{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T00:33:26Z","timestamp":1788482006703,"version":"build-2803163510"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643685960","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,5,15]],"date-time":"2025-05-15T00:00:00Z","timestamp":1747267200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,5,15]]},"abstract":"<jats:p>Creating standardized billing codes from clinic notes is challenging due to the complexity of over 22,000 codes and the unstructured nature of medical records. This paper investigates how well GPT-4, can automate CPT\/HCPCS codes generation. To assess its understanding, we prompted GPT-4 to produce CPT\/ HCPCS codes from their textual descriptions. Next, we prompted GPT-4 to generate billing codes, with confidence scores, from Vanderbilt University Medical Center clinic notes linked to billing codes by patient visit identifiers. GPT-4 achieved 20.8% accuracy in generating exact codes from code descriptions and 28.9% mean true positive rate in assigning correct codes for clinic notes. These results highlight the challenges LLMs face in understanding and generating accurate billing codes.<\/jats:p>","DOI":"10.3233\/shti250490","type":"book-chapter","created":{"date-parts":[[2025,5,16]],"date-time":"2025-05-16T08:58:24Z","timestamp":1747385904000},"source":"Crossref","is-referenced-by-count":1,"title":["Exploring the Potential of GPT-4 in Creating Billing Codes from Clinic Notes"],"prefix":"10.3233","author":[{"given":"Qingyuan","family":"Song","sequence":"first","affiliation":[{"name":"Vanderbilt University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yike","family":"Li","sequence":"additional","affiliation":[{"name":"Vanderbilt University"},{"name":"Vanderbilt University Medical Center"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bradley A.","family":"Malin","sequence":"additional","affiliation":[{"name":"Vanderbilt University"},{"name":"Vanderbilt University Medical Center"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhijun","family":"Yin","sequence":"additional","affiliation":[{"name":"Vanderbilt University"},{"name":"Vanderbilt University Medical Center"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Intelligent Health Systems \u2013 From Technology to Data and Knowledge"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI250490","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,16]],"date-time":"2025-05-16T08:58:24Z","timestamp":1747385904000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI250490"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,15]]},"ISBN":["9781643685960"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti250490","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5,15]]}}}