Decentralized Health Data Platform for Secure Clinical Trial Recruitment
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Solution Overview
Problem
Current systems lack effective and secure mechanisms for individuals to manage and control their health data, leading to inaccessible and underutilized health information, unnecessary duplicative tests, and limited progress in health research.
Innovation Solution
A computer system providing a data storage and sharing platform with secure, access-controlled data areas, application programming interfaces (APIs) for authorized data access, and features like encryption, deidentification, and automated procedures for data management and sharing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If health data is stored in separate proprietary systems with access control, then data security and privacy are improved, but data accessibility and re-use are worsened
Solution Approach 1:
The patent introduces a data intermediary layer (API gateway, data exchange platform) that mediates between proprietary health data systems and external applications. This intermediary enables controlled data sharing through standardized interfaces while maintaining the security boundaries of original systems, resolving the contradiction between security and accessibility.
Solution Approach 2:
The patent implements universal data access protocols and standardized APIs that allow multiple applications and systems to access health data through a common interface. This multi-functional approach enables the same secured data storage system to serve multiple purposes (clinical trials, research, patient access) without compromising security.
2Measurement precision
If patients must repeatedly fill out forms to provide health information, then data accuracy for each specific study is improved, but patient burden and time consumption are worsened
Solution Approach 1:
The patent implements preliminary data collection where patient health information is gathered once through standardized forms and stored in a persistent, structured format. This preliminary action eliminates the need for repeated form-filling, as the data can be reused across multiple studies with appropriate authorization, reducing patient burden while maintaining accuracy.
Solution Approach 2:
The patent creates standardized data copies and templates that can be replicated across different studies and applications. Once patient data is collected and validated, standardized copies can be distributed to multiple research projects without requiring patients to re-submit information, reducing time consumption while preserving data accuracy through template validation.
3Ease of operation
If health data is not shared across studies, then patient privacy control is improved, but research progress and data re-use are worsened
Solution Approach 1:
The patent implements dynamic permission systems where data sharing authorization is not static but can be adjusted over time. Patients can grant, modify, or revoke access permissions for their health data to different studies and applications dynamically, enabling research progress while maintaining ongoing privacy control.
Solution Approach 2:
The patent changes the parameters of data sharing from binary (shared/not shared) to multi-dimensional parameters including which specific data elements are shared, with which applications, for what duration, and under what conditions. This parameter-based approach enables nuanced data sharing that advances research while preserving patient privacy control.
4Adaptability or versatility
If standardized data formats and taxonomies are implemented, then data interoperability is improved, but system complexity for data management is worsened
Solution Approach 1:
The patent extracts the complexity of data standardization and formatting into separate, dedicated components (data normalization services, taxonomy mapping engines). These extracted components handle the complex transformations independently, allowing the main health data systems to maintain their original formats while still achieving interoperability through the specialized extraction layer.
Data Source
AI summary
Methods, systems, and apparatus, including computer-readable media encoded with computer program instructions, for a decentralized application ecosystem and data sharing platform. In some implementations, a system stores data for different individuals in different logical data storage areas. The system stores data indicating a set of predetermined data classifications, and for at least some of the data storage areas, the system determines and stores data classifications for data stored in an encrypted form in the data storage area. The system provides an application programming interface (API) that enables multiple different applications to access the data storage areas over a communication network. The system is configured to (i) provide access through the API to the data of data storage areas, conditioned on applications providing authorization tokens, and (ii) provide access through the API to the data classifications in the metadata that is not conditioned on providing authorization tokens.