CC BY-NC-ND 4.0 · Appl Clin Inform 2020; 11(01): 190-199
DOI: 10.1055/s-0040-1703015
Research Article
Georg Thieme Verlag KG Stuttgart · New York

Data Model Requirements for a Digital Cognitive Aid for Anesthesia to Support Intraoperative Crisis Management

Stefanie Schild
1   Department of Medical Informatics, Biometrics and Epidemiology, Chair of Medical Informatics, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
,
Julian Gruendner
1   Department of Medical Informatics, Biometrics and Epidemiology, Chair of Medical Informatics, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
,
Christian Gulden
1   Department of Medical Informatics, Biometrics and Epidemiology, Chair of Medical Informatics, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
,
Hans-Ulrich Prokosch
1   Department of Medical Informatics, Biometrics and Epidemiology, Chair of Medical Informatics, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
,
Michael St Pierre
2   Department of Anesthesiology, University Hospital Erlangen, Erlangen, Germany
,
Martin Sedlmayr
3   Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
› Author Affiliations
Funding This research was supported by the Funk Stiftung (grant number RM-FS3–2017–1).
Further Information

Publication History

14 August 2019

19 January 2020

Publication Date:
11 March 2020 (online)

Abstract

Objective The aim of this study is to define data model requirements supporting the development of a digital cognitive aid (CA) for intraoperative crisis management in anesthesia, including medical emergency text modules (text elements) and branches or loops within emergency instructions (control structures) as well as their properties, data types, and value ranges.

Methods The analysis process comprised three steps: reviewing the structure of paper-based CAs to identify common text elements and control structures, identifying requirements derived from content, design, and purpose of a digital CA, and validating requirements by loading exemplary emergency checklist data into the resulting prototype data model.

Results The analysis of paper-based CAs identified 19 general text elements and two control structures. Aggregating these elements and analyzing the content, design and purpose of a digital CA revealed 20 relevant data model requirements. These included checklist tags to enable different search options, structured checklist action steps (items) in groups and subgroups, and additional information on each item. Checklist and Item were identified as two main classes of the prototype data model. A data object built according to this model was successfully integrated into a digital CA prototype.

Conclusion To enable consistent design and interactivity with the content, presentation of critical medical information in a digital CA for crisis management requires a uniform structure. So far it has not been investigated which requirements need to be met by a data model for this purpose. The results of this study define the requirements and structure that enable the presentation of critical medical information. Further research is needed to develop a comprehensive data model for a digital CA for crisis management in anesthesia, including supplementation of requirements resulting from simulation studies and feasibility analyses regarding existing data models. This model may also be a useful template for developing data models for CAs in other medical domains.

Protection of Human and Animal Subjects

Human and/or animal subjects were not included in the project.


 
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