UC52: Genetic Counseling Pre-Screen

The Problem

Genetic counselors are scarce (1 counselor per ~100,000 people in the US). Patients with hereditary cancer risk (BRCA mutations, Lynch syndrome, familial hypercholesterolemia) benefit from genetic counseling, but long wait times and limited access prevent timely identification. AI-powered pre-screening can identify high-risk patients for expedited counselor referral.

What the Agent Does

Patient or provider completes family history questionnaire in EHR (parents, siblings, children diagnoses and ages at diagnosis)
Agent applies validated genetic risk assessment models (Tyrer-Cuzick for breast cancer, PREMM5 for Lynch syndrome, etc.)
Calculates hereditary risk score: if >20% lifetime BRCA risk or >10% Lynch risk, flags for genetic counselor referral
Pre-screen summary identifies specific risk factors: "Multiple early-onset breast cancers in family; BRCA testing recommended"
Generates counselor referral with clinical context; expedites scheduling
Provides patient with education: what BRCA/Lynch mutations mean, testing process, privacy protections (GINA)
Tracks testing outcomes: confirms genetic testing ordered, results received, interpretation documented

Data Requirements

Primary Data Sources: Family history questionnaire (parents, siblings, children diagnoses and ages), personal cancer/health history, genetic risk models (Tyrer-Cuzick, PREMM5, InVitae model), patient demographics (ethnicity, age)
Classification: PHI/PII (family history, genetic risk assessment)
Quality Metrics: Risk stratification accuracy >95% (validated against genetic counselor assessment); sensitivity for hereditary cancer >90%; specificity >75%
Complexity: Medium-High (genetic risk model algorithms, family history interpretation)
Systems: Epic EHR, InVitae genetic counseling platform

Score Breakdown

Criterion	Weight	Score (1-5)	Weighted
Time Recaptured	15%	4	0.60
Error Reduction	10%	3	0.30
Cost Avoidance	10%	3	0.30
Strategic Leverage	5%	3	0.15
Data Availability	15%	3	0.45
Process Clarity	15%	3	0.45
Ease of Implementation	10%	3	0.30
Fallback Available	10%	3	0.30
Audience (Int/Ext)	10%	4	0.40
Composite	100%		3.30

Why It Scores Well

Clinical Precision: Identifies high-risk patients for counseling; improves cancer prevention through early screening
Access Improvement: Triages limited counselor resources to highest-risk patients
Regulatory Fit: GINA protects against genetic discrimination; no novel regulatory barriers
Evidence Base: Risk models validated in oncology literature
Scalability: Can screen entire cancer patient population

Regulatory Alignment

GINA (Genetic Information Nondiscrimination Act): Prohibits discrimination based on genetic information; agent must not disclose genetic status to insurers/employers without patient consent
FDA: Genetic risk assessment tool may require 510(k) review depending on autonomy. Advisory-only risk stratification typically exempt.
State Genetic Testing Laws: Some states require specific informed consent for genetic testing; agent must not recommend testing without appropriate counseling
HIPAA: Family history is PHI; genetic risk information is sensitive
Genetic Discrimination Laws: Some states have additional genetic privacy protections

Sprint Factory Fit

2 to 3 sprints (family history questionnaire design, genetic risk model integration, counselor referral workflow, GINA compliance review)

Sprints Required: 2 to 3 sprints (family history questionnaire design, genetic risk model integration, counselor referral workflow, GINA compliance review)
Timeline: 4 to 6 weeks from requirements to pilot
Governance: Genetic counselor and oncology leader approval of risk models; validate accuracy in first 50 assessments
Success Metrics: Risk stratification accuracy >95%; sensitivity >90%; genetic counselor referral time reduction >50%; testing uptake in identified high-risk patients >60%

Comparable Implementations

Deploy This Use Case with the Sprint Factory

From zero to a governed, production agent in 6 weeks.

Sprint Factory Schedule a Briefing

Related Use Cases

On-Demand Clinical

AI Clinical Scribe & Note Generator

Score: 4.3/5.0

On-Demand Clinical

Medical Knowledge Base Search

Score: 3.75/5.0

On-Demand Clinical

Patient History Summary ("Highlight Reel")

Score: 3.6/5.0