ArticleNIHR open research2023
A realist review of the causes of, and current interventions to address 'missingness' in health care.
Article in NIHR open research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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.
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Who cites it
11 citing papers in PubMed.
- Review
- Addressing the causes of 'missingness' in healthcare: a co-designed suite of interventions.BMC medicine · 2026Article
- Optimeet: A computational tool to enhance participant attendance in group research.Behavior research methods · 2025Article
- Why Do Individuals with Diabetes Miss Their Dietitian Appointments? A Mixed-Methods Study on Barriers and Strategies for Improved Engagement in Diabetes Care.Healthcare (Basel, Switzerland) · 2025Article
- 'Challenging but ultimately rewarding' - lived experiences of Deep End Northern Ireland GPs: a qualitative study.The British journal of general practice : the journal of the Royal College of General Practitioners · 2024Article
- Article
- Trends and socioeconomic inequalities in the dental attendance of adult smokers in Scotland from 2009 to 2019, a repeated cross-sectional study.BMC public health · 2024Article
- Understanding the causes of missingness in primary care: a realist review.BMC medicine · 2024Review
- Inclusion health and missingness in health care: dig where you stand.The British journal of general practice : the journal of the Royal College of General Practitioners · 2023Article
- A realist review of the causes of, and current interventions to address 'missingness' in health care.NIHR open research · 2023Article
- Artificial intelligence machine learning-driven outpatient appointment management: A qualitative study on acceptability.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: This protocol describes a realist review exploring the problem of "missingness" in healthcare, defined as the repeated tendency not to take up offers of care that has a negative impact on the person and their life chances. More specifically, the review looks at the phenomenon of patients missing multiple appointments in primary care in the UK - at the causal factors that influence how patients come to be "missing" in this way, and what interventions might support uptake and "presence" in healthcare. Background research informing this project suggests that a high rate of missed appointments predicted high premature death rates, and patients were more likely to have multiple long-term health conditions and experience significant socioeconomic disadvantage. Most research in this field focuses on population- or service-level characteristics of patients who miss appointments, often making no distinction between causes of single missed appointments and of multiple missed appointments. There have therefore been no interventions for 'missingness', accounting for the complex life circumstances or common mechanisms that cause people to repeatedly miss appointments. Methods: We use a realist review approach to explore what causes missingness - and what might prevent or address it - for whom, and in what circumstances. The review uses an iterative approach of database searching, citation-tracking and sourcing grey literature, with selected articles providing insight into the causal dynamics underpinning missed appointments and the interventions designed to address them. Discussion: The findings of this review will be combined with the findings of a qualitative empirical study and the contributions of a Stakeholder Advisory Group (STAG) to inform the development of a programme theory that seeks to explain how missingness occurs, whom it affects and under what circumstances. This will be used to develop a complex intervention to address multiple missed appointments in primary care. PROSPERO registration: CRD42022346006.
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Registered trials
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