gms | German Medical Science

63. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS)

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie

02. - 06.09.2018, Osnabrück

The AcuWave Software Suite: introducing a medical research tool to a productive environment

Meeting Abstract

Suche in Medline nach

  • Henning Begerau - AMP Lab, Department of Anesthesiology & Intensive Care Medicine, University of Bonn Medical Center, Bonn, Deutschland
  • Maximilian Oremek - AMP Lab, Department of Anesthesiology & Intensive Care Medicine, University of Bonn Medical Center, Bonn, Deutschland
  • Andreas Hoeft - Department of Anesthesiology & Intensive Care Medicine, University of Bonn Medical Center, Bonn, Deutschland
  • Sven Zenker - AMP Lab, Department of Anesthesiology & Intensive Care Medicine, University of Bonn Medical Center, Bonn, Deutschland

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. 63. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS). Osnabrück, 02.-06.09.2018. Düsseldorf: German Medical Science GMS Publishing House; 2018. DocAbstr. 280

doi: 10.3205/18gmds171, urn:nbn:de:0183-18gmds1717

Veröffentlicht: 27. August 2018

© 2018 Begerau et al.
Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). Lizenz-Angaben siehe http://creativecommons.org/licenses/by/4.0/.


Gliederung

Text

Introduction: User expectations in both research and clinical use have evolved rapidly, driven by the availability of big-data algorithms in research and intuitive mobile devices in routine settings, with requirements from both worlds converging in translational research. When evaluating current off-the-shelf products, it became obvious that available software for data acquisition, processing, and visualisation of physiological monitoring data in acute care settings is not meeting expectations in either field, leading to the decision to start the development of the AcuWave software project [1].

Its key distinguishing feature is the seamless modular integration of user-developed analyses that can access all available data from multiple sources and share a standardised state-of-the art HTML5 user interface [2]. The integration into existing infrastructure and focussing on medical personnel as primary users requires different approaches to design, end-user communication, and support, and poses regulatory, technical, and administrative challenges compared to systems used in a research environment.

Here, we describe our experiences in transferring the AcuWave framework from the research environment into production use as a campus-wide data tool integrated into the existing patient data management software (PDMS).

Methods: The targeted goals were set by evaluating the work of doctoral students using existing medical data [3].

Medical data is sensitive and subject to many regulations and restrictions. To guarantee safety and privacy, AcuWave uses established enterprise authentication services. The data protection concept required by applicable regulations was verified by the institutional data protection officer and roll-out was consented by the employee representation councils. The software was then integrated into the existing PDMS, allowing the user to work directly in the context of the current documentation environment. A logging and monitoring solution [4] was installed to provide error notifications and usage analysis to improve the software quality and stability.

A usability evaluation was conducted to quantify to which extent the implementation met previously defined objectives.

Results: The time and resources needed to transfer a solution developed in a research context into productive clinical environments requirements are often underestimated. Getting clearance from administration, workers’ representation and data protection officials involved actions which took more than four months to complete. Delays induced were significant, although overall effort invested was manageable at less than 10% of technical development efforts required for system integration.

A persisting issue is the necessity to prevent the use for diagnostic or therapeutic purposes as the software is not a certified medical device. User training proved to be vital to the success of non-essential software.

Discussion: AcuWave was added successfully to the toolkit available to clinicians for daily use, demonstrating that roll-out and maintenance of a software developed in a research context into a production environment is feasible. The usage statistics increase but evaluation showed that few users are responsible for the majority of user interactions. Further training and information will be necessary to increase awareness of this tool. Secondary use for scientific purposes is provided in the same environment, ensuring that regulatory requirements are met and the entrance barrier to using the software is lowered.

The authors declare that they have no competing interests.

The authors declare that an ethics committee vote is not required.


References

1.
Zenker S, Begerau H, Thull B. Modular decoupling of data acquisition from analysis and visualization in acute care monitoring to facilitate evaluation and implementation of new derived parameters and visualization techniques: concept and prototype implementation. Oral presentation, European Society for Computing and Technology in Anesthesia and Intensive Care (ESCTAIC) Annual Meeting 2011. Nürnberg, Germany. Journal of Clinical Monitoring and Computing. 2012;25:232.
2.
Begerau H, Oremek M, Hoeft A, Zenker S. The AcuWave Software Suite: a modular analysis and visualisation tool to facilitate the evaluation of derived parameters for researchers and clinicians in acute care. In: Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie, Hrsg. 62. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS). Oldenburg, 17.-21.09.2017. Düsseldorf: German Medical Science GMS Publishing House; 2017. DocAbstr. 254.
3.
Oremek M, Kiefer N, Hoeft A, Zenker S. Estimation of Properties of the Heart from beat-to-beat Pulse Pressure Variations in Atrial Fibrillation Using a Mechanistic Mathematical Model: Insights from Inference with Full Uncertainty Quantification. Journal of Critical Care. 2017;38:368-69.
4.
Graylog. Open Source Log Management. Available from: https://www.graylog.org Externer Link