Speech-based Documentation in Emergency Medical Services with the Electronic Language Interface for Ambulance Services

Meier, Lea; Bauer, Jan Gabriel; Denecke, Kerstin (2020). Speech-based Documentation in Emergency Medical Services with the Electronic Language Interface for Ambulance Services In: 2020 IEEE International Conference on Healthcare Informatics (ICHI) (pp. 1-6). IEEE 10.1109/ICHI48887.2020.9374336

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Emergency medical services (EMS) assume a leading role in case of an emergency: They provide the professional preclinical care on site and decide on the further treatment of the patient. In order to trace the treatment process of the patient after a rescue operation, information such as drug administration are documented in an operation protocol. Such documentation is often done following the rescue operation. Due to the high psychological strain and stress, the retrospective documentation is error-prone. In Switzerland, about 80% of EMS use paper-based protocols. While electronic protocols ensure data sharing to third-party systems, no process improvements are guaranteed. In a Wizard-of-Oz experiment with speculative design, we investigated how media can support paramedics in the documentation process. Since voice records were evaluated as a promising tool in that study, ELIAS, the Electronic Language Interface for Ambulance Services was developed. ELIAS is based on a digital emergency protocol and allows paramedics to use a speech-based user interface to document measurements at the time when they are performed. We run tests to study the word error rate during transcription in different settings. Furthermore, an analysis with ambient noise has been performed. The results let us conclude that once implemented in daily practice, ELIAS has the potential of increasing the semantic and time-related accuracy of emergency protocol data.

Item Type:	Conference or Workshop Item (Paper)
Division/Institute:	School of Engineering and Computer Science > Institute for Patient-centered Digital Health School of Engineering and Computer Science
Name:	Meier, Lea; Bauer, Jan Gabriel and Denecke, Kerstin
Subjects:	R Medicine > R Medicine (General) T Technology > T Technology (General)
ISSN:	2575-2634
ISBN:	978-1-7281-5382-7
Publisher:	IEEE
Language:	English
Submitter:	Kerstin Denecke
Date Deposited:	16 Mar 2021 14:49
Last Modified:	25 Oct 2023 14:15
Publisher DOI:	10.1109/ICHI48887.2020.9374336
ARBOR DOI:	10.24451/arbor.14501
URI:	https://arbor.bfh.ch/id/eprint/14501