcomes
Ushering in the next generation of precision medicine which will integrate this novel behavioral information will require more than simple data collection from one or two popular devices or apps. It will involve characterizing the whole person and intrinsically measuring individual patient behaviors of many forms to assess whether they are relevant, or not, to health outcomes.
Connected devices, both consumer and clinical grade, enable the passive, continuous capture of endless forms of behavioral data in the real lives of patients with their consent. Advanced analytics, AI, and machine learning enable us to quantify and understand the impact of the most relevant behaviors on outcomes even in complex therapeutic areas, at various stages of disease.
Take, for example, a large retrospective analysis of real life behavioral data from patients with self-reported chronic conditions across the US. The analysis utilized data from 7,261 users of wearables and trackers, demographic data, and health characteristics to develop a predictive model for the presence of chronic conditions.
Incorporating real life behavior data significantly improved the model’s ability to predict the presence of chronic conditions.
More specifically, the findings showed that intra-day step and sleep data recorded from passive trackers significantly improved the model’s ability to predict the presence of conditions related to mental health and central nervous system disorders.
As Mullen pointed out in a recent webinar, “Patients’ lives are complex. The episodic view we have of them today from doctors’ visits and clinical trials does not give us the full picture.”
Convergence around the “Behaviorome”
To fully realize the potential of precision medicine that integrates both behavior and biology, the industry needs to converge around the patient from both of these aspects.
Patients in the digital era are empowered and have the key to unlocking the future of precision medicine via the data they own and control. They are connecting into the health care ecosystem, tracking various aspects of their own health behaviors, and generally assuming more influential roles across therapeutic areas. Patients also have the opportunity to assume a critical role in real world health outcomes research, providing the foundation for value-based care. With their participation into studies outside clinic walls, they actively contribute to quantifying health outcomes in a whole new way, so we can finally see what’s working, or not, for them 24/7.
The industry leaders of the digital era of medicine will be the healthcare stakeholders that provide value while empowering and understanding patients in their daily lives. Providers can deliver more individualized care by accounting for behavioral differences in patient management. Health plans can better understand population cost drivers both inside and outside clinic walls to target optimal outreach and time interventions. Pharma can more completely assess therapeutic response, find new ways to measure and influence adherence-related factors, and quantify outcomes for value-based discussions with payers and PBMs.
In the digital era, a fuller potential for precision medicine can be realized due to our ability to characterize everyday behaviors of patients–anytime, anywhere, across therapeutic areas, and outside brick and mortar walls. Just as the human genome launched the first wave of precision medicine diagnostics, therapeutics and clinical tools, we are now rapidly defining the human “behaviorome” that will propel the next wave.
 Quisel, Tom, David C Kale, and Luca Foschini. Intra-day Activity Better Predicts Chronic Conditions. In: NIPS 2016 Workshop on Machine Learning for Healthcare (NIPS ML4HC). 2016.
Originally posted on LinkedIn