Duplicate Document Detection Reduces Backlog by 95%
Ontellus is the nation’s largest, full-service procurer of medical records, wage and employment records, and diagnostic imaging files, pharma, social security records, billing records and other claims-related data services.
Ontellus enables claims adjusters with analytics that help review case records in a logical timeline that dynamically adapts as more records are retrieved. Adjusters can share important sensitive HIPAA data digitally in the cloud with their legal counsel to support litigated claims.
Challenge Accepted
Out of the box, Power Platform can recognize duplicate data records, like rows on a spreadsheet, comparing each column to each other column. But recognizing duplicate documents is more challenging. The file names may be the same or different, but the actual documents may or may not be duplicates. The same document can be scanned and received twice, in which case the files are not digitally equivalent, even though they are duplicates.
Optical Character Recognition, including that used by Power Platform AI Builder, can read forms, but it tends to work well for very well-defined document layouts, and doesn’t perform as well when a large variety of document types are received. This can be mitigated by making two passes – one to classify the document type, and a second, type-specific pass to process a more rigidly defined format. But, in some cases, a human review is required. Making this process as streamlined as possible will make the task less burdensome to your team and cut your costs.
Build the Solution
To optimize duplicate detection review process for Ontellus, Bauen Solutions implemented a multi-step process. When documents are received, a check is first made for obvious duplicate markers, such as identical filenames, types, sizes, and digital fingerprint. The file is uploaded to Azure Blob Storage, which is also far less costly than storing it within Dataverse directly.
After confirming no exact matches are found based on the file info, the document is coded, classifying it by type of record (invoice, statement, requested record, etc.), relevant account, etc., after which the system checks for existing documents matching the coded criteria.
For each potential duplicate found, a request is created for a human to verify before the document is processed further.
Each review is processed quickly by displaying the records side by side. For multi-page documents, the pages can be scrolled simultaneously to check corresponding pages.
In this example, the user quickly ascertains the records are not duplicates within seconds – the latter is an invoice paid confirmation. Likely this near-duplicate may have been improperly classified, whether by human error or by OCR technology being unable to process a less than ideal image.
Bottom Line Benefits
By automating the obvious duplicates, Bauen Solutions was able to reduce the number of documents needing human review by 90%. This massive time savings also increased accuracy by helping information workers focus on reviewing more difficult cases to detect. Taking it a step further, additional AI technologies can process the text within the document, or the images within a document such as a scanned PDF, allowing AI to discern and prioritize the attention of the information worker to cases that need it.
If your business requires processing thousands of documents daily, with duplicates eating into your profits, let Bauen Solutions help you reduce the workload and streamline what can be an expensive, burn-out inducing, mind-numbing process. Your team will thank you for it.
Because of the changes:
- Reduced manual comparison backlog and workload by 95%.
- Increased accuracy by allowing side by side comparison on screen versus previous printed paper process.
* Company information not available as development was done under a non-disclosure agreement. It’s considered internal intellectual property and competitive advantage.
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