RPMShare - Database solution for remote patient monitoring (RPM) datasets of high density vitals

Why
Currently, patient home monitoring is a megatrend, promising to reduce readmission, and emergency visits and globally add years of health. Owing to US 21st Century act and Reimbursement Schedule from Medicare (up to 54 USD per month per patient) US market is flooded with RPM companies (over 100 for sure) providing primary physicians and hospitals the possibility to collect data from patients' homes, including blood pressure, blood sugar, weight, heart rate, and others. Most companies collect and store the data in free formats, creating an "unholy mess" of data, which has a very limited chance to be ever reused. The hospital only gets insights from single patient results as a dashboard concentrating on cases showing vitals going out of normal range. While research by scientific groups and several advanced companies shows that even data of medium accuracy could predict adverse events like heart failure weeks before happening.
A project which is able to provide a federated environment for these new types of data, allowing patients and hospitals truly own data, connecting it to classic EHR, and making data readily available for AI/ML, a project like this is poised to conquer the US maket, with other markets following the trend.

Who
RPM Companies collecting the data will love the solution which will transfer the data from devices using FHIR, provide full security and compliance, and will include a multitude of routine functions for data analysis, and even data representation. They will stop creating hundreds of repositories of similar software code and concentrate on patient success.
Hospitals will be able to have their own structured and standardized silos of data, they will have a chance to change RPM providers, and have a history of patient vitals. They will have EHR data and RPM data connected. Dashboards could be integrated into existing EMRs much easier and finally, they will be precious sources of integrated data for research.
Patients will be able to reuse their data, have it analyzed by leading health tech companies, and enrich their vitals with even more data from wearables and other devices.
Researchers will be able to analyze the data in the same cloud as it is stored, and by anonymizing datasets, with integrated EMR and RPM data, they could potentially assemble unprecedented volumes of data. AI/ML-ready datasets will boost the predictive power of digital health in only a few years from the first implementations of data collection.

How
HealthShare is already able to store and receive data in FHIR format, minor additions for hl7 standards are to be implemented and accepted by the community. In a way, RPMshare is a mini-version of HealthShare, if designed using an interoperability framework it could even have universal connection standards for existing devices. A secret sauce could be made from the integration of InterSystems solutions in anonymization and the IntegratedML package with RPMshare.
To create immediate value and populate cloud service a consortium or partnership with existing RPM companies could be developed, where they will receive benefits of instrumentation and standardization and InterSystems will populate hundreds of thousands of years of observations (assuming companies already have tens of thousands of clients). In simple words, it is an Uber for RPM data.