Stanley Alexandra L, Edwards Thomas C, Jaere Martin D, Lex Johnathan R, Jones Gareth G
Faculty of Medicine, Imperial College London, London, UK.
MSk Lab, Imperial College London, London, UK.
Digit Health. 2023 Jan 26;9:20552076231152177. doi: 10.1177/20552076231152177. eCollection 2023 Jan-Dec.
Knee pain is caused by various pathologies, making evaluation in primary-care challenging. Subsequently, an over-reliance on imaging, such as radiographs and MRI exists. Electronic-triage tools represent an innovative solution to this problem. The aims of this study were to establish the magnitude of unnecessary knee imaging prior to orthopaedic surgeon referral, and ascertain whether an e-triage tool outperforms existing clinical pathways to recommend correct imaging.
Patients ≥18 years presenting with knee pain treated with arthroscopy or arthroplasty at a single academic hospital between 2015 and 2020 were retrospectively identified. The timing and appropriateness of imaging were assessed according to national guidelines, and classified as 'necessary', 'unnecessary' or 'required MRI'. Based on an eDelphi consensus study, a symptom-based e-triage tool was developed and piloted to preliminarily diagnose five common knee pathologies and suggest appropriate imaging.
1462 patients were identified. 17.2% ( = 132) of arthroplasty patients received an 'unnecessary MRI', 27.6% ( = 192) of arthroscopy patients did not have a 'necessary MRI', requiring follow-up. Forty-one patients trialled the e-triage pilot (mean age: 58.4 years, 58.5% female). Preliminary diagnoses were available for 33 patients. The e-triage tool correctly identified three of the four knee pathologies (one pathology did not present). 79.2% ( = 19) of participants would use the tool again.
A substantial number of knee pain patients receive incorrect imaging, incurring delays and unnecessary costs. A symptom-based e-triage tool was developed, with promising performance and user feedback. With refinement using larger datasets, this tool has the potential to improve wait-times, referral quality and reduce cost.
膝关节疼痛由多种病理情况引起,这使得初级保健中的评估具有挑战性。随后,存在对影像学检查(如X光片和磁共振成像)的过度依赖。电子分诊工具是解决这一问题的创新方案。本研究的目的是确定在骨科医生转诊前不必要的膝关节成像的比例,并确定电子分诊工具是否比现有的临床路径更能推荐正确的成像检查。
回顾性确定2015年至2020年期间在一家学术医院接受关节镜检查或关节置换术治疗的18岁及以上膝关节疼痛患者。根据国家指南评估成像的时间和适当性,并分类为“必要”、“不必要”或“需要磁共振成像”。基于一项电子德尔菲共识研究,开发了一种基于症状的电子分诊工具并进行试点,以初步诊断五种常见的膝关节病理情况并建议适当的成像检查。
共确定了1462例患者。17.2%(n = 132)的关节置换术患者接受了“不必要的磁共振成像”,27.6%(n = 192)的关节镜检查患者没有进行“必要的磁共振成像”,需要随访。41名患者参与了电子分诊试点(平均年龄:58.4岁,58.5%为女性)。33名患者获得了初步诊断。电子分诊工具正确识别了四种膝关节病理情况中的三种(有一种病理情况未出现)。79.2%(n = 19)的参与者会再次使用该工具。
大量膝关节疼痛患者接受了不正确的成像检查,导致延误和不必要的费用。开发了一种基于症状的电子分诊工具,其表现和用户反馈良好。通过使用更大的数据集进行改进,该工具有可能缩短等待时间、提高转诊质量并降低成本。