The challenges
As an organization operating in the healthcare space, PharmaCord is no stranger to processing large volumes of documents. Every new prescription enrollment and approval case involves numerous documents being submitted by the patient, doctors, insurance companies and many other organizations.
Manual reviews and data entry of thousands of documents a day
Until now, processing of all these incoming documents was mostly a manual task. Even though the documents came in digitally as email attachments or faxes, they had to be reviewed by an employee, who would then classify and separate them as needed and add keywords and other metadata. With those tasks complete, the employee would then forward the documents for ingestion into Lynk (PharmaCord’s proprietary case management system). There, another user would attach the documents to the correct patient case and perform manual data entry from these documents into PharmaCord’s repository, OnBase.
Part of the challenge with manual processing was the sheer volume of incoming documents. Each enrollment application can require over 30 different types of documents and forms ranging from medical records, prescriptions and lab results, to IDs, income and tax statements, and insurance approvals and preauthorizations. With the process being so document-heavy, it was not uncommon for PharmaCord employees to have to classify and separate 2,000-3,000 documents a day across PharmaCord’s more than 40 prescription programs.
Intake documentation came in a single file of mixed document packets
Another challenge with the incoming documents was they often arrived in mixed document packets scanned into a single file, and considerable effort had to go into separating them and properly classifying the individual documents.
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Considerable seasonal volume spikes
There was also a dramatic recurring seasonal spike in volume during the annual patient re-enrollment period, during which time the processing volume almost doubled. This required PharmaCord to commit additional resources to this already costly process.
Processing errors were unavoidable
Finally, there was also a desire to reduce document processing errors. Given the volume and variety of documents processed every day, even the best human workers could make simple mistakes which could result in rework and delay patients receiving the medications they need.