Patient Adherence Tracking via Prescription Fill Gap Analysis
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Solution Overview
Problem
Patients often fail to adhere to their prescribed medication regimens due to confusing instructions, side effects, and other factors, leading to negative health impacts and unnecessary healthcare visits.
Innovation Solution
A system and method for tracking patient adherence to prescription medication regimens, which involves receiving prescription history data, calculating adherence metrics such as fill gaps and medication possession ratio, and generating reports to identify adherence levels and provide personalized feedback and recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If patients are provided with comprehensive medication regimens for multiple chronic conditions, then treatment effectiveness is improved, but patient adherence deteriorates due to complex instructions and multiple medications
Solution Approach 1:
The system segments the medication regimen into individual components (prescription fills, refills, dosing schedules) and analyzes them separately to identify adherence patterns. This allows complex multi-condition regimens to be broken down into manageable units for tracking and analysis.
Solution Approach 2:
The system provides feedback to both patients and providers by generating adherence reports that highlight compliance patterns, fill gaps, and areas for improvement. This feedback loop enables patients to understand their adherence status and adjust behavior, while providers can modify treatment plans accordingly.
2Reliability
If patients take multiple medications at different times for different conditions, then health outcomes are improved, but measurement of adherence becomes more difficult
Solution Approach 1:
The system uses a universal adherence measurement framework that can track multiple medications, conditions, and time periods through a single integrated approach. The same core methodology (analyzing fill gaps, calculating possession ratios) applies across different medication types and patient scenarios, simplifying measurement complexity.
Solution Approach 2:
The system adds temporal and dimensional layers to adherence measurement by analyzing patterns across multiple time points, conditions, and medication types. This dimensional expansion allows complex adherence behavior to be measured and visualized in a structured manner that reveals underlying patterns.
3Reliability
If patients experience side effects from medications, then treatment efficacy is maintained, but patient compliance deteriorates due to discomfort
Solution Approach 1:
The system enables feedback mechanisms where patients can report side effects and adherence issues, allowing providers to adjust medications or provide support. This feedback loop helps maintain treatment efficacy while addressing compliance problems caused by side effects.
Solution Approach 2:
The system tracks changes in adherence parameters over time and can identify correlations between side effect episodes and compliance changes. This allows for dynamic adjustment of treatment parameters to maintain efficacy while improving patient comfort and compliance.
4Adaptability or versatility
If patients have history of non-compliance, then treatment plans become more complex, but monitoring and management becomes more difficult
Solution Approach 1:
The system segments the monitoring process into distinct analytical components (fill gap analysis, possession ratio calculation, pattern recognition) that can be applied systematically to patients with complex histories. This segmentation reduces overall monitoring complexity by breaking down the analysis into manageable steps.
Solution Approach 2:
The system performs preliminary analysis of patient history and adherence patterns before finalizing treatment plans. By identifying compliance risks and patterns in advance, the system can proactively adjust monitoring strategies and treatment approaches, reducing the complexity of ongoing management.
Data Source
AI summary
The method and system determine and report measures of adherence of patients to prescription medication regimens based upon fill gaps in the prescription history of the patients. The measure of adherence may be the proportion of days covered by the medication. The method and system may receive or access information relating to a patient's medical history, including past prescription medication fills. Fills of both the prescription medication and other medications that may substitute for the prescription medication may be considered in determining patient adherence levels. Upon determining the patient's level of adherence, the system and method may generate a report including the adherence information and associated information, such as a home pharmacy location. The report may include an indication of whether new-to-therapy information should be presented to a patient based on patient adherence levels.