Evidence map›Paper›PMID 39792334›Full record

ArticleOphthalmology and therapy2025

Transforming Non-Digital, Clinical Workflows to Detect and Track Vision-Threatening Diabetic Retinopathy via a Digital Platform Integrating Artificial Intelligence: Implementation Research.

Peranut Chotcomwongse, Paisan Ruamviboonsuk, Chaiwat Karavapitayakul, Koblarp Thongthong, Anyarak Amornpetchsathaporn, Methaphon Chainakul, Malee Triprachanath, Eckachai Lerdpanyawattananukul, Niracha Arjkongharn, Varis Ruamviboonsuk and 6 more

Registry-linked trialAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Ophthalmology and therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05166122 (Implementation of an Integrated System of Artificial Intelligence and Referral Tracking for Real-time Diabetic Retinopathy Screening), which is not on this map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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.

NCT05166122 naunknown statusnot on this map

Implementation of an Integrated System of Artificial Intelligence and Referral Tracking for Real-time Diabetic Retinopathy Screening

TypeinterventionalSponsorDepartment of Medical Services Ministry of Public Health of ThailandRan2022 to 2022Enrolled1,600ConditionsDiabetic Retinopathy, Artificial Intelligence, ScreeningArmsArtificial Intelligence
3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

16 authors.

Peranut ChotcomwongseDepartment of Ophthalmology, College of Medicine, Rajavithi Hospital, Rangsit University, Bangkok, Thailand.
Paisan RuamviboonsukDepartment of Ophthalmology, College of Medicine, Rajavithi Hospital, Rangsit University, Bangkok, Thailand. paisan.trs@gmail.com.ORCID http://orcid.org/0000-0001-6114-6220
Chaiwat KaravapitayakulDepartment of Medical Services (DMS), Ministry of Public Health, Nonthaburi, Thailand.
Koblarp ThongthongAyutthaya Provincial Hospital, Ayutthaya, Thailand.
Anyarak AmornpetchsathapornDepartment of Ophthalmology, College of Medicine, Rajavithi Hospital, Rangsit University, Bangkok, Thailand.
Methaphon ChainakulDepartment of Ophthalmology, College of Medicine, Rajavithi Hospital, Rangsit University, Bangkok, Thailand.
Malee TriprachanathUtai Community Hospital, Ayutthaya, Thailand.
Eckachai LerdpanyawattananukulUtai Community Hospital, Ayutthaya, Thailand.
Niracha ArjkongharnDepartment of Ophthalmology, College of Medicine, Rajavithi Hospital, Rangsit University, Bangkok, Thailand.
Varis RuamviboonsukDepartment of Ophthalmology, King Chulalongkorn Memorial Hospital, Bangkok, Thailand.
Nattaporn VongsaDepartment of Ophthalmology, College of Medicine, Rajavithi Hospital, Rangsit University, Bangkok, Thailand.
Pawin PakaymaskulDepartment of Ophthalmology, College of Medicine, Rajavithi Hospital, Rangsit University, Bangkok, Thailand.
Turean WaiwareeAyutthaya Provincial Hospital, Ayutthaya, Thailand.
Hathaiphan RuampunpongGoogle LLC, Mountain View, CA, USA.
Richa TiwariGoogle LLC, Mountain View, CA, USA.
Viroj TangcharoensathienInternational Health Policy Program (IHPP), Ministry of Public Health, Nonthaburi, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionScreening diabetic retinopathy (DR) for timely management can reduce global blindness. Many existing DR screening programs worldwide are non-digital, standalone, and deployed with grading retinal photographs by trained personnel. To integrate the screening programs, with or without artificial intelligence (AI), into hospital information systems to improve their effectiveness, the non-digital workflow must be transformed into digital. We developed a cloud-based digital platform and implemented it in an existing DR screening program.

methodsWe conducted the following processes in the platform for prospective DR screening at a community hospital: capturing patients' retinal photographs, uploading them for grading by AI or trained personnel on alternate weeks for 32 weeks, and referring vision-threatening DR to a referral center. At this center, the platform was applied for the assessment of potential missed referrals via remote over-reading by a retinal specialist and tracking referrals. Implementational outcomes, such as detecting positive cases, agreement between AI and over-reading, and referral adherence were assessed.

resultsOf 645 patients screened by AI, 201 (31.2%) were referrals, 129 (64.2%) of which were true positives agreeable by over-reading; 115 of these true positives (89.1%) had referral adherence. False negatives judged by over-reading were 1.1% (5/444). Of 730 patients in manual screening, 175 (24.0%) were potential referrals, 11 (6.3%) of which were referred at the point-of-screening; eight of these (72.7%) adhered to referral. The remaining 164 cases were appointed for later examination by a visiting general ophthalmologist; 11 of these 116 examined (9.5%) were referred for non-DR-related eye conditions with 81.8% (9/11) referral adherence. No system failure or interruption was found.

conclusionsThe digital platform can be practically integrated into the existing non-digital DR screening programs to implement AI and monitor previously unknown but important indicators, such as referral adherence, to improve the effectiveness of the programs.

trial registrationClinicalTrials.gov. (registration number: NCT05166122).

Indexed as

Artificial intelligenceDiabetic retinopathyDigital healthReal-world implementationVision-threatening diabetic retinopathy

Identifiers

PMID39792334
PMCPMC11754548

What OpenQuestion holds

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LicenceCC BY-NC
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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.