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Purpose <p>Dictation of outpatient clinic letters can result in increased workload for clinicians. The use of generative, natural language processing artificial intelligence (AI) software could be used to supplant dictation and typing, alleviating the clinician’s workload. Therefore, our objective was to validate the use of AI software, Lyrebird AI (Lyrebird Health, Ltd.) to create accurate and readable clinic letters, in the context of a single clinician general paediatric neurosurgery clinic and a multi-disciplinary craniofacial clinic.</p> Methods <p>Twenty consultations were included, wherein a microphone was used to record the entire consultation. For each consultation, two letters were generated independently: (1) Lyrebird AI letter automatically generated at the end of the recording and (2) human clinician manual dictation in the usual manner. The letters were compared using objective readability metrics and a subjective rating by an independent blinded clinician for clinical accuracy.</p> Results <p>AI-generated clinic letters significantly improved readability compared to clinician-dictated letters, when using the Flesch–Kincaid Grade Level (median 10.3, IQR 0.75), (median 10.9, IQR 1.15) (<i>z</i> = 2.73, <i>p</i> &lt; 0.05), and SMOG Index (median 11.7, IQR 1.25) (median 13.1, IQR 0.9) (<i>z</i> =  − 3.36, <i>p</i> &lt; 0.001) metrics. An independent blinded clinician subjectively chose the AI-generated letters for overall preference in 75% of cases.</p> Conclusions <p>Lyrebird AI–generated clinic letters increased readability whilst maintaining clinical accuracy. Future work should focus on time, effort, and cost saving analysis. Presently, the findings of this study provide validation of Lyrebird AI for complex, multi-stakeholder clinical settings.</p>

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Integration of AI-generated clinic letters in complex paediatric neurosurgery outpatient settings

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月19日

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  • Mohamed Elmolla,
  • Anjum Aarifa Khanom,
  • Ahmad M. S. Ali,
  • Christian Duncan,
  • Anusha Hennedige,
  • Vejay N. Vakharia

摘要

Purpose

Dictation of outpatient clinic letters can result in increased workload for clinicians. The use of generative, natural language processing artificial intelligence (AI) software could be used to supplant dictation and typing, alleviating the clinician’s workload. Therefore, our objective was to validate the use of AI software, Lyrebird AI (Lyrebird Health, Ltd.) to create accurate and readable clinic letters, in the context of a single clinician general paediatric neurosurgery clinic and a multi-disciplinary craniofacial clinic.

Methods

Twenty consultations were included, wherein a microphone was used to record the entire consultation. For each consultation, two letters were generated independently: (1) Lyrebird AI letter automatically generated at the end of the recording and (2) human clinician manual dictation in the usual manner. The letters were compared using objective readability metrics and a subjective rating by an independent blinded clinician for clinical accuracy.

Results

AI-generated clinic letters significantly improved readability compared to clinician-dictated letters, when using the Flesch–Kincaid Grade Level (median 10.3, IQR 0.75), (median 10.9, IQR 1.15) (z = 2.73, p < 0.05), and SMOG Index (median 11.7, IQR 1.25) (median 13.1, IQR 0.9) (z =  − 3.36, p < 0.001) metrics. An independent blinded clinician subjectively chose the AI-generated letters for overall preference in 75% of cases.

Conclusions

Lyrebird AI–generated clinic letters increased readability whilst maintaining clinical accuracy. Future work should focus on time, effort, and cost saving analysis. Presently, the findings of this study provide validation of Lyrebird AI for complex, multi-stakeholder clinical settings.