Scholarlink

<p>The digitalisation of health data has helped drive initiatives like the Scottish Collaborative Optometry-Ophthalmology Network eResearch (SCONe), which links retinal images from community optometry practices with other routinely collected health data to enhance disease detection. As data-driven approaches expand throughout the healthcare system, patient and public involvement and engagement (PPIE) is increasingly recognised as essential for improving the quality, relevance, and acceptability of health research. However, despite growing endorsement, challenges remain, including inconsistent terminology, varying levels of involvement, limited implementation guidance, and a lack of evidence on its impact. These challenges are even more pronounced in data science, particularly within large-scale research, where PPIE is often underreported, leaving the field without a clear framework for meaningful implementation. This article offers a reflective account of the challenges and barriers encountered by SCONe in developing a PPIE strategy. By documenting this process, it provides insights into the complexities of implementing PPIE in large research consortia and offers practical guidance for future initiatives seeking to enhance the impact and relevance of public partnerships in large scale data science research.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Beyond the dataset: integrating public voices in data science

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月8日

查看全文
  • Ana-Paula Rubio,
  • Janette Dunn,
  • Janice Borthwick,
  • Sheila Saunders,
  • Claire Tochel,
  • Heather Anderson,
  • Lorna Coull,
  • Malihe Javidi,
  • Heather Cloete,
  • Alice McTrusty,
  • Jonathan Penny,
  • Tom MacGillivray,
  • Andrew J. Tatham,
  • Tracy Jackson,
  • Carol Porteous,
  • Niall Strang,
  • Baljean Dhillon,
  • Miguel O. Bernabeu

摘要

The digitalisation of health data has helped drive initiatives like the Scottish Collaborative Optometry-Ophthalmology Network eResearch (SCONe), which links retinal images from community optometry practices with other routinely collected health data to enhance disease detection. As data-driven approaches expand throughout the healthcare system, patient and public involvement and engagement (PPIE) is increasingly recognised as essential for improving the quality, relevance, and acceptability of health research. However, despite growing endorsement, challenges remain, including inconsistent terminology, varying levels of involvement, limited implementation guidance, and a lack of evidence on its impact. These challenges are even more pronounced in data science, particularly within large-scale research, where PPIE is often underreported, leaving the field without a clear framework for meaningful implementation. This article offers a reflective account of the challenges and barriers encountered by SCONe in developing a PPIE strategy. By documenting this process, it provides insights into the complexities of implementing PPIE in large research consortia and offers practical guidance for future initiatives seeking to enhance the impact and relevance of public partnerships in large scale data science research.