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Clinical Trial Eligibility Screener

Automated patient screening system that evaluates medical criteria to determine clinical trial eligibility based on multiple health factors.

Solution

This eligibility screening system streamlines the clinical trial recruitment process by automating patient qualification assessment. It evaluates candidates against six key medical criteria: diagnosis type, disease stage, current medications, age, treatment history, and comorbidities. The system flags patients with qualifying diagnoses (breast, lung, or colorectal cancer) while excluding those with advanced stage IV disease.

The screening tool identifies medication conflicts that could compromise trial outcomes, particularly immunosuppressants, anticancer agents, and corticosteroids. Age verification ensures patients fall within the 18-75 year trial parameters. Treatment history analysis prevents enrollment of heavily pre-treated patients, limiting prior treatments to two or fewer. The system also screens for disqualifying comorbidities including autoimmune disorders, heart failure, and uncontrolled diabetes, providing detailed justification for each eligibility determination.

How it works

The eligibility assessment follows this process:

Input Collection: Captures comprehensive patient data including diagnosis, disease stage, current medications, age, prior treatments, and comorbidities.
Diagnosis Verification: Validates if the patient's condition matches targeted cancer types (breast, lung, colorectal).
Stage Evaluation: Confirms disease progression is within acceptable parameters (stages I-III).
Medication Screening: Identifies contraindicated medications that would exclude participation.
Age Validation: Verifies patient age falls within protocol-defined range.
Treatment History: Ensures limited prior therapy exposure (≤2 treatments).
Comorbidity Assessment: Screens for exclusionary concurrent medical conditions.
Eligibility Determination: Aggregates all criteria results to produce a final eligibility decision with detailed reasoning.

Where teams use it

Clinical research organizations
Pharmaceutical trial management
Hospital research departments
Oncology centers
Medical research institutions
Patient recruitment services

Inside the decision model

Clinical Trial Eligibility Screener ships as a JDM decision graph with 8 nodes, 6 decision tables and 14 rules. Download it, load it into GoRules, and run it as-is on Zen Engine.

Decision graph8 nodes · read-only

input patienttable diagnosisEligibilitytable diseaseStageEligibilitytable medicationEligibilitytable ageEligibilitytable priorTreatmentEligibilitytable comorbidityEligibilityexpression eligibilitySummary

Patient

input

One patient object carries all six screened attributes, diagnosis, diseaseStage, currentMedications, age, priorTreatments, and comorbidities, and the graph fans it out to six criterion checks that run in parallel before the summary merges their flags.

Sample requestJSON

{
  "patient": {
    "id": "P67890",
    "name": "John Smith",
    "age": 68,
    "diagnosis": "lung_cancer",
    "diseaseStage": "IV",
    "currentMedications": [
      "immunosuppressants",
      "albuterol",
      "omeprazole"
    ],
    "priorTreatments": 3,
    "comorbidities": [
      "autoimmune_disease",
      "COPD"
    ],
    "lastLabResults": {
      "wbc": 3.8,
      "hgb": 10.9,
      "plt": 150,
      "creatinine": 1.2
    }
  }
}

Diagnosis Eligibility

table

Qualifying cancers are enumerated directly: a patient.diagnosis of 'breast_cancer', 'lung_cancer', or 'colorectal_cancer' sets eligibility.diagnosis.flag true, and anything else falls to the false row with 'Diagnosis does not match trial criteria'. Enumerating target indications is exactly how oncology protocols define their study population, so this list is the first thing a protocol amendment would touch.