Data Is Eating The World
Examining the consumer and clinical use cases for RWD in the health & wellness space.
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A special thank you to R.J. Briscione, Sr. Director, SDoH Strategy & Execution at CVS Health/Aetna for collaboration efforts on this piece.
The quantity and quality of real-world data (RWD) collected across the plethora of different health & wellness devices and electronic data sources has expanded precipitously in recent years. Once collected, RWD can be structured, analyzed and turned into real-world evidence (RWE), which the FDA defines as clinical evidence regarding the usage and potential benefits or risks of a medical product.
Even if not verified by clinical studies or trials to officially be considered RWE, insights derived from RWD serve many use cases within health & wellness, ranging from consumer to clinical - each consisting of different infrastructure components (i.e., data sources and integrations) that undergird novel applications.
The pandemic brought the importance of health literacy to center stage, fundamentally shifting the way people think about caring for themselves and spawning new consumer-facing products that offer both prevention and treatment. The emergence of these products catalyzed the proliferation of innovation across the entire supply chain.
Wearables & connected devices
Wearables adoption has been particularly strong in recent years as fitness monitors and smartwatches brought movement tracking to the masses and as consumer-facing medical devices made monitoring various analytes and biomarkers possible for the first time.
As more and more companies enter the wearables and connected devices space to capitalize on increasing demand, the number of siloed RWD repositories is expanding exponentially. However, garnering data in closed environments via hardware infrastructure is consumer health 1.0. Consumer health data is significantly more valuable when it can be interpreted in a way that creates positive behavior change.
In order to build consumer health 2.0, data interoperability across disparate data sources is a requirement, creating an entirely new wave of companies looking to enable the demystification of RWD via software infrastructure.
Think Plaid for wearables and connected devices. Companies such as Terra* and Vital provide a unified API solution that gives developers the ability to pull in their users’ health data across wearables such as Oura Ring* or connected devices such as Zwift.
This critical infrastructure piece affords customers two core value props: (1) speed-to-market and iteration velocity, and (2) the ability to correlate multiple siloed RWD repositories to ultimately produce personalized, longitudinal consumer experiences.
*Disclaimer: NEXT VENTŪRES portfolio company
Longitudinal health tracking
The insightfulness of point solution devices like Eight Sleep for sleep or Levels for metabolic health has constraints. In a closed ecosystem, triangulating insights and linking cause and effect is friction-filled and time consuming. True correlation is generated by an interoperable ecosystem enabled by data ubiquity.
By leveraging the aforementioned turnkey APIs or native integrations, emerging companies are tackling the opportunity of building consumer health 2.0. These companies' applications sit atop all of the health & wellness point solutions, aggregating metrics and allowing users to understand how everything fits together. Examples include applications for optimizing holistic health or fitness performance.
It’s important to note that while comprehensive insights or readiness scores are exciting and helpful on the surface, context is king. Wearables data should be treated like a smoke signal (i.e., a sign of where to look to uncover deeper insight) rather than a full-blown fire that needs to be doused with water straight away.1
Precision wellness & DTC medicine
As consumers look to stay healthier for longer, they are adopting a prevention-first approach to wellness.
Instead of bucketed supplement packs for immunity or cardiovascular health, precision nutrition companies are utilizing RWD collected through biomarker tests to offer supplement packs that are personalized to one’s deficiencies.
DTC precision medicine solutions are also utilizing RWD in a similar way to provide medications or treatments that are calibrated to one’s unique biology. Examples include prescribing birth control based on one’s genetic background and hormone levels or diagnosing vaginal infections by using AI to identify vaginal microbiome imbalances.
The RWD spectrum across clinical use cases stretches far beyond just data collected through connected devices or biomarker tests. Sources such as EMRs, payor claims records and social determinants of health (SDoH) databases collectively contain essential data that provide a holistic view of patients.
