Dynamic Query Selection System for Health Attestation Accuracy
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Solution Overview
Problem
Users completing daily health attestations through online questionnaires often rely on muscle memory, leading to inaccurate responses due to repetitive question formats and ordering, which compromises the reliability of infection control measures.
Innovation Solution
A query selection system that dynamically varies the presentation format and ordering of questions, utilizing a database to generate inquiry prompts based on historical query selection information and user profiles, ensuring users actively engage with each question.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the same questionnaire format and question ordering is used repeatedly, then users can complete surveys quickly and efficiently, but users rely on muscle memory and provide inaccurate responses
Solution Approach 1:
The system dynamically changes the ordering and presentation of questions based on user responses and historical data. Question sequences are not fixed but adapt in real-time, preventing users from relying on muscle memory while maintaining survey flow and completion efficiency
Solution Approach 2:
The system uses feedback from user responses and historical query selection information to adjust subsequent question ordering. This creates a adaptive loop where the questionnaire evolves based on collected data, maintaining both efficiency and accuracy
2Reliability
If question ordering is varied dynamically, then response accuracy improves by preventing muscle memory, but system complexity increases due to database and historical data requirements
Solution Approach 1:
The database serves multiple functions: storing survey data, tracking historical query selections, analyzing user patterns, and generating adaptive question sequences. This multi-functionality reduces the need for separate specialized systems while achieving dynamic question ordering
Solution Approach 2:
The system automatically analyzes historical data and user patterns to generate optimized question orderings without requiring manual intervention. The adaptive logic serves itself by continuously learning from collected data, reducing operational complexity
Data Source
AI summary
Methods and systems for a query selection system are provided. The methods and systems include operations comprising: accessing a database comprising a plurality of data inquiries, a data inquiry of the plurality of data inquiries being associated with inquiry metadata including a data type, a data inquiry, a plurality of data responses, and display data; accessing a query definition group, the query definition group defining a plurality of data types to include in a data inquiry prompt; accessing historical query selection information representing one or more data inquiries of the plurality of data inquiries previously presented to one or more users; configuring, based on the query definition group and the historical query selection information, a set of the plurality of data inquiries; and generating the data inquiry prompt based on the configured set of the plurality of data inquiries.