Internal Platform Modernization
Quality Databank
Quality Data Bank is a desktop application designed to centralize and automate medical classification code assignment across two key workflows: Authority Monitoring and Complaint Databank.
Problem
Manual & Inconsistent Classification
Classification codes were previously assigned manually in local Excel files. This led to inconsistencies, version control issues, and reliance on individual interpretation when mapping device and patient problems.
Fragmented Data Across Workflows
Authority monitoring and complaint tracking were managed separately, making it difficult to compare trends across datasets. Because coding was not standardized, combining the data for analysis required manual cleanup.
Limited Reporting & Visualization
Without consistent classification logic across both workflows, reliable cross-sectional dashboards were not possible. Manual processes restricted scalable data visualization and data-driven decisions.
The project progressed from analyzing a manual process to delivering an automated solution. Improving clarity, reducing friction, and increasing visibility were central to enhancing the overall user experience
Research & Planning
I reviewed existing Excel workflows and identified gaps in medical classification code consistency and data structure. I worked with stakeholders to define standardized mapping rules and determine how records should be stored in SharePoint. Reporting and dashboard needs were considered from the start.
Design & Prototyping
I structured the application into three primary user experiences: Authority Monitoring, Complaint Data Bank, and File Status Tracking. I designed validation states for CSV uploads, guided form patterns for complaint entry, and a clear status interface for tracking file processing. The UX focused on clarity, transparency, and reducing ambiguity.
Development & Implementation
I built automated CSV ingestion that extracts uploaded records, assigns standardized classification codes, and writes structured entries to SharePoint. A file status screen tracks each upload as Pending, Completed, or Failed. In the complaint module, dynamic form logic generates classification codes once required specifications are selected.
Testing & Optimization
I validated edge cases across multiple product categories and tested CSV formatting variations. Error handling was refined to make issues easy to resolve. Performance was optimized for bulk uploads and frequent complaint submissions.
The final solution combines CSV-based authority monitoring, guided complaint intake, and file status tracking into a single, consistent system.
Automated Authority Monitoring Intake
Users select a product category and upload a CSV file. The system extracts device and patient problem data, automatically assigns standardized classification codes, and stores structured records in SharePoint.
Structured Complaint Entry
A simplified entry form standardizes complaint submissions. Built-in validation ensures required fields are completed while maintaining an intuitive experience. All records align with the same classification structure used in Authority Monitoring.
Specification-Based Classification Logic
Within the complaint module, users can select up to four specification fields, with at least two required. Once two or more are selected, the classification code dynamically pre-populates based on predefined logic.
File Processing Status Dashboard
A dedicated file status screen provides visibility into uploaded CSV files. Users can see whether a file is Pending (still extracting and assigning codes), Completed, or Failed. This transparency improves trust in the system and allows users to quickly identify and resolve issues.
By automating classification and centralizing records in SharePoint, the team moved away from manual Excel tracking to a more scalable workflow. The data is now structured, easier to analyze, and ready for reporting.
Enabled Cross-Sectional Data Visualization
Because classification codes are assigned consistently across authority and complaint records, the data can now be visualized together in dashboards. Trends across product categories and problem types can be analyzed with confidence.
Stronger Data-Driven Decisions
Quality leaders can confidently identify recurring trends and prioritize corrective actions using consistent, structured data. Standardized classification codes now serve as the foundation for reporting and informed database decisions.
Reduced Manual Effort & Improved Accuracy
Automation significantly reduced manual coding errors and spreadsheet management. CSV upload functionality streamlines bulk processing, while dynamic form logic speeds up complaint entry.