ArticleBMJ open quality2019
Identifying and resolving the frustrations of reviewing the improvement literature: The experiences of two improvement researchers.
Article in BMJ open quality, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Interventions for improving critical care in low- and middle-income countries: a systematic review.Intensive care medicine · 2024Pooled it
- Commentary on "Protecting Against Unintended Risk From Student Quality Improvement Projects in Health Care".Advances in health information science and practice · 2026Article
- Article
- Changes in health worker knowledge and motivation in the context of a quality improvement programme in Ethiopia.Health policy and planning · 2021Article
- Completeness of reporting of quality improvement studies in neonatology is inadequate: a systematic literature survey.BMJ open quality · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
aimsSummarising quality improvement (QI) research through systematic literature review has great potential to improve patient care. However, heterogeneous terminology, poor definition of QI concepts and overlap with other scientific fields can make it hard to identify and extract data from relevant literature. This report examines the compromises and pragmatic decisions that undertaking literature review in the field of QI requires and the authors propose recommendations for literature review authors in similar fields.
methodsTwo authors (EJ and JF) provide a reflective account of their experiences of conducting a systematic literature review in the field of QI. They draw on wider literature to justify the decisions they made and propose recommendations to improve the literature review process. A third collaborator, (WC) co-created the paper challenging author's EJ and JF views and perceptions of the problems and solutions of conducting a review of literature in QI.
resultsTwo main challenges were identified when conducting a review in QI. These were defining QI and selecting QI studies. Strategies to overcome these problems include: select a multi-disciplinary authorship team; review the literature to identify published QI search strategies, QI definitions and QI taxonomies; Contact experts in related fields to clarify whether a paper meets inclusion criteria; keep a reflective account of decision making; submit the protocol to a peer reviewed journal for publication.
conclusionsThe QI community should work together as a whole to create a scientific field with a shared vision of QI to enable accurate identification of QI literature. Our recommendations could be helpful for systematic reviewers wishing to evaluate complex interventions in both QI and related fields.
Indexed as
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What OpenQuestion holds
Registered trials
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.