A Hybrid Approach to Prior Authorization Data Mining from Fax PDFs Using Altova MapForce and Natural Language Processing

Authors

  • Balasubramanian Rengasamy

Keywords:

Prior authorization automation, Natural Language Processing, Altova MapForce, Healthcare Document Extraction, Medical Data Transformation.

Abstract

Another major challenge requiring solutions by healthcare organizations is how to process priorauthorization requests that are sent over fax and presented in PDF files, which constitute unstructured orsemi-structured data. The continuous use of manual processing incurs the creation of bottlenecks in operations, the escalation of administrative expenses,

References

American Medical Association, "2024 AMA prior authorization physician survey". [Online]. Available: https://www.ama-assn.org/system/files/prior-authorization-survey.pdf

Downloads

Published

2026-01-08

How to Cite

Balasubramanian Rengasamy. (2026). A Hybrid Approach to Prior Authorization Data Mining from Fax PDFs Using Altova MapForce and Natural Language Processing . Journal of Computational Analysis and Applications (JoCAAA), 35(1), 89–96. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/4643

Issue

Vol. 35 No. 1 (2026): JOCAAA

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.