Introduction
Continuous
monitoring of critically ill children is essential for the timely
identification of deteriorating vital signs. However, monitoring is often
intermittent in low-resource settings, affecting the quality of care. This
study assessed the implementation barriers and facilitators of a locally
adapted, robust, low-cost continuous monitoring system (IMPALA) in Malawi.
Methods
A mixed-method
implementation study of the IMPALA system in the paediatric High-dependency
unit of a tertiary hospital from November 2022 to October 2023. Data were
collected through over 300 hours of observations, in-depth interviews with 14
healthcare providers and nine caregivers of admitted children, and questionnaire-based
surveys from 24 healthcare providers and 72 caregivers. Qualitative data were
analysed thematically using inductive and deductive approaches. Descriptive
statistics (frequencies, percentages, means, and standard deviations) were calculated
for categorical and continuous variables.
Results
Healthcare providers and caregivers indicated that the
IMPALA monitors improved care by providing the ability to measure reliably multiple
vital signs, with long-lasting (4 hours) backup power and alarm provisions. Healthcare
providers reported spending less time on child monitoring after the
introduction of IMPALA (1.8 hours per day
pre-IMPALA (95% CI: 1.19-2.48) compared to 3.3 hours post-IMPALA (95% CI:
2.36-4.23; p <0.00). Still, they recognised alarm fatigue, limitations in
knowledge of the technology, and staff shortages as barriers to the use of
IMPALA. Some caregivers expressed concerns about the reliability of the
monitoring system.
Conclusion
The
continuous monitoring device was well-received overall by healthcare providers
and caregivers. It was perceived to save time and improve the quality of care.
Opportunities to further enhance engagement with the device include
strengthening caregivers’ knowledge and involvement to address their mistrust
or misconceptions about the device, minimising false alarms, and providing
ongoing training to healthcare providers so that new, existing, and rotating
staff know how to engage with the device. No formula was used to calculate the weights, apart from using STATA Response Rates: In total, 23 observations
and in-depth interviews (IDIs) were conducted at Zomba Central Hospital's
paediatric HDU, with healthcare providers (n = 14) and caregivers (n = 9) of
nine critically ill children (aged 3 months to 5 years old) admitted to the HDU. The sampling frame for the questionnaire-based
caregiver survey consisted of all caregivers of critically ill children aged
three months to five years who were admitted to
the HDU. The sampling frame for the questionnaire-based
healthcare provider survey comprised all healthcare workers (i.e., the complete
census of nurses and clinicians) working in the HDU. There was a 100% response rate among the caregivers and healthcare providers, as all participants were willing to share their experiences with the monitor's usage. Presence of Common Scales: None The sampling frame for the questionnaire-based
caregiver survey consisted of all caregivers of critically ill children aged
three months to five years who were admitted to
the HDU. The sampling frame for the questionnaire-based
healthcare provider survey comprised all healthcare workers (i.e., the complete
census of nurses and clinicians) working in the HDU from January to May 2023. We
estimated the minimum detectable effect size of the change in hours spent on
monitoring children before and after IMPALA for a sample of n = 24 healthcare workers, based on a one-sample mean t-test power calculation with α = 0.05, β = 0.80, and a standard deviation of 1.1025, to be 0.597. Though the sample
size was small, it was appropriate for the exploratory, early-stage nature of
this study. It was chosen to balance statistical power with feasibility in a
resource-constrained setting. Caregivers above 18 years old of critically ill children admitted to the high dependency unit
Healthcare providers above 18 years working in the high dependency unit. Smallest Geographic Unit: Zomba, Malawi face-to-face interview; web-based survey;