Artificial Intelligence (AI) technology in healthcare promises more efficient processes and accurate outcomes, which then results in lower operational costs. The use of AI solutions in medical coding is rapidly growing and has helped healthcare organizations increase productivity and reduce the burden on coders. But, unlike a well-trained medical coder, AI does not have the capability and sensitivity to extract and interpret pertinent information from complex medical record scenarios. The medical record includes ambiguous acronyms, local jargon, and specialty medical language and terminology that add to the complexity of abstracting documentation. For AI to learn these skills, medical coders will have to teach it, and auditors will have to check its accuracy.
This study examines how medical coders perceive the use of AI in medical coding. It utilizes survey data to analyze the performance and impact of AI utilization in medical coding, the likelihood of AI completely replacing medical coders and the necessary skills or knowledge a medical coder needs to stay relevant and adjust to the change. A survey was created using freeonlinesurveys.com. The link was distributed through professional social media, LinkedIn, targeting medical coders with coding and health information credentials. The survey consists of nineteen (19) questions assessing their type of credential(s), coding experience, knowledge and experience in AI, how AI impacts medical coding, and what skill set and type of training they think would be beneficial to anticipate the change, Keywords: productivity, efficiency, accuracy, skills, change, adaptable, collaboration
Published:
January 7, 2025
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