Evidence map›Paper›PMID 41858608›Full record

ReviewLancet regional health. Americas2026

Alleviating Costs for Critical Eye Specialty Services (ACCESS): a prospective cohort analysis of a cost-coverage program at a public safety-net hospital.

Ryan A Morton, Irene J Pak, Alice S Tang, Deborah Chesky, Hemal K Kanzaria, Madeline Yung, Tyson N Kim

Abstract readReview
In one paragraph

Review in Lancet regional health. Americas, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Ryan A MortonDepartment of Ophthalmology, University of California-San Francisco, San Francisco, CA, USA.
Irene J PakDepartment of Ophthalmology, University of California-San Francisco, San Francisco, CA, USA.
Alice S TangDepartment of Ophthalmology, University of California-San Francisco, San Francisco, CA, USA.
Deborah CheskyAll May See Foundation, San Francisco, CA, USA.
Hemal K KanzariaDepartment of Emergency Medicine, University of California-San Francisco, San Francisco, CA, USA.
Madeline YungDepartment of Ophthalmology, University of California-San Francisco, San Francisco, CA, USA.
Tyson N KimDepartment of Ophthalmology, University of California-San Francisco, San Francisco, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the United States, gaps in public insurance coverage and high out-of-pocket costs for specialty ophthalmic services contribute substantially to preventable vision loss and disability among underserved populations. We describe the structure, implementation, and early outcomes of ACCESS (Alleviating Costs for Critical Eye Specialty Services), a hospital-based cost-coverage program established at an urban safety-net hospital to address these financial barriers. ACCESS delivers essential vision-restorative treatments frequently excluded from insurance coverage at no cost through hospital support and philanthropic funding. Prospective clinical and demographic data demonstrated marked reductions in visual disability among treated patients and substantial downstream economic benefit relative to program costs. These findings demonstrate that targeted cost-coverage programs embedded within safety-net systems can reduce disparities in vision care, while providing actionable evidence to inform hospital policy development and support broader expansion of insurance coverage for high-impact ophthalmic specialty services.

Indexed as

Corneal ectasiaHealth equityInsurance coverageScleral lensVision care

Identifiers

PMID41858608
PMCPMC12999287

What OpenQuestion holds

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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.