Failure mode and effect analysis (FMEA) to identify and mitigate failures in a hospital rapid response system (RRS)

Ehsan Ullah; Mirza Mansoor Baig; Hamid GholamHosseini; Jun Lu

doi:10.1016/j.heliyon.2022.e08944

Failure mode and effect analysis (FMEA) to identify and mitigate failures in a hospital rapid response system (RRS)

Heliyon. 2022 Feb 11;8(2):e08944. doi: 10.1016/j.heliyon.2022.e08944. eCollection 2022 Feb.

Authors

Ehsan Ullah^{1

2}, Mirza Mansoor Baig³, Hamid GholamHosseini³, Jun Lu^{1

4

5

6

7}

Affiliations

¹ School of Science, Faculty of Health and Environmental Sciences, Auckland University of Technology, Private Bag 92006, Auckland 1142, New Zealand.
² Clinical Governance Support Unit, Taranaki District Health Board, Private Bag Private Bag 2016, New Plymouth 4342, New Zealand.
³ School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Private Bag 92006, Auckland 1142, New Zealand.
⁴ School of Public Health and Interdisciplinary Studies, Faculty of Health and Environmental Sciences, Auckland University of Technology, New Zealand.
⁵ Maurice Wilkins Centre for Molecular Discovery, Auckland 1010, New Zealand.
⁶ College of Food Science and Technology, Nanchang University, Nanchang 330031, Jiangxi Province, China.
⁷ College of Food Engineering and Nutrition Sciences, Shaanxi Normal University, Xi'an 710119, Shaanxi Province, China.

Abstract

We performed FMEA on the existing RRS with the help of routine users of the RRS who acted as subject matter experts and evaluated the failures for their criticality using the Risk Priority Number approach based on their experience of the RRS. The FMEA found 35 potential failure modes and 101 failure mode effects across 13 process steps of the RRS. The afferent limb of RRS was found to be more prone to these failures (62, 61.4%) than the efferent limb of the RRS (39, 38.6%). Modification of calling criteria (12, 11.9%) and calculation of New Zealand Early Warning Scores (NZEWS) calculation (11, 10.9%) steps were found to potentially give rise to the highest number of these failures. Causes of these failures include human error and related factors (35, 34.7%), staff workload/staffing levels (30, 29.7%) and limitations due to paper-based charts and organisational factors (n = 30, 29.7%). The demonstrated electronic system was found to potentially eliminate or reduce the likelihood of 71 (70.2%) failures. The failures not eliminated by the electronic RRS require targeted corrective measures including scenario-based training and education, and revised calling criteria to include triggers for hypothermia and high systolic blood pressure.

Keywords: Clinical deterioration; Early warning score; Failure modes and effects analysis; Rapid response system; Vital signs.