Extensible Templates for Research Study Management
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Solution Overview
Problem
Current data management systems for research studies, particularly in mobile-health (mHealth) studies, are cumbersome and inefficient due to the lack of common schemas or interfaces, requiring manual and ad-hoc management by software developers, and fail to seamlessly integrate immediate and subjective information with large-scale resources, making it difficult to combine public data with geospatial data effectively.
Innovation Solution
A research study management system utilizing deployable templates that allow for the configuration and management of research studies, enabling 'create once, deploy many' functionality, which automates setup and changes of configurations for instruments and analysis tools, integrating with various data sources and providing customizable interfaces for data merging, manipulation, and visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing data management systems are used for mHealth studies, then data can be collected from multiple devices, but the systems become cumbersome and expensive due to lack of common schemas and interfaces
Solution Approach 1:
The patent implements a universal data schema that enables multiple device types (wearables, smartphones, medical monitoring devices) to integrate their data through a common interface. This universal schema acts as a standardized language that different devices can speak, eliminating the need for separate management systems for each device type and reducing overall system complexity.
Solution Approach 2:
The patent introduces an intermediary layer (the common schema and interface specification) that mediates between diverse data sources and the research management system. This intermediary translates various device-specific data formats into a unified structure, allowing researchers to work with standardized data without directly managing the complexity of individual device protocols.
2Reliability
If manual data management by software developers is used, then data can be tracked, but the process becomes ad-hoc and expensive
Solution Approach 1:
The patent enables researchers to independently configure and manage their own study data using standardized templates and schemas without requiring specialized software development expertise. The system provides self-service capabilities through pre-built data structures and automated processing routines that researchers can deploy directly, eliminating the need for continuous developer intervention while maintaining data integrity.
Solution Approach 2:
The patent implements pre-defined data schemas, validation rules, and processing templates that are established before studies begin. These preliminary structures automatically guide data collection and processing throughout the study, ensuring consistency and accuracy without requiring manual configuration during active research, thereby improving both reliability and productivity.
3Ease of operation
If spreadsheets are used to record participant information, then data can be recorded simply, but the spreadsheets become unwieldy and lack data validation
Solution Approach 1:
The patent transforms static spreadsheet structures into dynamic, adaptive data models that automatically adjust to different study designs and device configurations. The system provides spreadsheet-like simplicity for data entry while incorporating automated validation, type checking, and constraint enforcement that adapt to the specific requirements of each study, maintaining ease of operation while ensuring data quality.
Solution Approach 2:
The patent implements automated feedback mechanisms including real-time validation, error detection, and data quality monitoring that immediately inform users of issues during data entry. This feedback loop maintains data quality control without requiring manual review processes, preserving the simplicity of spreadsheet operations while preventing unwieldiness through automated governance.
4Adaptability or versatility
If researchers need to combine public data resources with local geospatial data, then comprehensive analysis is possible, but the integration process becomes complex without common interfaces
Solution Approach 1:
The patent creates a universal data interface that enables seamless integration of diverse data sources including public health databases (Health.gov), geospatial information systems, and local research data. This universal interface standardizes data exchange protocols and schemas, allowing researchers to combine multiple data sources through a single unified approach rather than managing separate integration processes for each data type.
Data Source
AI summary
Configurations and techniques for a research study management system are disclosed, enabling deployment of an extensible, reproducible, and deployable template for use in assessment, intervention, or other research studies. In an example, a technique to configure a template to use in a research project includes associating the template with one or more instruments to collect project data, associating the template with one or more tools to process the collected project data, associating the template with a data set definition, and defining one or more rules of operation for the template. In a further example, a technique to deploy the template for use in a research project includes defining a schedule based on the template, defining a plurality of configuration parameters of one or more instruments, and deploying the template to engage a human study participant to perform data collection activities via the one or more instruments.