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Streamlining patient information from ambulatory acquisitions with
AI-Powered Document Processing

Mid-Atlantic Healthcare Network

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Overview

The healthcare industry relies on efficient document management to ensure the smooth flow of patient information, regulatory compliance, and effective decision-making from providers.

A major mid-Atlantic health system responsible for managing 9 million documents per year was grappling with significant challenges in its document indexing process, especially in the ambulatory space. 

 

Challenges

The indexing process, the backbone of the health system's document management system, was weakening due to the sheer volume of documents. They had many capable indexers, but there were too many incoming documents leading to an unsustainable process. In addition, they faced barriers such as:

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Physical, full-time indexers were spending a lot of time keeping up with the demand for incoming documents.

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Keeping pace with the number of documents led to human errors and inconsistencies across information distributed throughout their systems.

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The health system and its departments didn't have the staff to keep up with demand, and they were experiencing employee burnout. Hiring for these positions was tough.

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As with manual indexing comes data entry errors. This meant data was entering their systems incorrectly.

Solution
Full-Service AI-Powered Document Processing

The health system embarked on a strategic initiative with DataBank to revamp its document indexing process. We implemented a modern, AI-Powered Document Processing system that combined artificial and machine learning technologies plus human validation to index documents swiftly and accurately.

1

Discovery

Together, we discussed their goals to index their multi-facility records and move away from paper.

2

File receipt

Their files were picked up and delivered to one of our HIPAA-compliant regional facilities.

3

Prep

Our team prepared their content to be processed while the client's team prioritized patient care.

4

Processing

Patient information was extracted and labeled based on predetermined keywords using AI technology.

5

Delivery

We delivered newly structured patient information directly to their EMR so it could be immediately accessed by their care teams and staff.

 

Results

The health system has eliminated manual indexing and classification of their ambulatory records. They now have structured, cohesive patient information starting at intake and flowing throughout their system that’s accessible to all employees.

This process is completely scalable as they acquire more facilities. DataBank continues to save the client from hiring additional full-time employees to support workloads and allows their care teams to focus on their patients.

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98% accuracy

Automated indexing achieved an accuracy rating of 98% for indexed healthcare records

55% cost decrease

The cost to index a single document was reduced from $1.50 to $0.68.

210% ROI

ROI for the implementation organization-wide was projected to be 210%.

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$7.9 million annual savings

The health system projected an annual savings of $7.9 million as a direct result of the adoption of the automated indexing system. Savings were accrued through reduced labor costs, minimized errors, and optimized resource allocation.

Workforce reallocation

They were able to reassign their indexers to more impactful roles, such as data analysts or exception trackers.

ROI and Vision

Vision

The health system achieved data intake accuracy, substantial cost savings, and increased workforce efficiency by replacing its manual indexing process with DataBank's full-service AI-Powered Document Processing.

The successful implementation of this solution not only resolved immediate pain points but also positioned them for long-term success by fostering strategic resource allocation and delivering a solid return on investment. 

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Learn more about DataBank’s
AI-Powered Document Processing from a healthcare specialist.

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