Improving Safety of Intrahospital Transport of Critically Ill Patients
CCCF ePoster library. Maude Peretz-Larochelle J. Nov 8, 2018; 233417
Ms. Julie Moore and Maude Peretz-Larochelle
Ms. Julie Moore and Maude Peretz-Larochelle
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Abstract
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Introduction: Intrahospital (IH) transfer of critically ill patients is associated with risks. However, current guidelines for transport safety are not widely adopted. Evidence from the literature suggests team composition and experience, proper equipment utilization, role clarification, and strong team communication prevent adverse events and thus create a safer environment for critically ill patients during IH transport [1,2].

 

Objective: We believe that change initiatives generated through quality improvement (QI) methodology will improve the safety of IH transport of critically ill patients. We hypothesize that the implementation of these QI initiatives will decrease adverse patient events (AE), provide safer patient transports, and improve comfort of the team of healthcare transport professionals (HCP).

 

Methods: We are conducting a prospective observational QI study of consecutive IH transports of critically ill patients at Mount Sinai Hospital in Toronto, Canada. The study consists of 3 components: (1) baseline questionnaire of HCP establishing the current state of and perspectives surrounding IH transfer safety, (2) development and implementation of a QI intervention aimed at addressing issues highlighted, and (3) post-implementation questionnaire of HCP perception of IH transfer safety. We will apply QI methodology (Plan-Do-Study-Act cycles) until 80% compliance with our intervention is achieved. The primary outcome measure is the HCP perception of transfer safety, evaluated using a Likert scale. The secondary outcome measure is adverse patient events. The balancing measures we are tracking include increased delays to IH transport and HCP satisfaction. Our analysis will be done using descriptive statistics to analyze pre- and post-intervention questionnaire responses. The pre- and post-intervention results will be compared using the chi-square statistic for dichotomous variables. The absolute risk reduction and its confidence interval will also be calculated.

 

Results: At the time of submission, we have analyzed 45 patient transfers in the first phase of our study. Our incidence of AE was 30/45 (67%). Eleven patient transfers had more than one documented AE resulting in a total of 44 AE. 41/44 (93%) AE were preventable and can be divided into the following categories: system problems, equipment problems, delays in transport, and medication issues. Of the 45 transfers, 20 (44%) were perceived as unsafe by the medical team. Discordance regarding perceived safety between healthcare professionals occurred in only 5/45 (11%) transports. Using a fishbone diagram, we are developing change initiatives to target the above mentioned categories.  Currently,  a transport safety checklist is hypothesized to address all baseline AE categories. The next phase of the study consists of deploying our initiative. We will continue to track AE, compliance, and our balancing measures as we implement our checklist. We will compare the results from our post-intervention questionnaire to our pre-intervention results.

*Results are current at the time of abstract composition and will be updated as the study progresses.



Conclusion: Most adverse events on IH transport are preventable. We hypothesize that our QI intervention will decrease AE during IH transport of critically ill patients and improve safety as perceived by HCP. Should the intervention be effective, it ought to be considered for validation in other critical care units.


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