Build a Multi-Center Trial Recruitment Diversity and Inclusion Modeler
Analyze synthetic cohort records across simulated medical centers to project demographic representation in clinical trial recruitment. Formulate recruitment adjustments to address severe demographic underrepresentation.
What you are building
The core problem, expected build, and operating context for this challenge.
Analyze synthetic cohort records across simulated medical centers to project demographic representation in clinical trial recruitment. Formulate recruitment adjustments to address severe demographic underrepresentation.
Trial Equity and Feasibility Officer
Ingest synthetic multi-center participant records with geographic and demographic covariates.
Compute site-specific eligibility yields against specified trial inclusion criteria.
Calculate disparity indices across age, sex, and ethnicity brackets against regional baselines.
Deliver a feasibility adjustment report with site-level cohort rebalancing suggestions.
Multi-site demographic breakdown dashboard with disparity index gauges and scenario simulation toggles.
Construct mock demographic records in normalized CSV or JSON format representing five simulated research hospital sites. Starter examples below are synthetic. They are not downloaded records.
HL7 FHIR overview Employ FHIR ResearchStudy and Group demographic structure patterns to define cohort stratification criteria.
anthropic-claude, pandas, scipy. anthropic-claude processes complex demographic disparity summaries to synthesize coherent site rebalancing strategies. Hosted Claude API for structured analytical summarization and protocol sensitivity review.
Submit runnable source, pinned dependencies, setup commands, a working interface, example outputs, and a recorded end-to-end demo. Include tests and an action log.
Ingests synthetic multi-site cohort files and validates demographic schema fields.
Computes demographic representation ratios relative to target population distributions.
Flags sites where inclusion yield drops below predetermined equity thresholds.
Outputs structured JSON containing disparity metrics and site-specific recommendations.
```json [ { "input": { "study_id": "DIV-2026-T1", "target_distribution": { "group_a": 0.5, "group_b": 0.5 }, "site_records": [ { "site": "Site_North", "group": "group_a", "eligible": true }, { "site": "Site_North", "group": "group_a", "eligible": true }, { "site": "Site_North", "group": "group_b", "eligible": false }, { "site": "Site_South", "group": "group_b", "eligible": true } ] }, "expected_output": { "study_id": "DIV-2026-T1", "total_eligible": 3, "observed_distribution": { "group_a": 0.67, "group_b": 0.33 }, "disparity_detected": true, "priority_site_for_outreach": "Site_North" } }, { "input": { "study_id": "DIV-2026-T2", "target_distribution": { "group_a": 0.5, "group_b": 0.5 }, "site_records": [] }, "expected_output": { "study_id": "DIV-2026-T2", "total_eligible": 0, "observed_distribution": {}, "disparity_detected": false, "priority_site_for_outreach": "none" } } ] ```
Research protocol planning system using synthetic demographics; makes no individual clinical care decisions. Use mock external writes. Require human review before any real deployment.
Participation guide
Research protocol planning system using synthetic demographics; makes no individual clinical care decisions. Use mock external writes and human review.
How work is evaluated
Ingests synthetic multi-site cohort files and validates demographic schema fields. Computes demographic representation ratios relative to target population distributions. Flags sites where inclusion yield drops below predetermined equity thresholds. Outputs structured JSON containing disparity metrics and site-specific recommendations.
Runnable source, pinned dependencies, setup commands, working interface, example outputs, recorded demo, tests, and action logs.
Challenge datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
Complete workflow
Ingest synthetic multi-center participant records with geographic and demographic covariates. Compute site-specific eligibility yields against specified trial inclusion criteria. Calculate disparity indices across age, sex, and ethnicity brackets against regional baselines. Deliver a feasibility adjustment report with site-level cohort rebalancing suggestions.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Correctness and evidence
Ingests synthetic multi-site cohort files and validates demographic schema fields. Computes demographic representation ratios relative to target population distributions. Flags sites where inclusion yield drops below predetermined equity thresholds. Outputs structured JSON containing disparity metrics and site-specific recommendations.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Review interface
Multi-site demographic breakdown dashboard with disparity index gauges and scenario simulation toggles.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Safe execution
Research protocol planning system using synthetic demographics; makes no individual clinical care decisions.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Ingest synthetic multi-center participant records with geographic and demographic covariates.
Compute site-specific eligibility yields against specified trial inclusion criteria.
Calculate disparity indices across age, sex, and ethnicity brackets against regional baselines.
Deliver a feasibility adjustment report with site-level cohort rebalancing suggestions.
Reference links and supporting material
Construct mock demographic records in normalized CSV or JSON format representing five simulated research hospital sites. Supplied starter examples are synthetic, not source extracts.
Challenge setup
Configuration summary for this challenge.
Challenge input
Input details are not configured.
Anthropic Claude
LLM for code generation & more
Evaluated output
No output checks are configured.
- Ingest synthetic multi-center participant records with geographic and demographic covariates. Compute site-...
- Ingests synthetic multi-site cohort files and validates demographic schema fields. Computes demographic rep...
- Multi-site demographic breakdown dashboard with disparity index gauges and scenario simulation toggles.
- 2 public reference cases
- 1 configured tool
Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.
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Configured tools
- Anthropic Claude · Optional
Evaluation contract
- Complete workflow · Weight 40
- Correctness and evidence · Weight 30
- Review interface · Weight 20
- Safe execution · Weight 10
Reference cases
- 2 public reference cases
Workflow tasks
No workflow tasks are configured.
Recipe freeze marker
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