Medical Device Authentication Engine for Healthcare Data Integrity
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Solution Overview
Problem
Current remote patient care systems face inefficiencies in correlating device and user data, leading to lost client-side information, inability to distinguish device users within households, and complexities in billing due to outdated CPT codes and lack of sophistication in handling new data sources.
Innovation Solution
A digital healthcare framework that includes a medical device with a sensor, authentication engine, encryption engine, and transmission component, which collects physiological data, authenticates users, attaches context information including unique device and user identifiers, and encrypts data before transmission, thereby ensuring data integrity and accurate ownership.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data correlation and mapping are performed at the data platform after data transmission, then data security during transmission is improved, but information loss occurs and processing efficiency deteriorates
Solution Approach 1:
The patent applies preliminary action by performing data correlation and mapping operations at the client-side device before data transmission. The device correlates physiological data with device ID and user ID, and maps this correlated data to the appropriate CPT code category before sending to the data platform. This eliminates information loss during transmission while maintaining security through encryption.
Solution Approach 2:
The patent introduces an intermediary processing layer at the client-side device that acts as a mediator between data collection and data transmission. This intermediary performs correlation and mapping functions locally, transforming raw physiological data into structured, coded data frames that include all necessary identification and billing information before transmission.
2Ease of operation
If multiple household members can use the same device, then device accessibility is improved, but user identification accuracy deteriorates
Solution Approach 1:
The patent implements feedback mechanisms where the device captures user identification information (such as virtual persona data) and uses this feedback to accurately attribute physiological measurements to the correct user. The system continuously refines user identification by correlating measurement patterns with registered user profiles, maintaining accuracy even when multiple household members use the device.
3Measurement precision
If CPT code mapping is performed manually or with simple rules, then billing accuracy is improved, but processing time and complexity increase
Solution Approach 1:
The patent transforms the CPT code mapping process by changing the parameters from manual or simple rule-based mapping to sophisticated automated mapping using multiple data parameters. The system analyzes physiological data characteristics, device type, user profile, and measurement context to automatically determine the appropriate CPT code category, significantly reducing processing time while maintaining or improving billing accuracy.
Solution Approach 2:
The patent replaces manual or rule-based CPT code mapping mechanisms with automated electronic mapping systems. The system uses algorithms and computational methods to perform code mapping, substituting mechanical or manual processes with electronic automation that processes data faster and with greater consistency.
4Speed
If data is transmitted without encryption, then transmission speed is improved, but data security deteriorates
Solution Approach 1:
The patent applies local quality by implementing selective encryption strategies where different portions of the data are encrypted with different levels of security based on their sensitivity. Critical identification and billing information is encrypted with higher security protocols, while less sensitive physiological data may use lighter encryption, optimizing both security and transmission efficiency.
Data Source
AI summary
A novel device component in a digital healthcare framework adds context to physiological sensor data, where such context data includes a first unique identifier associated with the device and a second unique identifier associated with the user who the physiological data belongs to. The physiological sensor data along with the context data is then encrypted and transmitted via an encrypted channel to a coordination gateway.