Evidence map›Paper›PMID 30258654›Full record

ArticleBMJ global health2018

Using a common data platform to facilitate audit and feedback on the quality of hospital care provided to sick newborns in Kenya.

Michuki Maina, Jalemba Aluvaala, Paul Mwaniki, Olga Tosas-Auguet, Catherine Mutinda, Beth Maina, Constance Schultsz, Mike English

Abstract read
In one paragraph

Article in BMJ global health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Michuki MainaHealth Services Unit, KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya.
Jalemba AluvaalaHealth Services Unit, KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya.
Paul MwanikiHealth Services Unit, KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya.
Olga Tosas-AuguetNuffield Department of Medicine, University of Oxford, Oxford, UK.
Catherine MutindaNeonatal Unit, Pumwani Maternity Hospital, Nairobi, Kenya.
Beth MainaNeonatal Unit, Pumwani Maternity Hospital, Nairobi, Kenya.
Constance SchultszDepartment of Medical Microbiology, Academic Medical Centre, Amsterdam, Netherlands.
Mike EnglishHealth Services Unit, KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya.

Funding

EPA EP-C-15-003Medical Research Council MR/M015386/1Wellcome Trust
6 · The paper itself

Abstract

Essential interventions to reduce neonatal deaths that can be effectively delivered in hospitals have been identified. Improving information systems may support routine monitoring of the delivery of these interventions and outcomes at scale. We used cycles of audit and feedback (A&F) coupled with the use of a standardised newborn admission record (NAR) form to explore the potential for creating a common inpatient neonatal data platform and illustrate its potential for monitoring prescribing accuracy. Revised NARs were introduced in a high volume, neonatal unit in Kenya together with 13 A&F meetings over a period of 3  years from January 2014 to November 2016. Data were abstracted from medical records for 15 months before introduction of the revised NAR and A&F and during the 3 years of A&F. We calculated, for each patient, the percentage of documented items from among the total recommended for documentation and trends calculated over time. Gentamicin prescribing accuracy was also tracked over time. Records were examined for 827 and 7336 patients in the pre-A&F and post-A&F periods, respectively. Documentation scores improved overall. Documentation of gestational age improved from <15% in 2014 to >75% in 2016. For five recommended items, including temperature, documentation remained <50%. 16.7% (n=1367; 95%  CI 15.9 to 17.6) of the admitted babies had a diagnosis of neonatal sepsis needing antibiotic treatment. In this group, dosing accuracy of gentamicin improved over time for those under 2  kg from 60% (95%36.1 to 80.1) in 2013 to 83% (95% CI 69.2 to 92.3) in 2016. We report that it is possible to improve routine data collection in neonatal units using a standardised neonatal record linked to relatively basic electronic data collection tools and cycles of A&F. This can be useful in identifying potential gaps in care and tracking outcomes with an aim of improving the quality of care.

Indexed as

audit and feedbackneonatal carequality of care

Identifiers

PMID30258654
PMCPMC6150140

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.