Automated Data Processing System for Large-Scale Healthcare Backlogs

The healthcare organization faces an overwhelming backlog of 19 million patient assessments due to manual data entry bottlenecks, with each assessment taking approximately 15 minutes to process manually. This results in significant delays, with the backlog requiring the effort of 33 full-time staff members over a year to clear, impacting patient care quality and operational efficiency.

A large healthcare provider network operating multiple hospitals and clinics, managing extensive patient data workflows and striving for operational efficiency.

• Develop an automated system to process around 4,000 patient assessments daily, significantly reducing manual effort and processing time.
• Eliminate the existing backlog of 250,000 assessments within 2 months of deployment.
• Ensure 100% accuracy in data entry to prevent errors in patient records.
• Enable seamless integration of automated data entry with existing healthcare management systems.
• Provide ongoing, reliable automation to support operational efficiencies for over 2.5 years with minimal downtime.

• Optical character recognition (OCR) and data extraction from scanned paper assessments.
• Matching and mapping extracted data to corresponding fields within the healthcare management system.
• Automated copy-paste functionality to input data with zero errors.
• Batch processing capability to handle high-volume assessments continuously.
• Monitoring dashboard for real-time oversight and error detection.

• Existing Electronic Health Record (EHR) platform
• Scanned document repositories
• Assessment data storage databases

• System uptime of 99.9% with no downtime post-deployment.
• Processing capacity of at least 4,000 assessments per day.
• Data accuracy rate of 100% in automated entry.
• Security measures compliant with healthcare data regulations (e.g., HIPAA).
• Scalability to support increasing data volume over time.

Implementation of this automation solution is expected to clear the 19 million assessment backlog within 2 months, processing approximately 4,000 assessments daily. This will deliver a substantial reduction in manual labor equivalent to 33 full-time staff, improve data accuracy to 100%, and enable healthcare providers to access timely, reliable patient data, thereby enhancing patient care quality and operational efficiency.