Auditable Asset Tracking Model for Opioid Pill Counting
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Solution Overview
Problem
Current pill counting methods for opioid use disorder management are labor-intensive, consuming significant time for medical professionals and lacking efficient automation, which diverts attention from other critical activities and does not adequately address diversion control.
Innovation Solution
A system utilizing a user interface with image-based pill counting facilitated by machine learning algorithms for object segmentation and verification, enabling remote and automated tracking of pill counts, with encrypted data transmission to ensure patient privacy and compliance with regulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional in-person or video call pill counting is used, then patient verification is achieved, but medical professional time is significantly consumed
Solution Approach 1:
The patient performs the pill counting themselves by capturing an image of their pills using their mobile device camera and submitting it through the application. The system then automatically verifies the count using machine learning image recognition technology, eliminating the need for the medical professional to manually count or supervise the counting process in real-time.
Solution Approach 2:
The manual mechanical process of counting pills by hand during in-person or video consultations is replaced with an automated image-based system. The mobile application captures images of the pills, and machine learning algorithms automatically analyze and verify the pill count, substituting human manual counting with automated optical recognition.
2Productivity
If automated image-based pill counting is implemented, then medical professional time is reduced, but system complexity increases
Solution Approach 1:
The mobile application serves multiple functions: it schedules pill counts, captures images of pills, automatically counts pills using machine learning, stores records securely, and enables communication between patients and medical professionals. This multi-functionality consolidates what would otherwise require separate systems into a single unified platform.
Solution Approach 2:
The system introduces a secure cloud-based server as an intermediary between the patient's mobile device and the medical professional's system. This server handles image processing, machine learning analysis, data storage, and verification, shielding the complexity of these operations from both the patient and medical professional while maintaining simple user interfaces.
3Reliability
If manual pill counting records are kept, then compliance tracking is possible, but audit readiness is compromised
Solution Approach 1:
The system creates digital copies of the pill counting process through captured images and automatically generated records. Each pill count is documented with a timestamped image, patient certification, and system-verified count, creating an immutable digital audit trail that can be easily retrieved and reviewed by regulatory authorities.
Solution Approach 2:
The system provides immediate feedback to both patient and medical professional regarding pill count verification results. The automated verification process compares the submitted image against expected pill quantities, notifies the patient of any discrepancies, and alerts the medical professional to potential compliance issues, enabling real-time compliance monitoring.
Data Source
AI summary
Techniques for tracking a progression of a therapeutic procedure that is performed by a patient are disclosed. A notification is received from a server computer system. This notification relates to a tracking process designed to monitor a progress of the patient in performing the therapeutic procedure. After receipt of the notification, a UI is displayed. This UI has a particular visual layout that is designed to facilitate the tracking process. In response to a particular field being selected within the UI, a secret key that de-identifies the patient is accessed. The accessed secret key and a specific image are then encrypted. As a consequence, encrypted data is generated. The encrypted data is then transmitted to the server computer system.