Database Rule Querying for Automated Medical Product Verification

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Solution Overview

Problem

Existing systems for retrieving and executing conditions stored in databases are inefficient and prone to manual errors, leading to inconsistencies and increased processing time in pharmacovigilance and adverse event reporting.

Innovation Solution

A method for querying and executing rules in a database that automates medical product verification using rule criteria and aliases, reducing manual intervention and ensuring consistent coding through standardized rules, thereby facilitating faster and more accurate case dataset generation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual verification methods are used for medical product data, then flexibility in handling edge cases is maintained, but processing time increases and errors are more likely to occur

Engineering Contradiction:

Improveadverse event processing speedVSAvoidverification accuracy

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system performs self-verification by automatically querying databases using extracted aliases and comparing them against stored medical product data. The automated rule evaluation process independently verifies product information without requiring manual intervention, thereby increasing processing speed while maintaining accuracy through consistent algorithmic application of verification rules.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical verification processes with an automated computational system. The method substitutes human operators with a computer-based rule evaluation mechanism that automatically queries databases, compares aliases against medical product records, and determines fulfillment of verification rules, thereby eliminating manual errors and accelerating processing.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Loss of time

If automated rule execution is implemented, then processing time is reduced and consistency is improved, but system complexity increases

Engineering Contradiction:

Improveprocessing timeVSAvoiddatabase querying system complexity

Core Design Contradiction:

Loss of timeVSDevice complexity

Solution Approach 1:

The verification process is segmented into distinct modular steps: extracting aliases from source files, querying the medical product database using these aliases, evaluating extracted data against stored verification rules, and generating case datasets. This segmentation allows each component to be independently optimized and managed, reducing overall system complexity while maintaining automation benefits.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces an intermediary rule evaluation layer that mediates between the source file data and the database queries. This intermediary component standardizes the interaction by extracting aliases, formulating queries, and evaluating results against predefined rules, thereby simplifying the overall architecture and making the automated system more manageable despite increased functionality.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Manufacturing precision

If standardized verification rules are applied, then coding consistency is improved, but adaptability to unique product scenarios decreases

Engineering Contradiction:

Improvecoding consistencyVSAvoidhandling unique product scenarios

Core Design Contradiction:

Manufacturing precisionVSAdaptability or versatility

Solution Approach 1:

The verification system employs dynamic rule evaluation where the same standardized rules can adapt to different product scenarios through flexible database querying. The system dynamically extracts aliases, queries relevant database records, and evaluates results against verification rules, allowing consistent coding while accommodating unique products through the flexibility of the query and evaluation process rather than rigid fixed logic.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS20260031239A1Systems and Methods for Querying an Executable Condition Stored in a Database

Publication Date: 2026.01.29 VEEVA SYSTEMS INC

AI summary

A method for querying and executing a second rule of a first database includes receiving a source file including first medical product data. The method further includes querying a first database to select a first rule. The first rule includes a first rule criteria. The method further includes determining the first medical product data of the source file does not fulfill the first rule criteria. The method further include querying the first database of the provider computing system to select the second rule. The second rule includes a second rule criteria and a target medial product. The method further includes determining the first medical product data of the source file fulfills the second rule criteria. The method further includes querying a second database to select second medical product data associated with the target medical product. The method further includes generating a case dataset and outputting the case dataset.