6500
Screening Kits Delivered
8000
Patients Served
80+
Labor Capacity Added
Organization Snapshot
Beacon Health System serves northern Indiana and southwest lower Michigan. Its colorectal cancer screening initiative shows how AI-enabled workflow automation can expand access to preventive care while preserving clinical oversight.
Industry
Healthcare
Region
Northern Indiana
Size
8000+ Associates
Development
Partnership with Magical
Deployment
Targeted Colorectal Cancer Screening Workflow
THE OPPORTUNITY
Thousands of Patients. Limited Administrative Capacity.
Beacon Health had thousands of patients with open colorectal cancer screening care gaps. Reaching them required a series of administrative steps: identifying patients, reviewing eligibility, generating orders, coordinating screening kits, and processing results.
The challenge was both volume and speed. Beacon estimated that completing the workflow manually within a 40-hour week would require more than 80 people working simultaneously.
Each unresolved care gap represented a patient who could miss an opportunity for early detection. Beacon needed to expand screening capacity while maintaining appropriate exclusions, patient choice, and provider oversight.
The goal was to remove administrative friction so more patients could receive timely screening and follow-up.
THE AI SOLUTION
Automate the Workflow. Preserve Clinical Judgment.
Beacon partnered with Magical to automate defined, high-volume administrative steps supporting colorectal cancer screening.
The solution supported:
Processing patient lists and screening eligibility information
Generating screening orders
Coordinating the screening workflow
Moving information into discrete electronic medical record fields
Approximately 8,000 patients were processed and 7,100 orders generated. The automated workflow was completed in approximately 40 hours.
Clinical judgments, exceptions, follow-up, and patient care remained the responsibility of healthcare professionals. AI supported the administrative workflow; it did not diagnose cancer.
RESULTS AND IMPACT
Administrative Capacity Became Access to Care
Expanded screening reach
Approximately 6,500 screening kits were delivered, and more than 2,600 completed kits were returned.
Identified patients needing follow-up
Approximately 10% of returned kits showed positive indications requiring further evaluation. These indications were not cancer diagnoses. Follow-up colonoscopies identified polyps in many dozens of patients.
Supported early cancer detection
The campaign’s first confirmed colon cancer detection involved a patient who otherwise likely would have remained unscreened. Early detection made surgical treatment possible.
Completed high-volume work without a staffing surge
Automation completed the workflow within approximately 40 hours, avoiding the estimated need for more than 80 people working in parallel to meet the same deadline. This comparison reflects additional capacity—not the elimination of 80 permanent positions.
LESSONS LEARNED
Four Principles for Responsible AI Adoption
AI Cannot Fix a Broken Process
The workflow, decision rights, exclusions, and exception paths must be clear before automation.
Deliberate Change Management
Provider and patient communication must be planned intentionally to support understanding and adoption.
Keep Metric Definitions Distinct
Patients processed, orders generated, kits delivered, kits returned, and positive indications measure different stages. Keep those distinctions clear when evaluating results.
Governance Continues After Launch
Responsible AI adoption requires ongoing intake, risk tiering, validation, monitoring, escalation, and adoption measurement.
Ready to Apply AI to Your Business?
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