Development and use of a tablet-based resuscitation sheet for improving outcomes during intensive patient care

Wasif Bokahri, Vimla L. Patel, Ayan Sen, Ashish Amresh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Data documentation from resuscitation events in hospitals, termed 'code blue' events, utilizes a paper form, which is institutionspecific. Problems with data capture and transcription exists, due to the challenges of dynamic documentation of patient, event and outcome variables as the code blue event unfolds. We hypothesize that an electronic version of code blue real-Time data capture would lead to improved resuscitation data transcription, and enable clinicians to address deficiencies in quality of care. To this effect, we present the design of a tablet-based application and its use by 20 nurses at the Mayo Clinic hospital. The results showed that the nurses preferred the tablet application over the paper based form. Furthermore, a qualitative survey showed the clinicians perceived the electronic version to be more accurate and efficient than paper-based documentation, both of which are essential for an emergency code blue resuscitation procedure.

Original languageEnglish (US)
Title of host publicationDH 2016 - Proceedings of the 2016 Digital Health Conference
PublisherAssociation for Computing Machinery, Inc
Pages17-21
Number of pages5
ISBN (Print)9781450342247
DOIs
StatePublished - Apr 11 2016
Event6th International Conference on Digital Health, DH 2016 - Montreal, Canada
Duration: Apr 11 2016Apr 13 2016

Other

Other6th International Conference on Digital Health, DH 2016
CountryCanada
CityMontreal
Period4/11/164/13/16

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Keywords

  • Intensive Care
  • Resuscitation
  • Tablet applications

ASJC Scopus subject areas

  • Health Information Management
  • Computer Science Applications
  • Health Informatics

Cite this

Bokahri, W., Patel, V. L., Sen, A., & Amresh, A. (2016). Development and use of a tablet-based resuscitation sheet for improving outcomes during intensive patient care. In DH 2016 - Proceedings of the 2016 Digital Health Conference (pp. 17-21). Association for Computing Machinery, Inc. https://doi.org/10.1145/2896338.2896362