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We aimed to determine the feasibility of quality indicators (QIs) for prehospital advanced airway management (PAAM) from a provider point of view.
The study is a survey based feasibility assessment following field testing of QIs for PAAM.
The study was performed in two physician staffed emergency medical services in Switzerland.
42 of the 44 emergency physicians who completed at least one case report form (CRF) dedicated to the collection of the QIs on PAAM between 1 January 2019 and 31 December 2021 participated in the study.
The data required to calculate the 17 QIs was systematically collected through a dedicated electronic CRF.
Primary outcomes were provider-related feasibility criteria: relevance and acceptance of the QIs, as well as reliability of the data collection. Secondary outcomes were effort to collect specific data and to complete the CRF.
Over the study period, 470 CRFs were completed, with a median of 11 per physician (IQR 4–17; range 1–48). The median time to complete the CRF was 7 min (IQR 3–16) and was considered reasonable by 95% of the physicians. Overall, 75% of the physicians assessed the set of QIs to be relevant, and 74% accepted that the set of QIs assessed the quality of PAAM. The reliability of data collection was rated as good or excellent for each of the 17 QIs, with the lowest rated for the following 3 QIs: duration of preoxygenation, duration of laryngoscopy and occurrence of desaturation during laryngoscopy.
Collection of QIs on PAAM appears feasible. Electronic medical records and technological solutions facilitating automatic collection of vital parameters and timing during the procedure could improve the reliability of data collection for some QIs. Studies in other services are needed to determine the external validity of our results.
by Richard Gebler, Martin Lehmann, Maik Löwe, Mirko Gruhl, Markus Wolfien, Miriam Goldammer, Franziska Bathelt, Jens Karschau, Andreas Hasselberg, Veronika Bierbaum, Toni Lange, Katja Polotzek, Hanns-Christoph Held, Michael Albrecht, Jochen Schmitt, Martin Sedlmayr
BackgroundThe COVID-19 pandemic revealed a need for better collaboration among research, care, and management in Germany as well as globally. Initially, there was a high demand for broad data collection across Germany, but as the pandemic evolved, localized data became increasingly necessary. Customized dashboards and tools were rapidly developed to provide timely and accurate information. In Saxony, the DISPENSE project was created to predict short-term hospital bed capacity demands, and while it was successful, continuous adjustments and the initial monolithic system architecture of the application made it difficult to customize and scale.
MethodsTo analyze the current state of the DISPENSE tool, we conducted an in-depth analysis of the data processing steps and identified data flows underlying users’ metrics and dashboards. We also conducted a workshop to understand the different views and constraints of specific user groups, and brought together and clustered the information according to content-related service areas to determine functionality-related service groups. Based on this analysis, we developed a concept for the system architecture, modularized the main services by assigning specialized applications and integrated them into the existing system, allowing for self-service reporting and evaluation of the expert groups’ needs.
ResultsWe analyzed the applications’ dataflow and identified specific user groups. The functionalities of the monolithic application were divided into specific service groups for data processing, data storage, predictions, content visualization, and user management. After composition and implementation, we evaluated the new system architecture against the initial requirements by enabling self-service reporting to the users.
DiscussionBy modularizing the monolithic application and creating a more flexible system, the challenges of rapidly changing requirements, growing need for information, and high administrative efforts were addressed.
ConclusionWe demonstrated an improved adaptation towards the needs of various user groups, increased efficiency, and reduced burden on administrators, while also enabling self-service functionalities and specialization of single applications on individual service groups.
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