Nurses’ use of early warning system vital signs observation charts in rural, remote and regional healthcare settings
Creators: name: Augutis, Wendy
Publisher: name: CQUniversity
Year: 2023
Subjects: Health and community services

description: Abstract Background Unrecognised patient deterioration in acutely ill hospital patients is a widely acknowledged problem. Early recognition of physiological derangements has resulted in reduced preventable adverse patient outcomes. The development and introduction of early warning systems (EWS) into hospital settings have been implemented as an initiative to address early detection of patient deterioration. Early warning systems comprise of a patient vital sign monitoring tool and escalation of care response protocol. While EWS have been implemented in all Australian healthcare facilities, little is known about nurses’ use of EWS in the rural and remote hospital context. Research question How are Early Warning System vital signs observation charts utilised by nurses in rural and remote healthcare settings? Method A retrospective chart review of EWS vital signs observation charts was undertaken to address the research question. The Gearing framework provided the methodology to guide the retrospective chart audit. The nine step Gearing framework for conducting a retrospective chart review approach included: conception of research, literature review, proposal development, data abstraction, development of protocols and guidelines for abstraction, sample, ethics, and pilot study. Queensland Adult Deterioration Detection (Q-ADDS) vital sign observation charts from 204 patients admitted to seven rural and remote Queensland Health facilities were examined. The patients were categorised into two groupings; Group 1 – patients who suffered a clinical ii deterioration event and were transferred to a larger facility for higher acute care (104 patients), and Group 2 - patients discharged home after an uneventful hospital stay (100 patients). The patients from groups 1 and 2 were demographically and diagnostically matched by approximate age, gender, hospital facility, and admitting diagnosis. All sets of vital signs collected over the 24- hour period prior to patient transfer or discharge were used in this study. The vital sign data collected were blood pressure (BP), heart rate (HR), respiratory rate (RR), oxygen saturation level (SaO2), supplementary oxygen flow rate (O2 flow rate), temperature and level of consciousness (LOC). Additional data collected included vital sign observation monitoring frequency, vital sign omissions, and the accuracy of the calculated aggregated EWS score as well as patient demographic data. Using a coding system, compliance with chart completion protocols for the use of numbers, dots, corrected writing, and BP arrows and dashes were also recorded to facilitate recognition of trends according to human factors principles. The quantitative data were statistically analysed using IBM SPSS Statistics Version 26. The demographic and diagnosis data were analysed using simple descriptive statistics. The Levene’s t-test at 95% confidence level (p &lt; .05) was used to establish differences between the patient groups, Groups 1 and 2. Relationships between variables, such as the number of patient monitoring events and the completeness of documentation, were analysed using Pearson’s correlation coefficient (r) to assess the direction and association between variables. The qualitative data, such as the presence of unwarranted notations, was statistically analysed by categorising the data prior to analysis.