Predictive Technology Selection for Clinical Trial Compliance
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Solution Overview
Problem
Researchers face challenges in selecting appropriate technologies for data collection in research studies due to the vast number of available digital health technologies, unclear capabilities, and rapid changes in technology options.
Innovation Solution
A computer system is configured to assess various technology items, such as devices and software packages, and select suitable options based on factors like data types, accuracy, battery life, network communication, reliability, and previous usage rates, using a database and machine learning models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If researchers manually evaluate technology options, then they can understand technology capabilities, but the process becomes time-consuming and inefficient
Solution Approach 1:
The system enables automated self-evaluation of technology options by using machine learning models to automatically assess technology capabilities, compatibility, and suitability for research studies, eliminating the need for manual researcher evaluation while maintaining high accuracy
Solution Approach 2:
The patent replaces manual mechanical evaluation processes with automated computational systems that use machine learning algorithms to assess technology options, substituting human time and effort with automated digital processing that operates faster and more consistently
2Reliability
If the system evaluates all available technology items, then it can find the most suitable option, but the complexity of the selection process increases
Solution Approach 1:
The system segments the technology evaluation process into distinct analytical components including capability assessment, compatibility analysis, and suitability scoring, allowing complex evaluations to be broken down into manageable parts that can be processed systematically
Solution Approach 2:
The patent introduces an intermediary computer system that acts as a mediator between researchers and technology options, handling the complexity of evaluation internally while presenting simplified results to users, thus shielding researchers from system complexity
3Productivity
If the system stores comprehensive technology data in a database, then it can efficiently retrieve and compare options, but the data management complexity increases
Solution Approach 1:
The system creates a universal technology database that serves multiple functions including storage, retrieval, comparison, and analysis of technology data, allowing a single data infrastructure to support diverse evaluation needs without requiring separate systems for each function
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for adapting digital trial to increase protocol compliance and retention. In some implementations, a system accesses (i) study data indicating a type of data to be collected in a research study and (ii) attribute data indicating attributes of participants in a cohort for the research study. The system identifies a set of technology items that are each capable of collecting the type of data indicated by the study data. The system determines a predicted level of compliance for each of the technology items in the set. The system selects a technology item for participants in the cohort to use in the research study based on the predicted levels of compliance. The system updates records for the research study to specify the selected technology item.