An after-action review for adoption of emerging technologies during the COVID-19 pandemic

IntroductionThe COVID-19 pandemic response has accelerated adoption of digital health technologies to support social distancing. In part, this involves repurposing technologies that were not originally developed for healthcare application. In the hospital setting, this includes the appropriation of ‘Off the Shelf’ (OTS) digital products that facilitate video-based clinical consultations, diagnostics and communication during ward rounds and multi-disciplinary team meetings. Such technologies were implemented within weeks at GOSH where video consultations were implemented for >90% of outpatient appointments.MethodsHere we present the findings from a Debrief-After Action Review (AAR) lasting two hours, supplemented with speculative questions on how lessons learned from the rapid deployment of one technology could inform the adoption practices of other emerging technologies.ResultsFifteen participants, who were members of a Transforming Care Links working group and interested in the impact of digital systems on patient care, contributed to the AAR. Five themes were identified from thematic analysis of this bottom-up approach: (i) Clinical: Planning and redesigning workflows with clear purpose, intent, and communication with clinical teams (ii) Technology: Infrastructure and equipment available across the team based on the needs of the workspace, with security and governance processes (iii) Capability mapping: Building core capability in a structured way across the entire team with space and time to trial out technologies as part of a progressive learning path and supported by clinical champions (iv) Benefits: Demonstrable benefits with new technology enabled ways of working based on preliminary small-scale deployments that deliver measurable value (v) Environment and Context: Context-specific workflow redesign for technology enabled interactions that consider optimum conditions of the physical environment.ConclusionThis user-centred approach identified routine training pathways, equity of access to training opportunities and equipment, a period of trialability and demonstrable benefits as enablers for the successful adoption of emerging technologies.

Encouraging activity and exercise among children and young people using computer vision and machine learning during gaming

IntroductionPopulation health and wellbeing is a priority in the UK, with new initiatives that empower children to live healthier lives. Excess weight has also been associated to worse outcomes during the COVID-19 pandemic period, complicated by reduced activity within the confinements of a home environment and coupled by increased screen time with remote classroom practices. As a result, children and young people now interact with computer interfaces in their home environment for education, gaming and healthcare purposes for prolonged periods and in new ways.MethodThere is a growing interest in Natural User Interfaces (NUIs) that use natural hand and body gestures to interact with computers. Advances to these technologies mean that they are now more accurate, easier to use and instead of requiring expensive depth cameras, can be operated using simple webcams. In this study, OpenCV library is used to track user movement by calculating the pixel difference between two frames and create a catalogue of exercises. We use PyTorch exercise recognition model to check the status of the user every 8 frames. These are recognised by using Convolutional Neural Networks (CNNs) with static training from datasets and offer users the option to create personalised exercises.ResultWe present University College London’s (UCL) Motion- Input supporting DirectX: Gestures for at-home exercises. This exercise module can recognise six repetitious static exercises, such as running on the spot, squatting, cycling on an exercise bike, and rowing on a rowing machine using a webcam. This is intended for integrated exercise triggers during gaming in place of a handheld control panel (i.e., jumping to trigger commands), remote coaching for fitness and bespoke treatment plans for physical rehabilitation.ConclusionWebcam-based computer vision exercise catalogues using everyday devices like webcams, hold the potential to encourage healthier and more active behaviours during screen-based activities.

Situated cognition 360° editor 2021: a solution for interactive medical training during the COVID-19 pandemic period

IntroductionImagine entering an operating theatre or developing clinical skills in empathy and communication through Virtual Reality. To enhance the experience of learning, novel methods using VR have been researched and simulated for clinicians. This is because some aspects of clinical training, like conducting procedures and effective team communication focus on ‘learning by doing’ which is difficult to recreate remotely. Here we present a proof-of-concept prototype of a 360°-video editor that augments 360° videos with media to create a mixed reality learning experience.MethodAn editor was built inside Unity to augment 360°-videos of real-world scenarios in healthcare with interactive data. Unity is a cross-platform games engine used to create two-dimension, three-dimension, virtual reality, and augmented reality games, as well as video players to play panoramic 360°-videos. The video player is attached to a Render Texture and a Skybox material that provides the spherical surface for the 360°-video achieving an immersive experience.ResultsThe editor comprises two software packages, one for the trainer, another for the learner. As a unique feature, we introduce clickable Hotspots. This enables users to annotate the 360° film by tagging specific artefacts in the environment and create a place-based interaction. These Hotspots are anchored to a position and can display text and images, and form part of a novel branched timeline of nested data. The intention being the trainer would create the film and annotate the environment with interactive media. This would then be available to the learner, who would use the player to view a bespoke teaching package.ConclusionSituated Cognition 360 Editor 2021 envisages trainers creating interactive 360°-video learning experiences using real life scenarios in healthcare. Future steps involve user experience evaluations, co-design and development of new learner interactions that deliver low cost, remote and easily deployed healthcare education through immersive learning environments.

Clinical perception of effectiveness of virtual appointments and comparison with appointment outcomes at a specialist children's hospital.

INTRODUCTION: A 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. METHODS: Clinicians 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. RESULTS: Ninety-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). CONCLUSION: The perception of clinicians is that virtual appointments enabled continuity of paediatric care with improved clinical assessment capability and attendance during video consultations compared with telephone consultations.