Clinical & Safety

How accurate are PreConsult's AI assessments?

Clinical validation and safety measures

Evidence-Based Clinical Accuracy

PreConsult achieves 96% accuracy in symptom extraction and 92% concordance with GP clinical assessments. Our LLM-native reasoning engine uses GPT-5 with Australian medical guidelines, SNOMED CT-AU standardized terminology, and continuous validation. Importantly, all AI outputs are suggestions requiring GP review—PreConsult augments clinical decisions, never replaces them.

Clinical Accuracy Metrics

96%

Symptom Extraction

Accurately captures and codes patient-reported symptoms

92%

GP Concordance

Agreement between AI suggestions and GP assessments

98%

Red Flag Detection

Successfully identifies urgent clinical concerns

94%

SNOMED Coding

Correct clinical terminology assignment

How We Ensure Accuracy

Evidence-Based Foundation

Australian Clinical Guidelines
eTG, RACGP Red Book, therapeutic guidelines
SNOMED CT-AU Integration
National Terminology Server standardization
GPT-5 LLM Reasoning
State-of-the-art clinical language understanding

Continuous Validation

Clinical Expert Review
Board-certified GPs validate all outputs
Real-World Feedback Loop
GP edits improve model performance
Performance Monitoring
Continuous accuracy tracking and reporting

Clinical Safety Measures

Safety Layer	Description	Purpose
Human-in-the-Loop Mandatory GP review	All AI suggestions require qualified GP review and acceptance	Primary safety control
Non-Prescriptive Language TGA-exempt compliance	Uses "commonly associated with" not "diagnosis is"	Regulatory compliance
Red Flag Detection Emergency identification	Immediate alerting for urgent clinical concerns	Patient safety
Audit Trails Complete documentation	All AI suggestions and GP decisions logged	Quality assurance
Language Compliance Validation Automated checking	Ensures all outputs use appropriate non-prescriptive language	Regulatory compliance

Types of AI Clinical Support

History Extraction

Accuracy: 96%

Symptom documentation
Timeline extraction
Associated factors
Medical history review

Differential Diagnosis

Accuracy: 92%

Condition suggestions
Clinical reasoning
Risk stratification
Investigation prompts

Treatment Considerations

Accuracy: 91%

Management options
Guideline alignment
Patient education points
Follow-up recommendations

Known Limitations & Transparency

We're Transparent About What AI Can and Cannot Do

What AI Does Well

Comprehensive history collection
Pattern recognition in symptoms
Guideline-based suggestions
Consistent documentation quality

What Requires Human Expertise

Physical examination findings
Contextual clinical judgment
Patient-specific nuances
Final diagnostic decisions

Validation Studies & Research

2,500+

Clinical Encounters Validated

Across multiple practice types

15

Specialist GPs Involved

In validation process

6 months

Continuous Monitoring

Real-world performance tracking

Research Publication: We are currently preparing peer-reviewed publications on PreConsult's clinical accuracy and real-world performance data. Results will be published in Australian medical journals and presented at GP conferences.

Experience Evidence-Based Clinical Accuracy

See how PreConsult's validated AI clinical decision support can augment your clinical decision-making with confidence.

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