Methods
Study design
A contextual inquiry methodological approach was used, including
observations and semi-structured interviews informed by the Systems
Engineering Initiative for Patient Safety (SEIPS)
model.10 The SEIPS model provides a framework to
understand work systems, processes and outcomes in health care and has
been used extensively in patient safety and AMS
research.11,12
This study was approved by the Hospital’s Human Research Ethics
Committee (2020/ETH02859). The Consolidated Criteria for Reporting
Qualitative Research (COREQ) Checklist13 was followed
for the methodology and reporting of this study.
Setting
This study was performed at two metropolitan public teaching hospitals
within the same local health district in New South Wales, Australia.
Hospital A has 750-beds and Hospital B has 1000-beds. Both hospitals
have an AMS team comprised of consultant and trainee infectious diseases
(ID) and/or microbiology doctors and a senior clinical pharmacist.
Restricted antimicrobials require approval from the AMS team.
Both hospitals use the same eMMS (Cerner Millennium®) with the exception
of the ICU at Hospital B, which uses IntelliSpace Critical Care and
Anaesthesia (Koninklijke Philips N.V©). The Cerner
Millennium eMMS was implemented at Hospital A in May 2015 and Hospital B
in September 2017. The hospitals have also implemented a clinical
dashboard, Live AMS, into the Cerner eMMS in October 2017, with new
features added in the subsequent years. Live AMS allows clinicians to
view all patients on antimicrobials, including medication order
information such as prescriber, indication and date of prescription.
Patients can be filtered using these categories. AMS team
representatives from the local health district were consulted during
development of Live AMS and were involved in the implementation of the
tool at their respective hospitals.
Participants
Purposive sampling was used to recruit participants for observations and
interviews, with doctors and pharmacists involved in conducting AMS
tasks invited by email. Study participation was voluntary and no
compensation was provided. Written consent was obtained for in-person
observations and interviews. Verbal consent was obtained for
video-conferencing sessions.
Data collection
Data was collected between May 2021 and August 2022. During this time
COVID-19 restrictions imposed by the government and hospital executives
restricted researcher entry into hospitals. Consequently, observations
were conducted through video-conference, and in-person once restrictions
were lifted. Clinician(s) were observed for a maximum of 2 hours at a
time. Multidisciplinary AMS team meetings were also observed. During the
observations, the researcher would occasionally ask participants to
explain what they were doing. The researcher took handwritten notes with
a focus on all elements of the work system (i.e. SEIPS), including
tools, tasks and people involved. Observations ceased when thematic
saturation was reached.
Interviews were conducted after observations. A semi-structured
interview guide (Appendix 1) was developed by the research team who have
expertise in qualitative research, human factors, pharmacy and clinical
informatics. The interview guide was piloted with doctors to ensure
understanding. Interviews were conducted in-person or through
videoconference, audio-recorded and transcribed verbatim.
Observations and interviews were conducted by a researcher (XX) with
previous qualitative research experience. XX was not known to the
participants prior to commencing the research and was not employed by
the hospitals.
Data analysis
Researchers met periodically throughout data collection to discuss
observations and interviews. Observation notes and interviews were
analysed using an inductive content analysis approach as per the
framework method.14 Two researchers (BV, MB)
independently coded the first three interview transcripts and met to
discuss and reach consensus on codes. The remaining interviews were
coded by one researcher (BV) using this framework. Observation notes
were coded by one researcher (BV). After inductive coding, themes from
interviews and observations were deductively mapped to the SEIPS model.
A second researcher (MB) reviewed all transcripts and coding for
accuracy and consistency.