More and more often, reports on clinical studies for approving new medicines are provided digitally by the FDA and other international approval bodies. The necessary documents, however, are distributed worldwide to sites like doctors’ practices and hospitals on paper, as comprehensive internet access is not always guaranteed. The documents include patient records, so-called clinical research forms (CRF), and data query forms (DQF). An individual patient record consists of a number of individual documents and can be 50 to 100 pages long. To allow employees of regulatory bodies to view patient records conveniently on screen, the individual documents must be comprehensively structured and linked together.
The scanned documents are automatically classified as CRF or DQF. Relevant patient data needs to be read out from both document types. Manual quality assurance must be carried out on the results of both classification and automatic reading-out. Bookmarks and hyperlinks must be generated using the read-out patient data. The documents, thus linked to digital patient records, must then be exported as highly-compressed PDF/A files.
The solution was built using the DocYard Platform. First, the workflow was modelled in the DocYard Cockpit. The FormRecognition, PDF-Plus-Package and XSL/T modules were particularly useful at this stage.
With the help of FormRecognition, incoming documents were then classified, manually checked and, where necessary, subjected to post-classification.
Afterwards, the patient data was automatically read and checked using the FormValidator. At this point in the workflow, the patient data was available to the FormRecognition module in XML format. The results were converted to XML format using the XSL Transformation Module, allowing them to be read as bookmarks and hyperlinks by the PDF-Plus-Package.
The PDF-Plus-Package’s MRC module compressed the scanned documents using the award-winning MRC layer system. Finally, the compressed data was exported, along with the XML-formatted bookmarks and hyperlinks, as structured, linked and fully text searchable PDF/A patient records.
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