Evidence map›Paper›PMID 42781576›Full record

ArticleBMJ public health2026

Identifying barriers and potential solutions to improve equitable access to community eye services in central Kenya: a rapid exploratory sequential mixed methods study.

Luke N Allen, Sarah Karanja, Michael Gichangi, Cosmas Bunywera, Emmaculate Muturi, Dickson Gachobi, Purity Kathure, Elizabeth Mutile Muasa, Lorna Mutwiri, Lorna Kajuju and 10 more

Abstract read
In one paragraph

Article in BMJ public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

20 authors.

Luke N AllenNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Sarah KaranjaCentre for Public Health Research, Kenya Medical Research Institute, Nairobi, Kenya.
Michael GichangiOphthalmic Services Unit, Kenya Ministry of Health, Nairobi, Kenya.
Cosmas BunyweraPeek Vision Ltd, Kitale, Kenya.
Emmaculate MuturiCollege of Ophthalmology of Eastern Central and Southern Africa, Nairobi, Kenya.
Dickson GachobiLifecare Hospital, Nairobi, Kenya.
Purity KathureCollege of Ophthalmology of Eastern Central and Southern Africa, Nairobi, Kenya.
Elizabeth Mutile MuasaCollege of Ophthalmology of Eastern Central and Southern Africa, Nairobi, Kenya.
Lorna MutwiriMeru County Health Department, Meru, Kenya.
Lorna KajujuMeru County Health Department, Meru, Kenya.
Faith KagwiriaChuka University, Chuka, Eastern, Kenya.
Benjamin NtabathiaCollege of Ophthalmology of Eastern Central and Southern Africa, Nairobi, Kenya.
Hillary RonoKitale County District Hospital, Kitale, Kenya.
David MacleodDepartment of Infectious Disease Epidemiology and International Health, London School of Hygiene & Tropical Medicine, London, UK.
Min KimDepartment of Infectious Disease Epidemiology and International Health, London School of Hygiene & Tropical Medicine, London, UK.
Malebogo TlhajoaneDepartment of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK.ORCID https://orcid.org/0000-0002-0601-5516
Matthew J BurtonDepartment of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK.
Jacqueline RamkeDepartment of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK.
Nigel M BolsterPeek Vision Ltd, London, UK.
Andrew BastawrousDepartment of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK.

Funding

Wellcome Trust
6 · The paper itself

Abstract

Background: Recent research has found that less than half of people identified with an eye problem in Meru county's screening programme were able to access care, with younger adults being the least likely to receive the care they needed. We aimed to interview and survey members of this 'left-behind' group to explore barriers and identify potential solutions using a rapid mixed-methods approach. Methods: First, we conducted interviews to explore perceptions of barriers and potential solutions. Next, we asked a representative sample to rank the suggested solutions by likely impact. Finally, we held a multistakeholder workshop to identify which of the top-ranked interventions offered the best balance of impact, feasibility, cost and potential risks. We used a deductive matrix and thematic analysis to rapidly analyse the interview data. Results: We conducted 67 interviews. Barriers to access included long queues, conflicting work engagements and lack of clear information. Proposed solutions focused on reducing queue lengths, providing better counselling and clinic information, holding mop-up clinics and maintaining adequate stocks and supplies. We conducted ranking surveys with 401 additional people from the left-behind group. All proposed solutions were ranked at moderately-to-highly likely to improve equitable access. Fifteen people attended the multistakeholder meeting, including community representatives. Workshop participants unanimously selected enhanced counselling and SMS reminders as the interventions that offered the best balance of impact, risk, cost and feasibility. The other proposed solutions were deemed impractical or unaffordable. Conclusions: Rapid mixed-methods and multistakeholder collaboration were used to identify a range of potential service modifications that will be implemented within the ongoing programme. Our approach was centred on the experiences and perceptions of those who face the highest barriers to care.

Indexed as

Community HealthHealth Services AccessibilityPublic HealthQualitative Research

Identifiers

PMID42781576
PMCPMC13599916

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.