{"title":"The potential benefit of artificial intelligence regarding clinical decision-making in the treatment of wrist trauma patients","authors":"Marco Keller, Meret Rohner, Philipp Honigmann","doi":"10.1186/s13018-024-05063-6","DOIUrl":null,"url":null,"abstract":"The implementation of artificial intelligence (AI) in health care is gaining popularity. Many publications describe powerful AI-enabled algorithms. Yet there’s only scarce evidence for measurable value in terms of patient outcomes, clinical decision-making or socio-economic impact. Our aim was to investigate the significance of AI in the emergency treatment of wrist trauma patients. Two groups of physicians were confronted with twenty realistic cases of wrist trauma patients and had to find the correct diagnosis and provide a treatment recommendation. One group was assisted by an AI-enabled application which detects and localizes distal radius fractures (DRF) with near-to-perfect precision while the other group had no help. Primary outcome measurement was diagnostic accuracy. Secondary outcome measurements were required time, number of added CT scans and senior consultations, correctness of the treatment, subjective and objective stress levels. The AI-supported group was able to make a diagnosis without support (no additional CT, no senior consultation) in significantly more of the cases than the control group (75% vs. 52%, p = 0.003). The AI-enhanced group detected DRF with superior sensitivity (1.00 vs. 0.96, p = 0.06) and specificity (0.99 vs. 0.93, p = 0.17), used significantly less additional CT scans to reach the correct diagnosis (14% vs. 28%, p = 0.02) and was subjectively significantly less stressed (p = 0.05). The results indicate that physicians can diagnose wrist trauma more accurately and faster when aided by an AI-tool that lessens the need for extra diagnostic procedures. The AI-tool also seems to lower physicians' stress levels while examining cases. We anticipate that these benefits will be amplified in larger studies as skepticism towards the new technology diminishes.","PeriodicalId":16629,"journal":{"name":"Journal of Orthopaedic Surgery and Research","volume":null,"pages":null},"PeriodicalIF":2.8000,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Orthopaedic Surgery and Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s13018-024-05063-6","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ORTHOPEDICS","Score":null,"Total":0}
引用次数: 0
Abstract
The implementation of artificial intelligence (AI) in health care is gaining popularity. Many publications describe powerful AI-enabled algorithms. Yet there’s only scarce evidence for measurable value in terms of patient outcomes, clinical decision-making or socio-economic impact. Our aim was to investigate the significance of AI in the emergency treatment of wrist trauma patients. Two groups of physicians were confronted with twenty realistic cases of wrist trauma patients and had to find the correct diagnosis and provide a treatment recommendation. One group was assisted by an AI-enabled application which detects and localizes distal radius fractures (DRF) with near-to-perfect precision while the other group had no help. Primary outcome measurement was diagnostic accuracy. Secondary outcome measurements were required time, number of added CT scans and senior consultations, correctness of the treatment, subjective and objective stress levels. The AI-supported group was able to make a diagnosis without support (no additional CT, no senior consultation) in significantly more of the cases than the control group (75% vs. 52%, p = 0.003). The AI-enhanced group detected DRF with superior sensitivity (1.00 vs. 0.96, p = 0.06) and specificity (0.99 vs. 0.93, p = 0.17), used significantly less additional CT scans to reach the correct diagnosis (14% vs. 28%, p = 0.02) and was subjectively significantly less stressed (p = 0.05). The results indicate that physicians can diagnose wrist trauma more accurately and faster when aided by an AI-tool that lessens the need for extra diagnostic procedures. The AI-tool also seems to lower physicians' stress levels while examining cases. We anticipate that these benefits will be amplified in larger studies as skepticism towards the new technology diminishes.
期刊介绍:
Journal of Orthopaedic Surgery and Research is an open access journal that encompasses all aspects of clinical and basic research studies related to musculoskeletal issues.
Orthopaedic research is conducted at clinical and basic science levels. With the advancement of new technologies and the increasing expectation and demand from doctors and patients, we are witnessing an enormous growth in clinical orthopaedic research, particularly in the fields of traumatology, spinal surgery, joint replacement, sports medicine, musculoskeletal tumour management, hand microsurgery, foot and ankle surgery, paediatric orthopaedic, and orthopaedic rehabilitation. The involvement of basic science ranges from molecular, cellular, structural and functional perspectives to tissue engineering, gait analysis, automation and robotic surgery. Implant and biomaterial designs are new disciplines that complement clinical applications.
JOSR encourages the publication of multidisciplinary research with collaboration amongst clinicians and scientists from different disciplines, which will be the trend in the coming decades.