Pilot implementation of an electronic diagnostic support tool (AiD‐DST) designed to identify the cause(s) of delirium
Elizabeth Leong, Stephane Chang, Kristi Yearwood, Eamonn Eeles, Stephanie Yerkovich, Carolina Ling, Andrew Teodorczuk, Nadeeka DissanayakaAbstract
Objective(s)
The identification of cause(s) of delirium remains a clinical challenge within medicine. Our group have previously successfully developed and tested the Aetiology in Delirium—Decision Support Tool (AiD‐DST). The AiD‐DST is designed to help medical professionals close the gap on the detection of cause(s) of delirium. Here, we report on use of AiD‐DST in the real‐world setting.
Methods
A real‐world implementation study of the AiD‐DST within a general medical ward of a metropolitan hospital was conducted over a 10‐week period. A mixed method evaluation was performed based upon the RE‐AIM Framework that incorporates reach, effectiveness, adoption, implementation and maintenance of an intervention.
Results
Reach: fifty‐three out of 87 (61%) eligible doctors consented to participation in the study. Effectiveness: A mean of 4.3 diagnoses were generated per patient with no difference in frequency when compared with historical control (z = 1.36; p = .17). Average usability score was 5.86 (SD = 1.15) on a 7‐point scale, with 93% of respondents being satisfied with the AiD‐DST. Free text feedback comprised themes of accessibility, ergonomics, diagnostic accuracy and applicability of AiD‐DST to related conditions. Implementation: Instrument completion rate was 98% (n = 49/50), with a median completion time of 90 s. Maintenance: Sixty‐seven % of uses of AiD‐DST occurred in the second half of the study (p = .3). Following the initiation period there was an increase in use (r = .79; p = 02).
Conclusion
Proof of principle was demonstrated for local implementation of a diagnostic support tool (AiD‐DST).