Simulation in New Zealand: what have you done for me lately? New Zealand Association for Simulation in Healthcare (NZASH) white paper.

Medical simulation has become an integral aspect of modern healthcare education and practice. It has evolved to become an essential aspect of teaching core concepts and skills, common and rare presentations, algorithms and protocols, communication, interpersonal and teamworking skills and testing new equipment and systems. Simulation-based learning (SBL) is useful for the novice to the senior clinician. Healthcare is a complex adaptive system built from very large numbers of mutually interacting subunits (e.g., different professions, departments, equipment). These subunits generate multiple repeated interactions that have the potential to result in rich, collective behaviour that feeds back into the organisation. There is a unique opportunity in New Zealand with the formation of Te Whatu Ora - Health New Zealand and Te Aka Whai Ora - Maori Health Authority and the reorganisation of the healthcare system. This viewpoint is a white paper for the integration of SBL into our healthcare system. We describe our concerns in the current system and list our current capabilities. The way SBL could be implemented in pre- and post-registration phases of practice are explored as well as the integration of communication and culture. Interprofessional education has been shown to improve outcomes and is best done with an interprofessional simulation curriculum. We describe ways that simulation is currently used in our system and describe other uses such as quality improvement, safety and systems engineering and integration. The aim of this viewpoint is to alert Te Whatu Ora and Te Aka Whai Ora of the existing infrastructure of the simulation community in New Zealand and encourage them to invest in its future.

Exploring the feasibility of smartglass facilitated remote supervision in the emergency department: A simulation study.

OBJECTIVE: Smartglasses are a wearable computer technology that has potential to facilitate remote supervision to junior doctors working in different clinical settings. The present study aimed to explore the feasibility of smartglass technology to enable remote supervision of junior clinicians by senior clinicians during emergency simulation scenarios. METHODS: This was a feasibility simulation study using high-fidelity mannequins and standardised patients. Trainee interns (TIs) and supervising clinicians (SCs) were invited to participate in two scenarios: a trauma case and a stroke case. There was a pre-sim questionnaire. The TI wore the smartglasses in a simulated ED bay and performed patient assessment and management. Remote supervision was provided by the SC via a livestream on a remote computer. Upon completion, participants completed a survey regarding their experience comprising of Likert scale and free-text questions. RESULTS: Fifteen TIs and 19 SCs participated. In general feedback from TIs and SCs was positive. TIs were able to identify and treat the key diagnostic problems set during the scenarios. Free-text survey responses provided specific feedback about what did and did not work when using the glasses. CONCLUSION: The present study demonstrates that smartglasses facilitated remote assistance has promise as an emergent technology and warrants further investigation in simulated and non-simulated environments.

Where can you wear your Libre? Using the FreeStyle Libre continuous glucose monitor on alternative sites.

AIM: To investigate the accuracy and acceptability of the FreeStyle Libre Flash continuous glucose monitoring system (FSL-CGM) at alternative sites during free living and under experimental conditions. MATERIALS AND METHODS: Participants with type 1 diabetes were provided with three FSL-CGM sensors applied to the upper arm, the lower back, and the anterior chest. On day 2 or 3, FSL-CGM sensor glucose was compared with venous glucose following a standard meal, during and after an exercise test, and after skin cooling. Participants completed 14-day use of the sensors with concomitant sensor scanning at all sites and capillary glucose tests. The primary outcome was accuracy between sensor sites of 14-day mean glucose. Clarke's error grids, precision absolute relative deviation, and mean absolute relative deviation were calculated. RESULTS: In the 20 participants, compared with the arm sensor, the accuracy of the back sensor and the chest sensor was 97.9% and 98%, respectively. Under experimental conditions, the arm sensor was more accurate than that of the back and chest. All the sensors recorded higher glucose concentration than venous samples during exercise. The arm and chest sites were most preferred, with the greatest sensor failures from the back. CONCLUSIONS: The FSL-CGM is clinically accurate when the sensors are applied to alternate chest or back sites. Greater variability occurs during rapid changes in glucose concentration with all sensor sites compared with venous glucose. Understanding these variabilities allows appropriate use of an economically viable continuous glucose monitor.