Clinical Decision Support System Temporal Context Management
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Clinical decision support systems (CDSS) face challenges due to the complexity of clinical guidelines and the ad hoc nature of patient data acquisition and entry, which can lead to misinterpretation of patient data and reduced effectiveness in providing rapid and accurate assessments.
Innovation Solution
A CDSS module that groups contiguous nodes in clinical guidelines into care phases, associates patient data with these phases, and determines patient care phase time intervals based on acquisition dates to improve data contextualization and reduce errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the scope of the clinical guideline is enlarged to cover more medical conditions, then the versatility and applicability of the CDSS is improved, but the size and complexity of the guideline increases substantially
Solution Approach 1:
The patent segments the clinical guideline into multiple care phases, where each phase represents a distinct temporal period in patient care (e.g., induction therapy, consolidation therapy, maintenance therapy). This segmentation allows the system to handle diverse medical conditions through modular phase definitions rather than requiring a single monolithic guideline structure, thereby improving versatility while managing complexity through organized decomposition.
Solution Approach 2:
The patent introduces a temporal dimension by organizing guideline nodes into sequential care phases with associated time intervals. This dimensional organization transforms the flat, complex guideline structure into a multi-dimensional framework where nodes are arranged both hierarchically within phases and chronologically across phases, enabling the system to accommodate various medical conditions through time-based progression rather than requiring exhaustive node coverage for each condition.
2Adaptability or versatility
If similar nodes are repeated multiple times in the clinical guideline to handle different clinical scenarios, then the adaptability to different conditions is improved, but the guideline size and data entry requirements increase
Solution Approach 1:
The patent creates care phase templates that can be universally applied across different clinical scenarios. Each care phase definition serves multiple functions: it structures nodes for different treatment types (chemotherapy, radiation, surgery), accommodates various medical conditions, and provides a reusable framework that reduces the need to create separate node structures for each scenario, thereby reducing overall guideline size while maintaining broad adaptability.
3Ease of operation
If patient data is acquired and entered ad hoc based on equipment availability and physician judgment, then the ease of operation is improved, but the accuracy and reliability of the CDSS assessment deteriorates due to temporal context loss
Solution Approach 1:
The patent pre-defines care phase time intervals and establishes the temporal context framework before patient data entry occurs. By having the temporal structure prepared in advance, the system can automatically associate patient data with the correct care phase based on acquisition dates, eliminating the need for complex temporal analysis during data entry while ensuring accurate contextual placement and maintaining assessment reliability.
4Reliability
If the CDSS requires detailed tracking of temporal context for each patient data point to ensure accurate assessment, then the reliability of assessment is improved, but the amount of information required for data entry increases
Solution Approach 1:
The system automatically performs temporal context assignment by comparing patient data acquisition dates with pre-defined care phase time intervals. This self-service mechanism eliminates the need for manual temporal annotation by users, as the system autonomously determines which care phase each data point belongs to, thereby maintaining high assessment accuracy without increasing the burden of data entry.
Data Source
AI summary
A clinical decision support system (CDSS) includes a CDSS module comprising a digital processing device configured to store patient data and a clinical guideline. The clinical guideline comprises connected nodes representing clinical workflow events, actions, or decisions, wherein contiguous groups of the nodes are grouped into care phases. The CDSS module is configured to associate patient data with patient care phases selected from the care phases of the clinical guideline, and determine patient care phase time intervals for the patient care phases based on acquisition date information for the patient data associated with the patient care phases. The selected patient care phase may be a care phase associated with a clinical guideline node associated with the new patient data, or may be a patient care phase that is consistent with the acquisition date for the new patient data.