Cited by 3Retinal Imaging and AnalysisOphthalmology and Visual Impairment StudiesRetinal Diseases and Treatments

Barriers and Determinants of Referral Adherence in AI-Enabled Diabetic Retinopathy Screening for Older Adults in Northern India During the COVID-19 Pandemic: Mixed Methods Pilot Study

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Chauhan, Anshul, Goyal, Anju, Masih, Ritika, Kaur, Gagandeep, Kumar, Lakshay, Neha, ­, Rastogi, Harsh, Kumar, Sonam +5 more·2025·JMIR Formative Research

Abstract

Background: Diabetic retinopathy (DR) is a leading cause of blindness globally. DR has increasingly affected both individuals and health care systems as the population ages. Objective: This study aims to explore factors and identify barriers associated with nonadherence to referral recommendations among older adult participants after DR screening (DRS) during the COVID-19 pandemic. Method: This paper presents findings from a pilot study on artificial intelligence–enabled DRS conducted in two districts in Punjab, India (Moga and Mohali) during the COVID-19 pandemic. The screenings were conducted from March to June 2022 at community health center Badhani Kalan in Moga and from March to June 2021 in community settings (homes) in Block Boothgarh, Mohali. Participants were referred to the district hospital for an ophthalmological review based on artificial intelligence–enabled screening. After 1 month, the participants were contacted by telephone to assess adherence to the referral recommendations. Participants who did not adhere to the referral were then interviewed alongside health care providers to understand the barriers explaining their nonadherence. Results: We aimed to recruit 346 and 600 older adult participants from 2 sites but enrolled 390. Key challenges included health facility closures due to COVID-19, low motivation among health personnel for recruitment, incomplete nonparticipation data, and high participant workloads. Approximately 45% of the participants were male and 55% female. Most participants (62.6%) were between 60 and 69 years old, while 37.4% were 70 or older, with a mean age of 67.2 (SD 6.2) years. In total, 159 participants (40.8%) were referred, while 231 participants (59.2%) were not. Only 23 (14.5%) of those referred followed through and visited a health facility for ophthalmological review, while 136 (85.5%) did not pursue further evaluation. Our analysis revealed no significant differences in the characteristics between adherent and nonadherent participants, suggesting that demographic and health factors alone do not predict adherence behavior in patients with DR. Interviews identified limited knowledge about DR, logistical challenges, financial constraints, and attitudinal barriers as the primary challenges. Conclusions: This study, conducted during the COVID-19 pandemic, showed suboptimal adherence to referral recommendations among older adult patients due to knowledge gaps, logistical challenges, and health system issues. Quantifying and understanding adherence factors are crucial for targeted interventions addressing barriers to referral recommendations after DRS. Integrating teleophthalmology into and strengthening infrastructure for artificial intelligence–enabled diabetic retinopathy screening to enhance access and outcomes.

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  • Real-world implementation of diabetic retinopathy screening with artificial intelligence-assisted care pathways has accelerated globally since 2020.

    “Real-world implementation of DR screening with AI-assisted care pathways has accelerated globally since 20208,13–22, yet evidence on clinical and health system outcomes such as referral uptake remains limited.”

    From Referral uptake after diabetic retinopathy screening with artificial intelligence-assisted care pathways: a systematic review and meta-analysis (2026) · cites this paper as [20]

    The Methods (Hardware and Software for DRS; page unavailable) document real-world AI-assisted screening at two sites in Punjab. The Introduction says the pandemic emphasized the need for AI-enabled screening, but neither passage establishes that implementation accelerated globally since 2020. (LLM, conf=0.82)

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Authors
Chauhan, A., Goyal, A., Masih, R., Kaur, G., Kumar, L., Neha, ­., Rastogi, H., Kumar, S., Singh, B. L., Syal, P., Gupta, V., Vale, L., & Duggal, M.
Affiliations
  • Post Graduate Institute of Medical Education and Research (IN)
  • Panjab University (IN)
  • Newcastle University (GB)
  • Indian Council of Medical Research (IN)
Corresponding author
Duggal, Mona
Venue
JMIR Formative Research
Published
2025-03-31
Volume
9
Pages
e67047-e67047
ISSN
2561-326X (ISSN-L)
OpenAlex
W4409139359
Cited by
3
References
58
Citations by year
2026: 3
FWCI
1.73
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • JMIR Formative Research (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Newcastle University ePrints (Newcastle Univesity) (cc-by)
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Retinal Imaging and Analysis
  • Health Sciences › Medicine › Epidemiology › Ophthalmology and Visual Impairment Studies
  • Health Sciences › Medicine › Ophthalmology › Retinal Diseases and Treatments
Keywords
diabetic retinopathy, diabetic retinopathy screening, referral adherence, older adults, COVID-19 pandemic, barriers to care, financial constraints, health knowledge, ophthalmological follow-up, community health centers, Punjab, India, health worker motivation, health facility closures, blindness prevention, North India

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