Evidence map›Paper›PMID 33214145›Full record

ArticleBMJ open quality2020

How to prioritise in quality improvement? Targeted implementation as a key for quality improvement in Kenyan health facilities.

Christine Nitschke, Maureen Nafula, Marc Brodowski, Irmgard Marx, Charles Kandie, Irene Omogi, Friederike Paul-Fariborz, Joachim Szecsenyi, Lucia Brugnara, Michael Marx

Abstract read
In one paragraph

Article in BMJ open quality, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

10 authors.

Christine NitschkeHeidelberg Institute of Global Health, University of Heidelberg, Heidelberg, Germany christine.nitschke@hotmail.de.
Maureen NafulaInstitute of Health Policy, Management and Research (IHPMR), Nairobi, Kenya.
Marc BrodowskiInstitute for Applied Quality Improvement & Research in Health Care (aQua), Göttingen, Germany.
Irmgard MarxEvaplan at the University Hospital, Heidelberg, Germany.
Charles KandieDepartment of Health Standards, Quality Assurance and Regulations, Ministry of Health, Nairobi, Kenya.
Irene OmogiHealth Programme, Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH, Nairobi, Kenya.
Friederike Paul-FariborzEvaplan at the University Hospital, Heidelberg, Germany.
Joachim SzecsenyiInstitute for Applied Quality Improvement & Research in Health Care (aQua), Göttingen, Germany.
Lucia BrugnaraEvaplan at the University Hospital, Heidelberg, Germany.
Michael MarxHeidelberg Institute of Global Health, University of Heidelberg, Heidelberg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundData from national surveys of low- and middle income countries indicates that there is still a need to improve the quality of healthcare in resource-poor settings. This study aims to understand the benefit of an integral, facility-driven, indicator-based approach used as a decision-making tool to define effective quality improvement interventions in Kenya.

objectiveThe aim of the study is to understand whether the integral approach developed leads to effective interventions.

methodsCategorical data is collected from ten health facilities covered by the Integrated Quality Management System (IQMS) project in Kenya. First the information on concrete improvement interventions implemented within the facilities is collected and merged into five different intervention topics. Second, groups of facilities with similar quality improvement interventions are selected to compare between the first and second quality assessment rounds. Those IQMS indicators matching the content of the intervention topic are extracted from the software VISOTOOL. In a third step, the data is summarised using means and SD. A one sample T-test is applied on the mean changes and SD. Frequency counts and percentages were used for the presentation of categorical data.

resultsAll improvement interventions resulted in positive and higher change values (T2-T1). Four of five intervention topics, show statistically significant improvements including neonatal mortality (42%; p<0.0001), waiting time (39%; p=0.0490), infection prevention control (28%; p=0.0007) and with shortages of staffing and transport in remote areas (32%; p=0.0194).

conclusionsIn all facilities the interventions selected have a positive impact, some of which markedly improved. It demonstrates that this integral quality improvement approach in Kenya can serve as an effective decision-making tool for identification and prioritisation of interventions. Those targeted interventions, being performed under institutionalisation in form of coaching and tutoring, effectively contribute to improving the quality of care in resource poor settings.

Indexed as

Health FacilitiesQuality ImprovementDelivery of Health CareHumansInfant, NewbornKenyadecision makingqualitative researchquality improvementquality measurement

Identifiers

PMID33214145
PMCPMC7678341

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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.