Diabetes Treatment Guidance Using Single-Draw Biomarker Integration
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Solution Overview
Problem
Conventional methods for devising diabetes treatment regimens are unsatisfactory as they lack a comprehensive, integrated approach to assess multi-dimensional patient conditions and provide personalized treatment plans, relying on piecemeal data acquisition and limited expert knowledge, leading to suboptimal therapeutic outcomes.
Innovation Solution
A system and method that integrates biochemical and demographic data from a single blood draw to generate a personalized treatment plan by mapping patient patterns to decision rules, linking them to a database of anti-diabetic drug classes, and generating a report that prioritizes intervention classes based on these patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional piecemeal data acquisition methods are used, then the simplicity of individual tests is maintained, but the comprehensiveness of patient condition assessment deteriorates
Solution Approach 1:
The patent combines multiple separate biochemical tests (A1C, renal function, Adiponectin, C-peptide, hsCRP, etc.) into a single integrated assessment system that processes all these tests together to provide a comprehensive view of patient condition, thereby reducing information loss while managing complexity through systematic integration
Solution Approach 2:
The integrated assessment system serves multiple functions simultaneously: it evaluates metabolic pathophysiology, assesses cardiovascular risk, determines treatment stage, and guides therapy selection, making a single system capable of handling diverse assessment needs that previously required multiple separate evaluation processes
2Measurement precision
If multiple separate tests are ordered at different time points, then the depth of specific condition analysis is improved, but the integration of overall patient picture deteriorates
Solution Approach 1:
The system performs preliminary integration of all biochemical test results before treatment decisions are made, creating a unified patient condition profile that combines precise measurements from multiple tests into a coherent overall picture that guides subsequent treatment planning
Solution Approach 2:
The patent introduces an intermediary integrated assessment layer that processes and synthesizes data from multiple precise measurements (A1C, renal function, Adiponectin, C-peptide, hsCRP, etc.) into a unified condition evaluation, acting as a mediator between individual test results and treatment decisions
3Ease of operation
If limited expert knowledge and database are used, then the simplicity of treatment selection is maintained, but the capability to handle complex anti-diabetic drug data deteriorates
Solution Approach 1:
The system implements self-service through automated algorithms that independently process patient data, evaluate treatment options, and generate recommended regimens without requiring manual expert analysis, thereby maintaining ease of operation while enhancing the capability to handle complex drug data through computational power
Solution Approach 2:
The patent replaces manual expert knowledge and mechanical review processes with automated computational systems that use algorithms to analyze complex anti-diabetic drug data, substitute human cognitive limitations with machine processing capabilities while maintaining user-friendly operation
4Adaptability or versatility
If over 200 alternate regimens are considered, then the adaptability of treatment options is improved, but the complexity of clinician decision-making deteriorates
Solution Approach 1:
The patent segments the overwhelming number of treatment options (over 200 alternate regimens) into structured categories and hierarchies, organizing them by drug class, treatment stage, and patient condition profiles, making the complex information manageable while preserving adaptability through systematic classification
Data Source
AI summary
Systems and methods are provided for providing diabetes patient treatment guidance for a patient in which a biochemical data set is obtained. The biochemical data set comprises test results from a single blood draw of the patient including at least three measurements selected from the set: a high-sensitivity c-reactive protein test, an adiponectin level test, an intact proinsulin level test, an insulin level test, a C-peptide test, a HbA1c test, and an eGFR level test. A demographic data set for the patient is also obtained that comprises the patient's gender and diabetes stage. The biochemical data set and demographic data set is run against one or more rules to determine a first patient therapy pattern. Then, a report is prepared based on an identity of the first therapy patient pattern. The report sets priorities among intervention classes for the patient based on the identity of the first patient pattern.