Evidence map›Paper›PMID 42231263›Full record

ArticleBMC health services research2026

Cost-utility analysis of retinopathy of prematurity screening strategies of universal referral, RetCam telemedicine, and direct examination in Iran: a markov model approach.

Parinaz Alizadeh, Maryam Manaberi, Afsar Dastjani Farahani, Cyrus Alinia

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

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Parinaz AlizadehNeonatal Health Research Center, Research Institute for Children's Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Maryam ManaberiNeonatal Health Research Center, Research Institute for Children's Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Afsar Dastjani FarahaniTranslational Ophthalmology Research Centre, National RoP Centre of Excellence, Farabi Eye Hospital, Tehran, Iran.
Cyrus AliniaDepartment of Health Management and Economics, School of Public Health, Urmia University of Medical Sciences, Urmia, Iran. alinia.s@umsu.ac.ir.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRetinopathy of prematurity (ROP) is a leading cause of preventable childhood blindness, particularly in low- and middle-income countries. In Iran, where the prevalence of ROP among premature infants exceeds 20%, limited access to subspecialist ophthalmologists constrains timely screening. This study evaluated the cost-utility of three alternative ROP screening strategies to inform national policy on optimizing resource allocation.

methodsA lifetime, societal-perspective cost-utility analysis was conducted using a state-transition Markov model. Three strategies were compared: (1) universal referral of all at-risk infants to tertiary centers; (2) RetCam-based nurse-led imaging with remote ophthalmologist review (telemedicine); and (3) local screening by general ophthalmologists with selective referral. Model inputs were derived from national data, published literature, and expert opinion. Costs (2025 Iranian Tomans) and quality-adjusted life years (QALYs) were discounted at 5.8%. Deterministic and probabilistic sensitivity analyses were performed to assess parameter uncertainty.

resultsThe Direct Examination scenario (general ophthalmologist screening) had the lowest mean cost (33.52 USD) and effectiveness (16.83 QALYs). RetCam imaging achieved higher effectiveness (17.14 QALYs) at a cost of 122.69 USD, yielding an incremental cost-effectiveness ratio (ICER) of 288.81 USD per QALY gained, well below Iran's willingness-to-pay (WTP) threshold of USD 7,047. The Universal Referral strategy was dominated, being both more costly and less effective. Probabilistic sensitivity analysis confirmed that RetCam imaging was cost-effective in 95.2% of 10,000 Monte Carlo simulations at a WTP of USD 6,000 per QALY. Diagnostic specificity and long-term vision care costs were the key ICER drivers.

conclusionsRetCam-based telemedicine screening for ROP in Iran is highly cost-effective compared to traditional direct examination or universal referral, offering substantial long-term health gains at an acceptable cost. Scaling up telemedicine screening, supported by quality assurance and training programs, could reduce preventable childhood blindness and improve efficiency of neonatal eye care delivery.

Indexed as

Neonatal ScreeningReferral and ConsultationRetinopathy of PrematurityTelemedicineCost-Benefit AnalysisCost-Effectiveness AnalysisHumansInfant, NewbornIranMarkov ChainsQuality-Adjusted Life YearsCost–utility analysisHealth economicsIranMarkov modelQuality-adjusted life yearsRetinopathy of prematurityScreening strategiesTelemedicine

Identifiers

PMID42231263
PMCPMC13455455

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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 OpenQuestion graph.