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Evaluation of an audit and feedback intervention to reduce gentamicin prescription errors in newborn treatment (ReGENT) in neonatal inpatient care in Kenya: a controlled interrupted time series study protocol

Abstract:
Background
Medication errors are likely common in low- and middle-income countries (LMICs). In neonatal hospital care where the population with severe illness has a high mortality rate, around 14.9% of drug prescriptions have errors in LMICs settings. However, there is scant research on interventions to improve medication safety to mitigate such errors. Our objective is to improve routine neonatal care particularly focusing on effective prescribing practices with the aim of achieving reduced gentamicin medication errors.
Methods
We propose to conduct an audit and feedback (A&F) study over 12 months in 20 hospitals with 12 months of baseline data. The medical and nursing leaders on their newborn units had been organised into a network that facilitates evaluating intervention approaches for improving quality of neonatal care in these hospitals and are receiving basic feedback generated from the baseline data. In this study, the network will (1) be expanded to include all hospital pharmacists, (2) include a pharmacist-only professional WhatsApp discussion group for discussing prescription practices, and (3) support all hospitals to facilitate pharmacist-led continuous medical education seminars on prescription practices at hospital level, i.e. default intervention package. A subset of these hospitals (n = 10) will additionally (1) have an additional hospital-specific WhatsApp group for the pharmacists to discuss local performance with their local clinical team, (2) receive detailed A&F prescription error reports delivered through mobile-based dashboard, and (3) receive a PDF infographic summarising prescribing performance circulated to the clinicians through the hospital-specific WhatsApp group, i.e. an extended package.
Using interrupted time series analysis modelling changes in prescribing errors over time, coupled with process fidelity evaluation, and WhatsApp sentiment analysis, we will evaluate the success with which the A&F interventions are delivered, received, and acted upon to reduce prescribing error while exploring the extended package’s success/failure relative to the default intervention package.
Discussion
If effective, these theory-informed A&F strategies that carefully consider the challenges of LMICs settings will support the improvement of medication prescribing practices with the insights gained adapted for other clinical behavioural targets of a similar nature.
Trial registration
PACTR, PACTR202203869312307. Registered 17th March 2022.
Publication status:
Published
Peer review status:
Peer reviewed

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Files:
Publisher copy:
10.1186/s13012-022-01203-w

Authors


More by this author
Institution:
University of Oxford
Division:
SSD
Department:
Education
Oxford college:
Kellogg College
Role:
Author
ORCID:
0000-0002-7915-3004
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Institution:
University of Oxford
Department:
External
Role:
Author
ORCID:
0000-0002-0851-3711
More by this author
Role:
Author
ORCID:
0000-0003-1533-9800

Contributors


Publisher:
BioMed Central
Journal:
Implementation Science More from this journal
Volume:
17
Issue:
1
Article number:
32
Place of publication:
England
Publication date:
2022-05-16
Acceptance date:
2022-04-10
DOI:
EISSN:
1748-5908
Pmid:
35578243


Language:
English
Keywords:
Pubs id:
1260515
Local pid:
pubs:1260515
Deposit date:
2023-06-21

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