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Informative Article | Engineering Science | India | Volume 9 Issue 1, January 2020
Utilizing Natural Language Processing and Machine Learning for Automated Medical Coding and Billing Optimization
Abstract: Merging Natural Language Processing (NLP) with Machine Learning (ML) in the medical sector offers promising enhancements across a variety of both administrative and clinical workflows. This paper delves into utilizing these sophisticated technologies to better the processes of medical coding and billing, which stand as essential yet intricate aspects of health care management. The conventional methods of manual coding come with substantial hindrances, including errors made by humans, significant time expenditure, and inconsistency, all of which lead to financial deficits and adherence problems. The system proposed makes use of NLP techniques for the interpretation and transformation of unstructured clinical narratives into universally accepted codes with high precision. Concurrently, ML algorithms are put to work, learning from past records to elevate the coding operation's accuracy and efficiency as time progresses. This paper outlines the architecture designed for the system, the processes deployed in managing data and training models, and how NLP and ML are integrated to comply with health care rules and uphold coding norms. Additionally, this study measures the system's efficacy through the application on actual medical documents and its comparison against older coding techniques. Results uncover notable enhancements in the precision of coding, a downturn in billing discrepancies, and a boost in operational efficiency that collectively contribute to better management of the revenue cycle. The document also contemplates the hurdles faced during the system's implementation, like issues regarding data privacy and the incessant need for model revisions to keep pace with evolving medical practices and guidelines. The concluding part of this paper reflects on the potential repercussions this technology could have on the health care industry, highlighting reduced overhead costs, improved patient care, and enabling a smoother, more automated approach to medical coding and billing.
Keywords: Natural Language Processing, Machine Learning, Medical Coding, Billing Optimization, Healthcare Administration, Data Privacy, Revenue Cycle Management, Clinical Documentation, Coding Standards, Operational Efficiency
Edition: Volume 9 Issue 1, January 2020,
Pages: 1909 - 1918