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Camera: A Consensus Study to Ascertain Minimum Datasets for Ear Remote Assessments

  • CAMERA Steering Committee
  • , CAMERA Working Group
  • , Jonathan Lee*
  • , Joseph Cowling
  • , Matthew E. Smith
  • , Nishchay Mehta
  • , Dimitrios Spinos
  • , Christopher Coulson
  • , Jameel Muzaffar
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

INTRODUCTION: Remote healthcare has demonstrated benefits in providing high quality care, improving patient access, and reducing morbidity. In ear, nose, and throat surgery, there has been a recent surge in remote care driven by advancements including endoscopic otoscopy and boothless audiometry, as well as the coronavirus pandemic, but uncertainty exists regarding the minimum data needed for accurate remote diagnosis.

METHODS: A panel of otology, audiology, general practice, and audiovestibular physicians was invited, and a literature review was undertaken to populate candidate dataset items for Round 1 of the Delphi process using the web-based software, Welphi. This was followed by two further Rounds, with controlled anonymised item-rating and qualitative feedback between rounds. Finally, a consensus meeting analysed and organised the results for dissemination of the final consensus outcomes.

RESULTS: Seventy studies were used to populate the questionnaire in Round 1. Thirty-four multi-disciplinary expert panellists determined the final data items across the 3 Delphi Rounds. Experts worked at over 16 different centres across the United Kingdom. There was an average response rate of 94% across all rounds.

DISCUSSION: This study highlights a multidisciplinary team's consensus essential dataset for effective remote ear assessment. With NHS waiting lists at an all-time high, remote assessment capacity could alleviate strain and enhance patient care. This initiative will facilitate novel service and pathway redesign with the aim of ensuring all patients have access to high-quality ear assessments, regardless of location. We are also hopeful that this standardised dataset will also facilitate research and audit of remote ear services.

Original languageEnglish
Pages (from-to)1002-1010
Number of pages9
JournalClinical Otolaryngology
Volume50
Issue number6
Early online date6 Jul 2025
DOIs
Publication statusPublished - Nov 2025

Bibliographical note

© 2025 John Wiley & Sons Ltd.

Keywords

  • Humans
  • Consensus
  • Delphi Technique
  • COVID-19/epidemiology
  • United Kingdom
  • Ear Diseases/diagnosis
  • Telemedicine
  • Remote Consultation
  • Datasets as Topic
  • SARS-CoV-2
  • Otolaryngology

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