ArticleFrontiers in artificial intelligence2024
AI integration in nephrology: evaluating ChatGPT for accurate ICD-10 documentation and coding.
Article in Frontiers in artificial intelligence, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Artificial Intelligence to Improve Clinical Coding Practice in Scandinavia: Crossover Randomized Controlled Trial.Journal of medical Internet research · 2025Trial
- Artificial intelligence in nephrology: predicting CKD progression and personalizing treatment.International urology and nephrology · 2026Review
- A pilot study on the impact of large language model assistance on the evaluation of complex medical living kidney donor candidates.Clinical transplantation and research · 2026Article
- A brief review of some artificial intelligence methods in nephrology.Pediatric nephrology (Berlin, Germany) · 2026Review
- Susceptibility of Assessment Types to AI-Generated Content in Digital Health and Health Information Management Education: Quasi-Experimental Pilot Study.JMIR medical education · 2026Article
- How do dialysis nurses and AI reason clinically? A scenario-based comparative study.BMC nursing · 2026Article
- Quality assessment of large language model-generated prior authorization letters in nephrology.Frontiers in digital health · 2026Article
- Large language models for extraction of OPS-codes from operative reports in meningioma surgery.Acta neurochirurgica · 2025Article
- Article
- A retrospective multi-site examination of chronic kidney disease using longitudinal laboratory results and metadata to identify clinical and financial risk.BMC nephrology · 2024Observational
- Generative artificial intelligence in graduate medical education.Frontiers in medicine · 2024Review
Corrections and comments
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Authors and funding
8 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Background: Accurate ICD-10 coding is crucial for healthcare reimbursement, patient care, and research. AI implementation, like ChatGPT, could improve coding accuracy and reduce physician burden. This study assessed ChatGPT's performance in identifying ICD-10 codes for nephrology conditions through case scenarios for pre-visit testing. Methods: Two nephrologists created 100 simulated nephrology cases. ChatGPT versions 3.5 and 4.0 were evaluated by comparing AI-generated ICD-10 codes against predetermined correct codes. Assessments were conducted in two rounds, 2 weeks apart, in April 2024. Results: In the first round, the accuracy of ChatGPT for assigning correct diagnosis codes was 91 and 99% for version 3.5 and 4.0, respectively. In the second round, the accuracy of ChatGPT for assigning the correct diagnosis code was 87% for version 3.5 and 99% for version 4.0. ChatGPT 4.0 had higher accuracy than ChatGPT 3.5 ( Conclusion: ChatGPT 4.0 can significantly improve ICD-10 coding accuracy in nephrology through case scenarios for pre-visit testing, potentially reducing healthcare professionals' workload. However, the small error percentage underscores the need for ongoing review and improvement of AI systems to ensure accurate reimbursement, optimal patient care, and reliable research data.
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