Remote patient monitoring (RPM) devices have become key components of modern digital care solutions. These FDA-cleared devices can include continuous glucose monitor (CGM) sensors, digital scales, blood pressure monitors and pulse oximeters that collect and track patient RWD.
EMRs, payor claims records and SDoH databases
Claims data submitted to payors help to paint a longitudinal picture of a patient’s interactions with the healthcare system that can’t be achieved by analyzing EMR data. However, where claims data excels in providing a comprehensive view of tests, procedures, and services provided, it lacks in depth of diagnoses and in timeliness given the nature of the healthcare revenue cycle.
Leveraging rich clinical data that lives in provider EMRs allows for real-time identification of patient conditions that may not be identified via claims data. Oftentimes, the payment that a provider receives (in a FFS model) is not directly related to the number or type of conditions for which the provider codes.2
While each source has its pros and cons, when combined, claims data and EMR data provide a complete, accurate, and timely view of a patient's clinical status.
Social determinants of health (SDoH) data serve as non-clinical information that helps to fill holistic patient information gaps, including the behavioral and environmental factors that influence daily health.
These vital data points live in sources such as census databases, Health Resources and Services Administration (HRSA) databases, Collaborative Drug Discovery (CDD) databases, Environmental Protection Agency (EPA) databases, community databases and third-party applications.
“We use SDoH data down to the individualized level, so that we can refer members with specific social needs to the ‘right’ match for them in order to create a true social-first, upstream model. These members may currently have high social needs, which would not necessarily show up as chronic conditions or high cost initially, but would over time, if we left the social needs ‘untreated’.”
- R.J. Briscione, Sr. Director, SDoH Strategy & Execution at CVS Health/Aetna
Similar to the aforementioned API solutions that function as data highways between applications and consumer wearables, companies such as Redox and Human API provide HIPAA- and SOC2-compliant APIs that allow providers, payors and developers to build and scale applications with a common interface for providers regardless of EMR or format.
Digital care solutions for chronic conditions
Many new digital care delivery companies are combining remote patient monitoring (RPM) devices with app platforms to help treat chronic conditions such as diabetes and hypertension. These FDA-cleared devices collect and track RWD and infuse it into a holistic digital care program that has been scientifically proven in clinical trials (i.e., RWE) to assist people in making and maintaining heathy lifestyle choices.
Companies such as Omada Health are going a step further by layering a care coordination coach on top of the digital care solution to help increase treatment adherence and patient return on effort.
RPM devices also promote in-home care delivery for post-acute transition, hospital-at-home programs or elders looking to age in place. With the help of a caregiver, patients are able to track vitals and work with providers (in-person or virtual) from their own homes while their health data is synced directly to their providers’ EMR.
Risk stratification software
Given that SDoH data is critical to realizing the shared benefits of value-based, holistic care, new social-first, clinical-second companies are emerging to provide whole-person solutions to every sector of the healthcare ecosystem.
Intelligence derived from these solutions help providers and payors better stratify which patients and members, respectively, are most impacted by social risk and in need of intervention. Examples include software platforms that work alongside a health system’s EHR or that integrate with a payor’s program.
“When we combine this social data and/or individual social indices with health records and claims, we can understand and quantify the impact social interventions have on things like avoidable utilization and quality metrics (STARs, HEDIS gaps etc.), with the goal of showing social’s impact on our true north star, total cost of care.”
- R.J. Briscione, Sr. Director, SDoH Strategy & Execution at CVS Health/Aetna
The proverbial ‘data is eating the world’ sentiment is taking hold in the health & wellness space and the use cases covered in this piece are just the tip of the iceberg. There are an abundance of additional clinical applications that leverage RWD, including the curation of proprietary data sets for academia research or RPM solutions for decentralized clinical trials, just to name a few.
The burgeoning use of RWD will be a boon to consumers and patients who stand to benefit from increased data transparency, agency and care accessibility. The tailwinds are equally as impactful for providers and payors as the confluence of clinical and social data not only make holistic, value-based care more feasible, but also reduce the total cost of care in the process.
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