{Reference Type}: Journal Article
{Title}: Improving the introduction of telemedicine in pre-hospital emergency medicine: understanding users and how acceptability, usability and effectiveness influence this process.
{Author}: O'Sullivan S;Krautwald J;Schneider H;
{Journal}: BMC Emerg Med
{Volume}: 24
{Issue}: 1
{Year}: 2024 Jul 12
{Factor}: 2.485
{DOI}: 10.1186/s12873-024-01034-6
{Abstract}: <B>BACKGROUND: </B>Increasing numbers of ambulance calls, vacant positions and growing workloads in Emergency Medicine (EM) are increasing the pressure to find adequate solutions. With telemedicine providing health-care services by bridging large distances, connecting remote providers and even patients while using modern communication technologies, such a technology seems beneficial. As the process of developing an optimal solution is challenging, a need to quantify involved processes could improve implementation. Existing models are based on qualitative studies although standardised questionnaires for factors such as Usability, Acceptability and Effectiveness exist.<BR><B>METHODS: </B>A survey was provided to participants within a German county. It was based on telemedical surveys, the System Usabilty Scale (SUS) and earlier works describing Usability, Acceptability and Effectiveness. Meanwhile a telemedical system was introduced in the investigated county. A comparison between user-groups aswell as an exploratory factor analysis (EFA) was performed.<BR><B>RESULTS: </B>Of n = 91 included participants n = 73 (80,2%) were qualified as emergency medical staff (including paramedics n = 36 (39,56%), EMTs n = 28 (30,77%), call handlers n = 9 (9,89%)) and n = 18 (19,8%) as emergency physicians. Most participants approved that telemedicine positively impacts EM and improved treatment options with an overall Usabilty Score of 68,68. EFA provided a 3-factor solution involving Usability, Acceptability and Effectiveness.<BR><B>CONCLUSIONS: </B>With our results being comparable to earlier studies but telemedicine only having being sparsely introduced, a positive attitude could still be attested. While our model describes 51,28% of the underlying factors, more research is needed to identify further influences. We showed that Usability is correlated with Acceptability (strong effect), Usability and Effectiveness with a medium effect, likewise Acceptability and Effectiveness. Therefore available systems need to improve. Our approach can be a guide for decision makers and developers, that a focus during implementation must be on improving usability and on a valid data driven implementation process.