Real-Time Trial Candidate Eligibility Evaluation System
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Solution Overview
Problem
Current systems face challenges in efficiently analyzing and consolidating candidate data from disparate electronic health records (EHRs) and other data sources, making it difficult for trial coordinators to identify eligible candidates for trials in a timely and meaningful manner.
Innovation Solution
A method and system that allow for real-time evaluation of candidates for trial eligibility by accessing a database containing candidate data, updating this data, and automatically evaluating it against multiple trial criteria, with the ability to generate a graphical user interface (GUI) displaying potential trial matches and allowing for candidate interest responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If candidate data is stored across multiple disparate EHR systems and third-party laboratories, then data completeness is improved, but data accessibility and analysis efficiency deteriorate
Solution Approach 1:
The patent implements a centralized data aggregation system that consolidates candidate data from multiple disparate EHR systems and third-party laboratories into a unified interface. The system merges data from hospital EHRs, external laboratories, and other sources, allowing trial coordinators to access comprehensive candidate information in one location rather than navigating multiple separate systems.
Solution Approach 2:
The patent introduces a centralized data aggregation system as an intermediary layer between trial coordinators and multiple data sources. This mediator system handles data collection, standardization, and presentation, shielding users from the complexity of underlying disparate systems while maintaining access to comprehensive data.
2Measurement precision
If trial coordinators manually analyze candidate data from multiple sources, then data accuracy can be verified, but time consumption and productivity deteriorate
Solution Approach 1:
The patent implements automated pre-screening functionality that performs preliminary data accuracy verification and eligibility assessment before trial coordinator review. The system automatically evaluates candidate data against trial criteria, flags potential issues, and prepares organized candidate lists, reducing the manual analysis burden while maintaining accuracy standards.
Solution Approach 2:
The patent replaces manual data analysis mechanisms with automated computational systems. The system automatically retrieves, standardizes, and evaluates candidate data from multiple sources, comparing it against trial eligibility criteria without requiring manual intervention for routine assessments, thereby dramatically improving productivity while maintaining accuracy through systematic validation.
3Loss of time
If candidate data is updated in real-time from multiple sources, then data currency is improved, but system complexity and integration difficulty worsen
Solution Approach 1:
The patent implements a universal data interface that can connect to and standardize data from multiple different EHR systems and third-party laboratories using common protocols. This multi-functional interface handles diverse data formats and update mechanisms uniformly, enabling real-time data currency without requiring separate integration solutions for each data source.
Solution Approach 2:
The patent employs data standardization that transforms varying data parameters from different sources into a unified format. The system automatically adjusts data parameters, formats, and structures to match standardized schemas, enabling real-time integration and updates from disparate sources while managing system complexity through consistent parameter transformation.
4Ease of operation
If comprehensive candidate information is displayed in a single interface, then data accessibility is improved, but information overload and usability worsen
Solution Approach 1:
The patent implements a segmented interface design that divides comprehensive candidate information into organized sections and categories. The system segments data into relevant groups such as demographic information, clinical data, eligibility status, and contact information, allowing trial coordinators to access comprehensive information while navigating a structured, manageable interface rather than facing undifferentiated data overload.
Data Source
AI summary
Systems and methods can evaluate candidates for eligibility to take part in trials. For example, a system may receive a request related to a candidate and access a database that includes a collection of data related to the candidate. In addition, the system may receive an update to the collection of data to generate an updated collection of data and automatically evaluate the updated collection of data against a plurality of trial criteria. In some examples, the system may determining at least one potential trial for the candidate based on the evaluation and convert the updated collection of data into one or more criteria sections and may subsequently automatically generate, substantially contemporaneous to determining the at least one potential trial, a graphical user interface (GUI) including the one or more criteria sections and automatically display, within the GUI, a message to one or more users related to eligibility of the candidate for the at least one potential trial.