Introduction There is increasing interest in Artificial Intelligence (AI) and its application to medicine. Perceptions of AI are less well-known, notably amongst children and young people (CYP). This workshop investigates attitudes towards AI and its future applications in medicine and healthcare at a specialised paediatric hospital using practical design scenarios. Method Twenty-one members of a Young Persons Advisory Group for research contributed to an engagement workshop to ascertain potential opportunities, apprehensions, and priorities. Results When presented as a selection of practical design scenarios, we found that CYP were more open to some applications of AI in healthcare than others. Human-centeredness, governance and trust emerged as early themes, with empathy and safety considered as important when introducing AI to healthcare. Educational workshops with practical examples using AI to help, but not replace humans were suggested to address issues, build trust, and effectively communicate about AI. Conclusion Whilst policy guidelines acknowledge the need to include children and young people to develop AI, this requires an enabling environment for human-centred AI involving children and young people with lived experiences of healthcare. Future research should focus on building consensus on enablers for an intelligent healthcare system designed for the next generation, which fundamentally, allows co-creation. Impact Children and young people (CYP) want to be included to share their insights about the development of research on the potential role of Artificial Intelligence (AI) in medicine and healthcare and are more open to some applications of AI than others. Whilst it is acknowledged that a research gap on involving and engaging CYP in developing AI policies exists, there is little in the way of pragmatic and practical guidance for healthcare staff on this topic. This requires research on enabling environments for ongoing digital cooperation to identify and prioritise unmet needs in the application and development of AI.
Objective: To identify key issues affecting the quality of life (QoL) of adult patients with craniofacial anomalies.Method: This was a qualitative prospective study, using in-depth, semistructured interviews. Ten patients who fulfilled the inclusion criteria were recruited during their attendance at the adult craniofacial clinic at the Eastman Dental Hospital, University College London Hospitals NHS Foundation Trust. Interviews ceased when no new themes were arising. A thematic framework analysis was used to identify major themes and subthemes relating to QoL in adult craniofacial patients.
IntroductionA transition from face-to-face to virtual consultations occurred in response to the COVID-19 pandemic. Evaluation of outcome data is essential for future healthcare modelling. MethodsClinicians at a children's hospital evaluated perceptions of face-to-face video and telephone appointments by questionnaire. Responses were compared with operational outcomes from June 2019 and June 2020. ResultsNinety-three clinicians responded from 28 subspecialties. Virtual consultations increased from 6% (2019) to 67% (2020). No differences were found between appointment types for recording a medical and social history; a significant difference (p<0.001) was seen for the perceived ability to detect clinical signs, organise investigations and make a diagnosis. The proportion of appointments resulting in discharge compared with face-to-face visits was unchanged. The proportion of patients requiring further contact increased from 35% (32% face-to-face and 3% telephone) to 46% (14% face-to-face; 21% telephone and 11% video; chi-squared 426; p<0.0001).The percentage of patients offered an appointment following two 'was not brought' appointments increased from 71% (2019) to 81% (2020) and was most common following telephone appointments (20% face-to-face, 43% telephone and 18% video; chi-squared 474; p<0.0001). ConclusionThe perception of clinicians is that virtual appointments enabled continuity of paediatric care with improved
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