Evidence map›Paper›PMID 40180372›Full record

ArticleBMJ open2025

Seizing the silent vision loss: cost-utility analysis of population-based glaucoma screening in India.

Neha Purohit, Sandeep Buttan, Parul Chawla Gupta, Ranjan Kumar Choudhury, Kathirvel Soundappan, Atul Kotwal, Shankar Prinja

Abstract readComparative Study
In one paragraph

Article in BMJ open, 2025. 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

7 authors.

Neha PurohitDepartment of Community Medicine and School of Public Health, Post Graduate Institute of Medical Education and Research, Chandigarh, India.
Sandeep ButtanSightsavers India, New Delhi, India.
Parul Chawla GuptaDepartment of Ophthalmology, Post Graduate Institute of Medical Education and Research, Chandigarh, India.
Ranjan Kumar ChoudhuryNational Health Systems Resource Center, New Delhi, India.
Kathirvel SoundappanDepartment of Community Medicine and School of Public Health, Post Graduate Institute of Medical Education and Research, Chandigarh, India.ORCID http://orcid.org/0000-0002-4839-0138
Atul KotwalNational Health Systems Resource Center, New Delhi, India.
Shankar PrinjaDepartment of Community Medicine and School of Public Health, Post Graduate Institute of Medical Education and Research, Chandigarh, India shankarprinja@gmail.com.ORCID http://orcid.org/0000-0001-7719-6986

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesGlaucoma is a major cause of irreversible blindness in India; however, if detected early, its progression can be either prevented or stabilised through appropriate medical or surgical treatment. We aim to evaluate the cost-utility of various models for population-based glaucoma screening at primary health centres in India. We also assess the potential impact of the implementation of a population-based screening programme on overall costs of care for glaucoma.

designCost-utility analysis using a mathematical model comprising a decision tree and Markov model was conducted to simulate relevant costs and health outcomes over a lifetime horizon.

settingScreening services were assumed to be delivered at primary health centres in India.

participantsA hypothetical cohort of different target population groups in terms of age groups and risk of glaucoma (age group 40-75 years, 50-75 years, 40-75 years age group at high risk of glaucoma, 50-75 years age group at high risk of glaucoma) were included in comparative screening strategies.

interventionsThe exclusive intervention scenarios were 12 screening strategies based on different target population groups (age group 40-75 years, 50-75 years, 40-75 years age group at high risk of glaucoma, 50-75 years age group at high risk of glaucoma), screening methods (face-to-face screening and artificial intelligence-supported face-to-face screening) and screening frequencies for 40-75 years aged population (annual vs once every 5 years screening), in comparison to usual care scenario. The usual care scenario (current practice) implied opportunistic diagnosis by the ophthalmologists at higher levels of care. PRIMARY AND SECONDARY OUTCOMES: The primary outcome was the incremental cost-utility ratio for each of the screening strategies in comparison to usual care. The secondary outcomes were per person lifetime costs, lifetime out-of-pocket expenditures, life years and quality-adjusted life-years (QALYs) in all screening scenarios and usual care.

findingsDepending on the type of screening strategy, the gain in QALY per person ranged from 0.006 to 0.046 relative to usual care. However, the screening strategies, whether adjusted for specific age groups, patient risk profiles, screening methods or frequency, were not found to be cost-effective. Nonetheless, annual face-to-face screening strategies for individuals aged 40-75 years could become cost-effective in a scenario of strengthened public financing and provisioning, such that at least 67% of those seeking care for confirmatory diagnosis and treatment use government-funded facilities, in conjunction with 60% availability of medications at government hospitals.

conclusionsEnhancing continuity of care following screening through either strengthening of public provisioning or strategic purchasing of care could make glaucoma screening interventions not only cost-effective, but also potentially cost-saving.

Indexed as

GlaucomaMass ScreeningModels, EconomicAdultAgedArtificial IntelligenceBlindnessContinuity of Patient CareCost-Benefit AnalysisDecision TreesHumansIndiaMiddle AgedGlaucomaHealth Care CostsHealth economicsHEALTH ECONOMICSMass ScreeningPrimary Health Care

Identifiers

PMID40180372
PMCPMC11969579

What Socratic holds

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LicenceCC BY
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Registered trials

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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 Socratic graph.