Dynamic Code List Visualization for Efficient Cross-List Decisions
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Solution Overview
Problem
Existing user interfaces for building custom code lists are inefficient as they do not dynamically update and compactly present data in response to user inputs, leading to increased mental workloads and reduced decision-making efficiency.
Innovation Solution
The system automatically and dynamically calculates data in response to user inputs and presents it efficiently and compactly through interactive and dynamic user interfaces, allowing users to build custom code lists from multiple code lists with different machine codes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional static user interfaces are used for building custom code lists, then the interface structure is simple and easy to implement, but the data is not dynamically updated and requires manual refresh, increasing mental workload and reducing decision-making efficiency
Solution Approach 1:
The user interface is transformed from a static display to a dynamic interactive system that automatically updates data presentations in response to user inputs. The interface dynamically recalculates and represents data based on user selections, code list changes, and relationships, eliminating manual refresh operations and keeping users informed of current system state without requiring them to remember previous configurations.
2Loss of information
If large amounts of data are presented in traditional tabular formats, then all information is visible, but the data occupies excessive screen space and is difficult to navigate and digest quickly
Solution Approach 1:
The interface transforms flat tabular data into multi-dimensional visual representations including hierarchical trees, network graphs, and spatial layouts. These visualizations organize data in multiple dimensions (hierarchy, relationships, proximity) allowing users to comprehend large datasets at a glance while maintaining access to complete information through interactive exploration and drill-down capabilities.
Solution Approach 2:
The data presentation is segmented into multiple interactive views and levels of detail. The interface divides large datasets into manageable visual segments that can be independently explored, filtered, and manipulated. Users can focus on specific portions of the data while maintaining awareness of the overall structure, reducing cognitive load while preserving information completeness.
3Productivity
If manual data review and code list building processes are used, then the system is simple to implement, but the process is slow and costly with increased mental workload
Solution Approach 1:
The system performs automatic data calculation, validation, and relationship detection without requiring manual intervention. The interface autonomously updates data presentations, validates code selections against business rules, detects relationships between codes, and maintains data integrity. This self-service capability eliminates repetitive manual tasks while providing intelligent assistance to users throughout the code list building process.
Solution Approach 2:
The interface implements continuous feedback loops that automatically monitor user actions and system state changes. When users select codes, modify parameters, or navigate the interface, the system immediately recalculates and updates the data presentation with relevant information, warnings, and suggestions. This real-time feedback reduces mental workload by keeping users informed of implications without requiring them to manually track changes.
4Ease of operation
If interactive and dynamic user interfaces are implemented to automatically calculate and present data, then decision-making efficiency and user experience are improved, but the system complexity and development effort increase
Solution Approach 1:
The interface is designed as a universal platform that handles multiple data types, visualization formats, and interaction modes through a unified architecture. The same core engine supports various code list operations, data presentations, and user preferences, reducing overall system complexity despite the enhanced functionality. This multi-functional design allows the system to adapt to different user needs without requiring separate specialized components for each function.
Data Source
AI summary
A computing system accesses one or more code lists, each including a plurality of items, each item comprising an alphanumerical machine code mapped to a human recognizable concept. The system may receive a query from a user, determine any matching and/or related items in the code lists, and generate an interactive visualization of the matching items. The visualization allows the user to view and detect relationships between items from multiple code lists in a manner that is not possible through review of the lists separately. The user can select nodes in a tree structured visualization to initiate addition of the corresponding alphanumerical machine codes to a custom code list.