Centre for Oral Immunobiology and Regenerative Medicine, Institute of Dentistry, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, Newark Street, London E1 2AT.
Centre for Teaching Innovation, Institute of Dentistry, Barts and the London School of Medicine and Dentistry, Queen Mary University of London Newark Street London E1 2AT.
Br Dent J. 2019 Jan 11;226(1):62-66. doi: 10.1038/sj.bdj.2019.8.
Oral surgery services are progressively moving out of traditional hospital departments and into primary care. This necessitates accurate methods of triaging referrals, so patients of varying complexity are managed in the most suitable environment. The latest NHS commissioning proposal identifies 'level 1' procedures as simple extractions which do not require referral. We developed a model for quantifying how accurately these simple extractions can be predicted from information in standard referral letters.
Experienced clinicians (N = 10) were independently asked to predict whether extractions (N = 25) were likely to be simple-forceps or surgical procedures, from information provided in specially developed standardised referral letters. One oral surgeon had previously completed all extractions. The triaging clinicians were asked to comment on reasons for each decision and state their level of confidence in their predictions.
Only 67% (range 52–76%) of extractions were correctly predicted as either simple or surgical with a significant propensity to underestimate the complexity of surgical extractions rather than overestimating simple procedures (p <0.05). High levels of confidence reported by the clinicians in their decisions correlated with more accurate predictions (p <0.05).
This is the first attempt to develop a model for clinical decision-making in oral surgery triage services. Our findings suggest there is significant scope for improvement and highlight areas for development.
口腔外科服务正逐渐从传统的医院科室转移到初级保健领域。这就需要有准确的分诊方法，以便将不同复杂程度的患者安排到最合适的环境中进行治疗。最新的国民保健制度（NHS）招标提案将“一级”手术定义为简单的拔牙手术，无需转诊。我们开发了一种模型，可以从标准转诊信中提供的信息中准确预测这些简单拔牙手术。
经验丰富的临床医生（N=10）被要求根据专门制定的标准化转诊信中提供的信息，独立预测 25 例拔牙手术中哪些是简单的钳子拔牙或手术拔牙。一位口腔外科医生此前已完成所有拔牙手术。分诊临床医生被要求对每个决策的原因进行评论，并对其预测的置信水平进行评估。
只有 67%（范围 52-76%）的拔牙手术可以正确预测为简单或手术拔牙，且存在低估手术拔牙复杂性而不是高估简单手术的明显倾向（p<0.05）。临床医生对其决策的高度信心与更准确的预测相关（p<0.05）。
这是首次尝试开发口腔外科分诊服务中临床决策的模型。我们的研究结果表明，还有很大的改进空间，并突出了需要进一步发展的领域。
