From 8 Hours to 45 Minutes: Automating Patient Financial Assistance

The Challenge

A specialty diagnostics company processed hundreds of financial assistance applications every month. Each batch of applications required 8 hours of manual processing: staff had to open each PDF, extract patient demographics and income data, verify eligibility against program criteria, manually enter the information into the billing system, and document the approval or denial.

The manual process was slow and error-prone. At a 94% accuracy rate, roughly 6% of applications were processed incorrectly — leading to patients being billed when they shouldn't have been, or approvals being delayed while errors were corrected. Patients were waiting weeks for answers on their financial assistance applications, creating frustration and sometimes causing them to delay or forgo necessary testing.

The patient services team knew the process needed to change, but the variety of document formats and the complexity of eligibility rules made automation seem difficult. Each assistance program had different criteria, income thresholds, and documentation requirements. A simple rules engine wouldn't be enough.

Our Approach

DxLogic deployed an AI-powered application processing system that handles the full pipeline from document intake to billing system update. OCR reads submitted documents regardless of format — typed PDFs, scanned forms, even photographed documents — and the AI extracts patient demographics, income information, household size, and supporting documentation.

The extracted data is validated against each financial assistance program's specific eligibility criteria using an automated rules engine. The rules engine handles the complexity of multiple programs with different thresholds, documentation requirements, and approval workflows. When the AI is confident in its extraction and the eligibility determination is clear, the application is approved or denied automatically and the result flows directly into the billing system.

For edge cases — illegible documents, missing information, or borderline eligibility — the system flags the application for human review with a clear summary of what it found and what it needs. This means the patient services team only touches the applications that genuinely require human judgment, rather than processing every single one manually.

The Results

Processing time dropped from 8 hours to 45 minutes per batch — a 91% reduction. Manual data entry was completely eliminated, and accuracy improved from 94% to 100% on automated applications. Most importantly, patients now receive answers in days instead of weeks. The patient services team has been redeployed from data entry to actual patient support — helping patients understand their options and navigate the assistance process rather than typing data into forms.