Evidence map›Paper›PMID 40499159›Full record

ArticleJournal of medical Internet research2025

Economic Evaluation of the Next Generation Electronic Medical Records in Singapore: Cost-Utility Analysis.

Cynthia Chen, Jarawee Sukmanee, Khai Wee Soon, Julian Lim, Jared Louis Andre D'Souza, Yot Teerawattananon

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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

6 authors.

Cynthia ChenSaw Swee Hock School of Public Health, National University Health System, National University of Singapore, Singapore, Singapore.ORCID https://orcid.org/0000-0002-1947-8069
Jarawee SukmaneeHealth Intervention and Technology Assessment Program, Ministry of Public Health, Nonthaburi, Thailand.ORCID https://orcid.org/0000-0002-4202-2465
Khai Wee SoonNational University Polyclinics Singapore, Singapore, Singapore.ORCID https://orcid.org/0009-0003-9725-0953
Julian LimSaw Swee Hock School of Public Health, National University Health System, National University of Singapore, Singapore, Singapore.ORCID https://orcid.org/0009-0006-8591-1103
Jared Louis Andre D'SouzaNg Teng Fong General Hospital, Singapore, Singapore.ORCID https://orcid.org/0000-0002-2415-7390
Yot TeerawattananonSaw Swee Hock School of Public Health, National University Health System, National University of Singapore, Singapore, Singapore.ORCID https://orcid.org/0000-0003-2217-2930

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith the vast development of technology and the evolving needs of patients and health care providers, electronic medical records (EMRs) have become a cornerstone for health information. However, different institutions have used different EMR systems. Our study investigates the potential benefits of implementing an integrated and common platform, known as the Next Generation Electronic Medical Record (NGEMR) in Singapore. The NGEMR allows improved data sharing between health care facilities and can promote better coordination between primary care and specialist care doctors to access patients' records from the same database.

objectiveThis study aims to conduct an economic evaluation of the NGEMR to inform future health care system upgrades.

methodsA cost-utility analysis comparing NGEMR with the legacy EMR was conducted using a decision tree model with a 1-year time horizon from a health care system perspective. Input parameters of patients visiting primary care at the National University Polyclinics and specialist outpatient clinics from a General Hospital were extracted from the EMR systems. The incremental cost-effectiveness ratio (ICER) was calculated using costs and quality-adjusted life years (QALYs).

resultsNGEMR was cost-effective and yielded a marginal health benefit (0.00006 QALYs gained) at a slightly higher cost (S $2.73; US $2.02), with an ICER of S $46,349 (US $34,298) per QALY. At the willingness-to-pay thresholds of 0.5- and 1-time gross domestic product (GDP) per capita (S $48,899; US $36,185 and S $97,798; US $72,371 per QALY), the implementation of NGEMR had a 52.2% and 64.7% probability of being cost-effective, respectively. The reduction in waiting time to see a specialist resulted in 2.3% fewer hospitalizations. The most influential parameter on the ICER was the probability of receiving duplicate tests, followed by the costs of admission and the probability of seeing a specialist. Reducing the probability of receiving duplicate tests for NGEMR from 20.7% to 13.2% resulted in a cost-saving ICER. A threshold analysis on the proportion of patients with a waiting time of less than 20 days for NGEMR was further explored, as it was a sensitive parameter on the cost-effectiveness of NGEMR. Increasing the proportion of patients with a waiting time of less than 20 days from 45.5% to 56% would result in cost savings for NGEMR.

conclusionsThe adoption of NGEMR is cost-effective in Singapore. Beyond cost-effectiveness, the reduction of waiting time between primary and specialist care can lower the possibility of patients' health deterioration, thus reducing hospital admissions. We recommend continuous monitoring of waiting times and the likelihood of having duplicate tests as countries transition from basic to advanced-level EMR systems. Future analyses could benefit from more granular data on timing and clinical indications and incorporate real-world local data as they become available through ongoing NGEMR rollout evaluations.

Indexed as

Electronic Health RecordsCost-Benefit AnalysisHumansQuality-Adjusted Life YearsSingaporecost-effectivenesscost-utilityelectronic medical recordsICERincremental cost-effectiveness ratioprimary careQALYquality-adjusted life year

Identifiers

PMID40499159
PMCPMC12198694

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LicenceCC BY
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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.