Pharmacy Database Structure for Prescription Risk Assessment
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Solution Overview
Problem
Pharmacies face challenges in determining whether to fulfill prescription drug requests due to lack of adequate computerized systems for accessing and managing prescription drug transaction data across different pharmacy systems, especially for new customers or those with unclear prescription histories, and existing solutions fail to provide real-time, usable data for making informed decisions.
Innovation Solution
A pharmacy database structure component that integrates data from multiple retail pharmacy systems, generating a multi-dimensional risk assessment matrix to aid pharmacists in determining whether to fulfill prescription drug requests by categorizing previous requests and transactions, enabling informed decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If pharmacies use separate, non-communicative computer systems for managing prescription data, then each system maintains operational independence and security, but the ability to access comprehensive prescription history across different pharmacies is lost
Solution Approach 1:
The patent implements a centralized prescription monitoring program (PMP) database that acts as an intermediary between independent pharmacy computer systems. This central database receives prescription transaction data from participating pharmacies and makes it accessible to authorized users, enabling comprehensive prescription history access while pharmacies maintain their operational independence and data security protocols.
2Loss of information
If a centralized system aggregates prescription data from multiple pharmacies, then comprehensive prescription history becomes accessible, but system complexity and data integration challenges increase
Solution Approach 1:
The system divides data management responsibilities into segments: individual pharmacies maintain their own transaction data locally, while the centralized PMP database aggregates and organizes this data according to standardized schemas. This segmentation allows comprehensive data collection without requiring complex real-time integration infrastructure at each pharmacy location.
Solution Approach 2:
The centralized database employs a universal data schema that can accommodate prescription data from multiple different pharmacy systems and formats. This multi-functional approach allows the same database structure to handle various data sources and query types, reducing overall system complexity.
3Ease of operation
If real-time prescription data access is implemented across multiple systems, then informed decision-making capability improves, but data transmission and processing time increases
Solution Approach 1:
The system pre-aggregates prescription data in the centralized PMP database as transactions occur at participating pharmacies. This preliminary action ensures that when a pharmacist queries the system, the comprehensive prescription history is already organized and ready for immediate retrieval, minimizing data transmission and processing time during actual use.
Data Source
AI summary
A data structure embodied on a computer-readable medium having a database schema for accessing and managing pharmacy transactions data in a structured query language (SQL) database. The database schema includes a session data schema representing a relational data table for capturing a plurality of sessions for accessing and managing the SQL database and a pharmacy prescription drug transaction results schema representing parameters for relating prescription drug transaction results with requesters, prescribers and the prescription drug. The session data schema and the pharmacy prescription drug transaction results schema used by a pharmacy business logic application to access and manage the pharmacy drug transaction results in the SQL database.