Differential Diagnoses Generator for Clinical Decision Support

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Solution Overview

Problem

Current diagnostic tools lack the ability to efficiently generate a short list of high probability differential diagnoses based on multiple patient signs, symptoms, and clinical findings, leading to increased healthcare costs and diagnostic errors, especially for novice physicians.

Innovation Solution

A system and method that analyzes patient data to generate a ranked list of high and low probability differential diagnoses, utilizing a computer-based system with modules for data input, disease database querying, and output reporting to assist healthcare providers in diagnosing patient conditions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If a physician considers all available differential diagnoses linked to a given sign, symptom or finding, then diagnostic completeness is improved, but time and healthcare costs increase

Engineering Contradiction:

Improvediagnostic completenessVSAvoidtime for patient encounter

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system extracts and filters only the most relevant differential diagnoses from the complete list of possible conditions. By using epidemiological data and clinical guidelines, it extracts the top-ranked diagnoses that are most likely to be correct, eliminating the need to consider all possible differentials and thus reducing time while maintaining diagnostic quality.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system changes the parameter of diagnostic approach from considering all possible diagnoses to considering only those ranked by probability. It transforms the complete list of differentials into a prioritized list based on epidemiological factors, patient demographics, and clinical presentation, allowing physicians to focus on the most likely diagnoses first.

Inventive Principle:

Principle #35Parameter changes

2Reliability

If a physician generates multiple differential diagnoses, then diagnostic accuracy is improved, but the complexity of diagnostic reasoning increases

Engineering Contradiction:

Improvediagnostic accuracyVSAvoidcomplexity of diagnostic reasoning

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system provides feedback to the physician by presenting a ranked list of differential diagnoses based on epidemiological data and clinical guidelines. This feedback mechanism helps physicians structure their reasoning process and validates their diagnostic hypotheses against established medical knowledge, reducing the cognitive complexity of generating multiple differentials.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system performs preliminary ranking of differential diagnoses before the physician needs to make a diagnostic decision. By pre-ordering the list of possible diagnoses based on probability and epidemiology, it eliminates the need for the physician to independently rank multiple differentials, thus reducing the complexity of diagnostic reasoning while maintaining accuracy.

Inventive Principle:

Principle #10Preliminary action

3Ease of operation

If novice physicians generate hypotheses, then diagnostic process is initiated, but quality and reliability of hypotheses are reduced

Engineering Contradiction:

Improveease of hypothesis generationVSAvoidquality of hypotheses

Core Design Contradiction:

Ease of operationVSReliability

Solution Approach 1:

The system provides self-service by automatically generating and ranking differential diagnoses based on the patient's presenting symptoms and epidemiological data. This eliminates the need for novice physicians to independently generate quality hypotheses, as the system does this for them using its built-in knowledge base and ranking algorithms.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system acts as an intermediary between the novice physician and the complex task of generating accurate differential diagnoses. It mediates by providing structured, epidemiologically-based hypothesis generation that bridges the gap between lack of experience and the need for high-quality diagnostic reasoning, thereby improving hypothesis quality without increasing operational complexity.

Inventive Principle:

Principle #24Intermediary (Mediator)

4Adaptability or versatility

If all disease conditions are listed, then comprehensive diagnostic reference is provided, but rare and uncommon diseases increase the list length

Engineering Contradiction:

Improvecomprehensive diagnostic referenceVSAvoidnumber of differential diagnoses

Core Design Contradiction:

Adaptability or versatilityVSQuantity of substance

Solution Approach 1:

The system applies local quality by tailoring the list of differential diagnoses to the specific patient presentation and epidemiological context. Instead of providing a generic comprehensive list, it locally adapts the reference to include only the most relevant conditions for that specific patient, thereby reducing the number of differentials while maintaining comprehensiveness for the given clinical scenario.

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS9536051B1High probability differential diagnoses generator

Publication Date: 2017.01.03 KABIR AZAD ALAMGIR

AI summary

A method for performing an automated medical diagnosis of a patient based upon a patient's signs/symptoms/findings which are input by a user/heath care provider and then further analyzed to then output a listing of high probability differential diagnoses/diseases and a low probability differential diagnoses/diseases that the patient may have. This analysis assists health care providers in providing a fast and early indication of potential conditions based upon an analysis of a patient's signs/symptoms/findings.