Inference Engine for Proactive Patient Health Monitoring
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Solution Overview
Problem
Current healthcare systems lack a proactive approach to patient care, failing to alert physicians or patients about the need for appointments based on clinical and wellness measures, leading to potential long-term health degradation.
Innovation Solution
A healthcare management system that analyzes data from disparate sources to determine if proactive steps are needed, using an inference engine to correlate patient wellness data with rule sets and send notifications for appointments or other actions, leveraging multiple data sources and communication channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional patient initiative-based appointment scheduling is used, then patients have autonomy in making appointments, but proactive prevention of health degradation is lost
Solution Approach 1:
The system enables self-service by automatically monitoring patient data from multiple sources, evaluating wellness measures against rule sets, and initiating appointment scheduling without requiring patient initiative. The inference engine autonomously detects when intervention is needed based on correlated data patterns.
Solution Approach 2:
The system implements continuous feedback loops by periodically evaluating patient wellness measures, comparing them against predefined rule sets, and automatically triggering notifications or appointments when thresholds are breached. This closed-loop feedback enables proactive intervention before health degradation occurs.
2Reliability
If periodic evaluation against rule sets is implemented, then proactive health monitoring is achieved, but system complexity increases
Solution Approach 1:
The system segments the complex monitoring task into distinct modular components: data collection modules for different sources, an inference engine for rule evaluation, and notification modules for different communication channels. This segmentation allows independent development and maintenance of each component while achieving comprehensive monitoring.
Solution Approach 2:
The inference engine serves as an intermediary layer between raw patient data and clinical decision-making. It correlates data from disparate sources, evaluates wellness measures against rule sets, and translates complex multi-source data into actionable insights, simplifying the overall system architecture.
3Measurement precision
If data from multiple disparate sources is correlated, then comprehensive patient assessment is achieved, but data integration complexity increases
Solution Approach 1:
The inference engine is designed with universal functionality to handle multiple data sources and evaluation criteria through a unified rule set framework. It can correlate diverse patient data types (clinical measurements, wellness surveys, lab results) using the same evaluation logic, eliminating the need for separate processing pipelines for each data source.
4Productivity
If automated appointment scheduling is implemented, then proactive care is enhanced, but loss of patient autonomy occurs
Solution Approach 1:
The system performs preliminary actions by proactively identifying when appointments are needed based on wellness measure evaluation, but structures notifications to preserve patient autonomy. The system prepares and presents scheduling options rather than forcing appointments, allowing patients to maintain control over their care decisions while benefiting from proactive identification of needs.
Data Source
AI summary
Health care monitoring and alerting systems are presented. Contemplated systems include a rule repository storing rules for sending notifications to interested parties regarding a patient's wellness status. An inference engine correlates actual, possibly real-time, patient wellness information with rule sets. If a patient's wellness status satisfies triggering criteria of a rule sets, the inference engine instructs a communication engine to send a notification to interested parties according to the rules set.