Management of a critical downtime event involving integrated electronic health record

Dave, Keyur, Boorman, Rhonda J., and Walker, Rachel M. (2020) Management of a critical downtime event involving integrated electronic health record. Collegian, 27. pp. 542-552.

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Abstract

Background: There are few descriptions of management of unplanned hospital-wide digital downtime and impact on patient care in health literature.

Aim: The aim of this study was to undertake a qualitative review of a prolonged critical technology downtime event in an Australian hospital in 2017.

Methods: Inductive content analysis was conducted on data collected through face-to-face, semi-structured, individual interviews conducted with nine hospitals employees (five nurses with direct-care/operational responsibilities, and four executive staff, including nursing) who played a role in the incident.

Findings: Analysis of the data using an open-source R package led to the extraction of 139 codes, 13 first-level categories, and 4 main categories. Main categories extracted were: impact of event, response to the event, resilience and institutional reserve, and challenges and learnings.

Discussion: The overall experience for interview participants was positive. Effective communication methods, particularly vertical communication, enabled multi-disciplinary teams (comprising nursing, medical and pharmacy personnel) to safely transition back from downtime paper records to the integrated electronic health record with no harm to patients. Participants identified teamwork contributed to a sense of comradery with clinical colleagues and executive staff. Contingency planning and training are essential for ensuring safe and effective management of technology downtime events.

Conclusion: The prolonged digital disruption and subsequent recovery was managed effectively using a face-to-face communication and support approach. This approach reduced the impact of the digital downtime and ensured patient safety. The data analysis strategy was enhanced using an computer-assisted qualitative data analysis software.

Item ID: 84226
Item Type: Article (Research - C1)
ISSN: 1322-7696
Copyright Information: © 2020 Australian College of Nursing Ltd. Published by Elsevier Ltd. Accepted Version: This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Date Deposited: 04 Dec 2024 02:16
Downloads: Total: 3
Last 12 Months: 3
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