Near-real-time Patient Data Transmission via Watchlist Monitoring
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Solution Overview
Problem
The disparate nature of electronic medical records (EMRs) across healthcare facilities complicates the retrieval and display of patient information, making it difficult for healthcare providers to access and utilize relevant data in a timely and unified manner.
Innovation Solution
A platform and service that enables near-real-time transmission of patient physiological data by determining changes in data elements and associating them with watchlists, which include connection data for third-party systems, allowing for integration and unification of patient data from multiple sources across a healthcare continuum.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple vendor-specific EMRs are used to store patient data across healthcare facilities, then each facility can maintain its own data source, but the disparate nature of data storage complicates retrieval and display of patient information
Solution Approach 1:
The patent introduces a data aggregation layer that acts as an intermediary between multiple vendor-specific EMRs and the user interface. This layer receives data from various sources in different formats, standardizes it, and presents it through a unified interface, thereby maintaining storage flexibility while simplifying data retrieval and display operations
Solution Approach 2:
The system implements a universal data model and standardized interface that can handle multiple data formats and sources. The data aggregation layer is designed to work with any vendor-specific EMR system, creating a multi-functional platform that retrieves and displays patient information across diverse systems through a single unified approach
2Reliability
If patient data is stored in disparate formats across multiple facilities, then each facility maintains data independence, but healthcare providers cannot access and utilize relevant data in a timely and unified manner
Solution Approach 1:
The data aggregation layer serves as a mediator that preserves the independence of each facility's data storage while enabling efficient unified access. It maintains the original data formats and structures at source systems, ensuring reliability and data independence, while simultaneously providing standardized, efficient access pathways for healthcare providers across the network
Solution Approach 2:
The system segments the data architecture into independent source systems and a centralized aggregation layer. Each facility's EMR remains an independent segment, maintaining data independence and reliability, while the aggregation layer segments and organizes data from multiple sources into a unified access structure that improves productivity and data retrieval efficiency
3Ease of operation
If a unified view of patient data is created from multiple sources, then data accessibility is improved, but the complexity of integrating disparate data formats increases
Solution Approach 1:
The data aggregation layer acts as an intermediary that handles all the complexity of integrating disparate data formats, standards, and structures. It implements data mapping, transformation, and normalization functions that unify data from multiple sources while shielding end users from the underlying integration complexity, thereby improving accessibility without exposing system complexity
Solution Approach 2:
The system creates standardized copies and representations of data from various sources in the aggregation layer. Instead of requiring direct integration of complex source systems, it generates simplified, standardized data copies that maintain the essential information while eliminating format discrepancies, thus improving accessibility while managing integration complexity through abstraction
Data Source
AI summary
Implementations for providing patient physiological data to a third-party system in near-real-time include determining that a value of a data element within a data source has changed, and determining that the data element is included in a watchlist, the watchlist including one or more topics, each topic being associated with at least one data element, and in response: providing a data element tuple associated with the data element, and transmitting the data element tuple to the third-party system over a network. Other implementations of this aspect include corresponding systems, apparatus, and computer programs, configured to perform the actions of the methods, encoded on computer storage devices.