What is High-Resolution Healthcare?
As advanced as healthcare is today, we haven’t yet figured out an objective way to measure functional outcomes—such as how easily a patient can get up and walk after knee surgery—when making treatment recommendations or paying claims/reimbursements. Weeks or months typically pass between office visits, limiting visibility into how patients are really doing.
Part of the reason healthcare cost is high and access is limited for underserved populations is that we simply don’t have enough visibility to tie it to what matters—functional outcomes. So instead, cost is driven by opaque diagnostic coding and fee-for-service strategies.
Digital health technologies have sought to improve patient care but have been limited by a fragmented ecosystem of different technologies that lack contextual understanding and silo patients from providers.
To address these shortcomings, we propose a new framework called High-Resolution Healthcare. We have built novel sensors and AI technology that can measure functional outcomes at a granular level and packaged this technology into an easily deployable plug-in that can be integrated natively into existing healthcare apps and websites. We believe that these advancements will augment care by improving outcomes and reduce costs by tying them to the needs of patients and providers.
What We Mean by “High-Resolution”
High-resolution tools refer to spatiotemporally precise objective measurements, such as the joint angle of an elbow and how it moves every 10 milliseconds. High-resolution Healthcare is about contextualizing these measurements to functional outcomes and treatment actions in their native healthcare community – for example how these joint angles relate to range of motion functional recovery after surgery and how it’s progressing relative to a similar population (e.g. in demographics, comorbidities, etc.).
The Impact of Care in Context
High-resolution healthcare can power a range of new capabilities. It builds on value-based care models by adding the ability to measure more granular behavior that tailors value to the individual within their health community, esp. when utilized in concert with more low-resolution measures like claims or clinic visit data. Here are a few potential advantages:
Power realistic recommendations for better outcomes
We can better triage high-risk patients and recommend treatment that considers a patient’s daily realities, increasing the chance of adhering to or completing treatment and realizing its benefits. In other words, we can better gain the insights to recommend the treatment that will be most effective for that unique patient.
Early Intervention and stop decline from compounding
We can better prevent comorbidities and decline that happen when patients are unable to complete treatment/when the impacts of mobility decline begin to compound.
More efficient healthcare delivery
We can better match provider time to the patients that need it most and provide adaptive notifications for providers, reducing administrative burden and saving time.
Discover unexpected insights
We can enable discovery of novel high-resolution biomarkers and how patients can be stratified and treated with more targeted therapies.
High-Resolution Healthcare and Value-Based Care
We believe that utilizing a High-Resolution Healthcare framework will drive more value-based and efficient healthcare delivery. It builds on existing value-based systems to align incentives with more predictive and preventive capabilities. Tailored to each patient, provider, and healthcare system, it flexibly connects what is most important to each patient's quality of life with each provider's effectiveness to manage their population.
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