Dynamic Medical Algorithm Updates for Point-of-Care Risk Assessment
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Solution Overview
Problem
Current electronic medical records systems lack a convenient method for incorporating diagnostic data into medical algorithms and updating them as new information becomes available, making it burdensome for healthcare providers to assess patient risk and disease states effectively.
Innovation Solution
A system that integrates a central computer with a database for storing diagnostic data and medical algorithms, allowing practitioners to assess patient risk through a user-friendly interface, and optionally includes features for managing patient records, billing, and scheduling, enabling rapid updates without major software upgrades.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If electronic medical records systems are implemented to store and process diagnostic data, then information processing and retrieval are facilitated, but the systems lack the capability to rapidly incorporate diagnostic data into medical algorithms and update them as new information becomes available
Solution Approach 1:
The system implements dynamic algorithm updates by allowing medical algorithms to be modified and reloaded without requiring major software upgrades. The architecture separates algorithm logic from the core system, enabling flexible adaptation as new medical information becomes available while maintaining operational efficiency.
Solution Approach 2:
The system divides medical algorithms into discrete, manageable components that can be independently updated and applied to patient data. This segmentation allows specific algorithmic elements to be modified based on new research findings without reworking the entire system, resolving the contradiction between processing efficiency and adaptability.
2Measurement precision
If medical algorithms are integrated into electronic records systems, then disease state assessment is improved, but the complexity of the system increases making it burdensome for healthcare providers
Solution Approach 1:
The system introduces an intermediary layer between the complex algorithmic processing and the healthcare provider interface. This intermediary automatically handles the computation of disease states from diagnostic data, presenting simplified results to providers while maintaining high assessment accuracy through sophisticated underlying algorithms.
Solution Approach 2:
The system performs automatic risk assessment and disease state evaluation without requiring manual intervention from healthcare providers. The algorithms autonomously process diagnostic data and generate assessments, reducing the burden on providers while maintaining high measurement precision through continuous computational analysis.
3Reliability
If comprehensive patient data is collected and stored, then complete risk assessment is enabled, but the workload for managing and updating patient records increases
Solution Approach 1:
The system continuously processes and analyzes patient data as it is collected, rather than requiring batch processing or manual review. Diagnostic measurements are automatically incorporated into risk algorithms in real-time, ensuring complete risk assessment without increasing provider workload, as the system performs continuous evaluation autonomously.
Solution Approach 2:
The system provides automatic feedback loops where diagnostic data collection triggers immediate risk reassessment. This feedback mechanism ensures that complete patient data is continuously utilized for accurate risk assessment while automating the management process, eliminating the need for additional manual time investment by healthcare providers.
Data Source
AI summary
In a further aspect of the invention, the calculated results may be communicated as a graphical output 196, such as is illustrated in FIG. 27. The graphical output 196 may be accessed by pressing a graph report button 198 on the report output dialog box (FIG. 26). The graphical output 196 is useful to further illustrate to the physician and the patient the changes in the calculated risk value over time, and in relation to the cholesterol levels. The graphical output 196 is also useful as a further tool in enabling a patient to understand the relationship between their health habits and the associated risk factor, and in encouraging the patient to participate in their own medical decision making.