Automated Red Flag Detection for Controlled Substance Dispensing
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Solution Overview
Problem
Current paper-based checklists for pharmacists to identify red flags in dispensing controlled substances are inadequate for large networks, as they cannot coordinate information across multiple pharmacies and are not easily updated to reflect new trends or substances.
Innovation Solution
A computer-implemented system that collects patient information, identifies red flags using machine learning, and prevents dispensing if it would violate regulations, allowing for real-time updates and coordination across a network of pharmacies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a paper-based checklist is used to identify red flags, then the pharmacist can evaluate prescriptions using a simple method, but the system cannot coordinate information across multiple pharmacies and is difficult to update
Solution Approach 1:
The patent replaces the manual paper-based checklist system with an automated computerized system that uses software algorithms and databases to identify red flags. This substitution enables real-time coordination across multiple pharmacies through networked databases and allows dynamic updates of red flag criteria without redistributing physical materials, thereby resolving the contradiction between ease of operation and adaptability
Solution Approach 2:
The patent creates a centralized digital copy of patient and prescription information that can be accessed by multiple pharmacies simultaneously. This digital copying and sharing mechanism enables coordination across the pharmacy network while maintaining a standardized, easily updatable set of red flag criteria that all locations can access in real-time
2Ease of operation
If a paper checklist is used, then the pharmacist can manually evaluate each prescription, but the system cannot easily be updated across a large nationwide network when new red flags are discovered
Solution Approach 1:
The patent replaces the manual distribution and updating of paper checklists with an automated electronic system. The computerized platform allows central administrators to update red flag criteria in a centralized database, which then automatically pushes updates to all connected pharmacies in real-time or near real-time, eliminating the time-consuming process of manually distributing updated papers across a nationwide network
Solution Approach 2:
The patent implements a feedback mechanism where pharmacies can report new red flag patterns or issues, which are then processed and incorporated into the centralized system. This feedback loop enables continuous improvement and rapid updates of the red flag criteria based on emerging trends, with changes automatically propagated across the entire network
3Ease of operation
If a paper-based checklist is used, then the pharmacist can identify red flags through one-on-one interaction, but the system cannot account for red flags that require coordination across multiple pharmacies
Solution Approach 1:
The patent merges the evaluation capabilities of multiple pharmacies into a single coordinated system. By combining patient information, prescription data, and red flag criteria into a centralized database accessible by all locations, the system consolidates information that would otherwise be siloed at individual pharmacies, enabling comprehensive red flag identification that leverages data from the entire network
Solution Approach 2:
The patent creates a universal system that serves multiple pharmacies simultaneously with a single coordinated platform. The centralized database and standardized red flag criteria enable the system to function across diverse locations, allowing information sharing and coordination while maintaining ease of operation through a consistent user interface and process workflow
Data Source
AI summary
Systems and methods for identifying Good Faith Dispensing red flags, as well as evidence to support the validity of a prescriptions for any red flags, associated a patient's attempting to fill a prescription for a controlled substance based on input from pharmacists as well as patient information coordinated across a network of pharmacies are provided herein. An exemplary computer-implemented method may include receiving a request to dispense a medication prescribed to a patient, collecting information associated with the patient, and identifying, based on one or more of the medication and the information associated with the patient, one or more red flags associated with dispensing the medication to the patient. The method may further include determining, based on the one or more identified red flags associated with dispensing the medication to the patient, whether dispensing the medication to the patient would violate any regulations, and if so, preventing the dispensing of the medication to the patient.