Patient Management Rules Engine for Adaptive Therapy Compliance
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Solution Overview
Problem
Existing systems for determining patient compliance with respiratory pressure therapy devices are costly, time-consuming, and prone to errors due to manual data processing, and they lack the ability to adapt to individual patient improvements over time.
Innovation Solution
A patient management system utilizing a rules engine that assesses therapy data from multiple devices, applies adjustable compliance rules, and provides customizable alerts and actions to improve patient compliance, including variable efficacy thresholds and moving averages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual data processing is used to determine patient compliance, then flexibility in handling individual cases is improved, but time consumption and error rate increase
Solution Approach 1:
The system implements dynamic rule configurations that allow compliance criteria to be adjusted based on individual patient needs and improving circumstances. The rules engine can modify alert thresholds and compliance requirements dynamically, enabling both automated processing and individualized handling without manual intervention.
Solution Approach 2:
The system incorporates feedback mechanisms where patient improvement data is continuously monitored and fed back into the rules engine. This allows the system to learn from individual patient progress and automatically adjust compliance assessments, reducing manual review needs while maintaining flexibility for exceptional cases.
2Productivity
If fixed compliance rules are applied to all patients, then processing efficiency is improved, but ability to account for patient improvement over time deteriorates
Solution Approach 1:
The rules engine transitions from static to dynamic rule application, where compliance thresholds and alert conditions automatically adjust based on patient history and improvement trends. This maintains processing efficiency while adapting to individual patient journeys.
Solution Approach 2:
The system changes key parameters of compliance rules based on patient progress. As patients demonstrate improvement, the rules engine modifies alert thresholds, grace periods, and compliance requirements, allowing fixed-rule efficiency to coexist with adaptive patient management.
3Loss of time
If automated rules engine is implemented, then time consumption is reduced, but system complexity increases
Solution Approach 1:
The rules engine is designed as a universal platform that handles multiple compliance standards, patient types, and device integrations through a single system. This consolidates complexity into one manageable component rather than distributing it across multiple manual processes.
Solution Approach 2:
The system implements self-service capabilities where the rules engine automatically configures and adjusts compliance parameters based on input data, reducing the need for manual system configuration and lowering operational complexity despite the advanced automation.
4Ease of operation
If standardized compliance thresholds are used, then ease of operation is improved, but measurement precision for individual patient needs deteriorates
Solution Approach 1:
The system applies local quality by allowing compliance thresholds to vary at the individual patient level while maintaining standardized operational procedures. The rules engine automatically tailors precision requirements to each patient's specific needs, condition severity, and improvement trajectory without complicating overall system operation.
Data Source
AI summary
A method of patient management including receiving therapy data associated with a plurality of durable medical devices and a first set of patients, and displaying an overview of patient compliance and a plurality of customizable tiles. The overview of patient compliance includes at least the number of patients in the first set of patients, current compliance data, compliance history data, and follow-up data. The plurality of aligned tiles includes at least a title and a plurality of selectable subtitles, each of the plurality of selected subtitles associated with one or more rules. Upon selection of a first selectable subtitle, displaying at least an indication of patients in a second set of patients, wherein the second set of patients is a subset of the first set of patients; upon selection of a first patient, displaying at least all of the rules triggered by the first patient.


