Health Data Querying With Hashed Grouping and Dynamic File Output

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Solution Overview

Problem

Existing data querying systems are computationally expensive and inefficient in grouping and sorting large datasets of health data records, leading to increased processing time and resource usage, and lack secure and customizable electronic file generation.

Innovation Solution

The system generates an intermediary group identifier based on data record fields, hashes it using SHA-256 for secure grouping, and dynamically structures electronic files according to user-defined queries, reducing processing power and memory usage.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If traditional data querying systems are used to group and sort large datasets of health data records, then data querying functionality is provided, but processing time and computational cost increase significantly

Engineering Contradiction:

Improvedata querying efficiencyVSAvoidprocessing time

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system pre-processes and cleanses data records before they are stored in the data repository. This preliminary action includes standardizing data formats, removing duplicates, and preparing data for efficient querying, which significantly reduces processing time when queries are executed later.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system divides the data repository into manageable segments or partitions based on data characteristics. This segmentation allows the querying system to process only relevant portions of the data rather than scanning entire datasets, thereby reducing computational cost and processing time.

Inventive Principle:

Principle #1Segmentation

2Productivity

If data records are cleaned and grouped manually or using traditional methods, then data organization is achieved, but processing power and memory usage increase

Engineering Contradiction:

Improvedata processing efficiencyVSAvoidprocessing power and memory usage

Core Design Contradiction:

ProductivityVSUse of energy by moving object

Solution Approach 1:

The system automatically cleanses, standardizes, and groups data records without requiring manual intervention or complex computational processes. The automated data cleaning and grouping algorithms efficiently organize data using minimal processing power and memory, eliminating the need for resource-intensive manual operations.

Inventive Principle:

Principle #25Self-service

3Adaptability or versatility

If electronic files are generated without customizable structuring, then file generation is simple, but adaptability to user-specific query requirements is limited

Engineering Contradiction:

Improvecustomizable file generationVSAvoidelectronic file structuring complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system dynamically structures electronic files based on user-defined query parameters and requirements. The file structure adapts automatically to match the specific data fields, formats, and organization needed for each query, providing versatility without requiring complex manual configuration or pre-defined templates.

Inventive Principle:

Principle #15Dynamics

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This approach significantly reduces processing time and resource usage, enhances data security, and allows for efficient, customizable electronic file generation, improving system uptime and productivity.

Implementation Method 1

The system generates an intermediary group identifier based on data record fields, hashes it using SHA-256 for secure grouping

Methodology Applied

Scientific EffectSHA-256 hashing:

Data Source

PatentUS12541798B1Systems and methods for querying data records of a repository

Publication Date: 2026.02.03 VEEVA SYSTEMS INC

AI summary

A method for querying one or more combined data records of a repository including generating a data record request and providing the data record request to one or more covered entity computing systems. The method includes receiving and cleaning the data records. The method includes assigning cleaned data records to a group. The method includes generating an attribute based on the cleaned data records of the group and adding the attribute to the cleaned data records of the group to generate multiple combined data records. The method includes storing the combined data records in the repository. The method includes receiving a query including a configuration property and executing the query on the data repository to select each combined data record from the data repository which matches the configuration property of the query. The method includes generating an electronic file including the selected combined data records and outputting the electronic file.