Decentralized Health Network Proof-of-Value for Adherence Monitoring
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Solution Overview
Problem
Current healthcare systems struggle with effectively monitoring and managing patient care outside traditional hospital settings, particularly in terms of adherence, tolerance, and risk assessment, which are crucial for value-based contracts and improving patient outcomes.
Innovation Solution
A decentralized health information network system utilizing a proof of value (PoV) consensus protocol to validate therapeutic events, attribute valuations, and facilitate settlements between payers and providers, while ensuring patient engagement and adherence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a decentralized health information network with proof of value consensus protocol is implemented, then patient adherence monitoring and therapeutic outcome validation are improved, but system complexity and implementation difficulty increase
Solution Approach 1:
The system segments the healthcare ecosystem into autonomous nodes (providers, payers, patients, pharmacies) that each maintain their own data locally. The proof of value protocol divides validation into discrete therapeutic events that can be independently verified and recorded on the distributed ledger, making the complex system manageable through modular decomposition
Solution Approach 2:
The distributed ledger acts as an intermediary layer that enables trust and validation between parties without requiring direct integration or centralized coordination. The proof of value consensus protocol serves as a mediator that automatically validates therapeutic events and attributes value, reducing the complexity of direct inter-organizational agreements
2Ease of manufacture
If static hard-coded data models are used for remote patient monitoring, then system implementation is simplified, but flexibility and customization capability are reduced
Solution Approach 1:
The system transitions from static hard-coded data models to dynamic, adaptable data structures that can evolve with changing healthcare requirements. The distributed ledger allows data models to be updated and customized by individual organizations without affecting others, enabling both ease of implementation and adaptability simultaneously
Solution Approach 2:
Each organization in the network can define and maintain its own local data models and validation rules tailored to its specific needs and patient populations. This local customization capability allows providers, payers, and pharmacies to optimize their implementations while maintaining interoperability through the common proof of value protocol
3Reliability
If comprehensive patient surveillance is implemented outside hospital settings, then patient safety and outcome improvement are enhanced, but data availability for value-based contracts is limited
Solution Approach 1:
The system establishes continuous patient surveillance through the distributed network, with therapeutic events and adherence data continuously captured and validated in real-time. This continuous data collection ensures both patient safety monitoring and comprehensive data availability for value-based contract validation without interruption or loss
Solution Approach 2:
The proof of value protocol creates feedback loops where therapeutic events are validated, value is attributed, and results are immediately available to all network participants. This real-time feedback mechanism ensures that data captured from home monitoring is promptly available for contract validation and care management decisions
Data Source
AI summary
A distributed network system in a healthcare environment provides for proof of value transactions among various stakeholders like patients, providers, and payers. The system operates based on predefined intervention, valuation, and communication rules governed by a consensus contract. These rules determine interventions in response to therapeutic events, attribute valuations to interventions for different stakeholders, and regulate communications within the network. The system records therapeutic events, selects interventions, communicates them to relevant nodes, assessing valuations, and settling transactions according to the consensus contract. Different scenarios are outlined, such as interventions based on diagnoses or observations, including actions directed towards patients or providers, and rewards for achieving therapeutic goals. Overall, the system enables transparent and accountable transactions in healthcare by leveraging distributed ledger technology within a consensus-driven network.