Evidence map›Paper›PMID 41642866›Full record

ArticlePloS one2026

Factors and determinants of primary care to tertiary care referrals in Singapore: A multi-centre analysis using artificial intelligence-powered large language models.

Sky Wei Chee Koh, Jasper Yi Xuan Huang, Joelle Lam, Si Hui Low, Jun Cong Goh, Ge Ji, Xin Jin, Howard Bauchner, Yii Jen Lew

Abstract readMulticenter Study
In one paragraph

Article in PloS one, 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

9 authors.

Sky Wei Chee KohNational University Polyclinics, National University Health System, Singapore.ORCID https://orcid.org/0000-0003-4520-646X
Jasper Yi Xuan HuangFaculty of Medicine, Nursing and Health Sciences, Monash University, Australia.
Joelle LamNational University Polyclinics, National University Health System, Singapore.
Si Hui LowNational University Polyclinics, National University Health System, Singapore.ORCID https://orcid.org/0009-0006-7273-4646
Jun Cong GohNational University Polyclinics, National University Health System, Singapore.
Ge JiData Science & Analytics, Alexandra Hospital, National University Health System, Singapore.
Xin JinData Science & Analytics, Alexandra Hospital, National University Health System, Singapore.
Howard BauchnerYong Loo Lin School of Medicine, National University of Singapore, Singapore.
Yii Jen LewNational University Polyclinics, National University Health System, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs Singapore adopts a population health approach under Healthier Singapore (Healthier SG), optimizing healthcare resources is crucial. We examined referral reasons (using large language models [LLM]), wait times, and analyse factors affecting referrals from primary to tertiary care.

methodsIn 2023, 1,063,646 patient visits from seven primary care clinics in Singapore were analysed. Patient demographics, clinic, physician characteristics, referral volumes and wait times were extracted. LLM Claude 3.5 Sonnet was utilized to identify and classify top referral reasons within the most frequently referred specialties based on referral notes. Chi-square tests identified differences in referral rates among categorical variables, while a generalised linear model (GLM) with an identity link (normal distribution) determined factors influencing referrals by physicians.

findingsAround 1 in 5 visits resulted in a referral (n = 210,839, 19.8%), achieving 76.0% attendance rate. Referrals peaked among patients aged 60-70 years. Male (Odds ratio [OR] 0.88, 95% Confidence interval [CI] 0.87-0.89) and Malay (OR 0.71, 95% CI 0.70-0.72, compared with Chinese) patients were less likely to be referred. Significant variations were observed among clinics (p < 0.001). Ophthalmology (11.1%), orthopaedic surgery (10.3%), and emergency (10.0%) were the most referred specialties, with blurred vision (n = 7,461), abnormal diabetic retinopathy screening (n = 5,266) and pregnancy and antenatal care (n = 3,959) being the top referral reasons. 51.5% were routine referrals. Wait time averaged 52.7 days with 48.9% meeting targets, with long wait times for Gastroenterology & Hepatology, and Endocrinology. On average, each additional year of physician experience was associated with a reduction of 4.45 referrals per physician (95% CI: 1.40-7.58, p = 0.005).

interpretationOur study highlighted disparities in referrals rates, patterns, and wait times. Continuing education and support for primary care is paramount. Resource allocation should be tailored to meet the population needs, with further research needed to ensure timely and appropriate referrals.

Indexed as

Artificial IntelligencePrimary Health CareReferral and ConsultationTertiary Health CareAdultAgedFemaleHumansLarge Language ModelsMaleMiddle AgedSingapore

Identifiers

PMID41642866
PMCPMC12875445

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