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

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Yayımlandı:Journal of Medical Internet Research vol. 27 (2025), p. e70484
Yazar: Chen, Cynthia
Diğer Yazarlar: Sukmanee, Jarawee, Khai Wee Soon, Lim, Julian, Jared Louis Andre D'Souza, Teerawattananon, Yot
Baskı/Yayın Bilgisi:
Gunther Eysenbach MD MPH, Associate Professor
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022 |a 1438-8871 
024 7 |a 10.2196/70484  |2 doi 
035 |a 3222369255 
045 2 |b d20250101  |b d20251231 
100 1 |a Chen, Cynthia 
245 1 |a Economic Evaluation of the Next Generation Electronic Medical Records in Singapore: Cost-Utility Analysis 
260 |b Gunther Eysenbach MD MPH, Associate Professor  |c 2025 
513 |a Journal Article 
520 3 |a Background:With 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.Objective:This study aims to conduct an economic evaluation of the NGEMR to inform future health care system upgrades.Methods:A 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).Results:NGEMR 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.Conclusions:The 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. 
651 4 |a United States--US 
651 4 |a Singapore 
653 |a Medical records 
653 |a Software 
653 |a Databases 
653 |a Waiting times 
653 |a Interoperability 
653 |a Health care policy 
653 |a Patients 
653 |a Willingness to pay 
653 |a Health care expenditures 
653 |a Outpatient clinics 
653 |a Health facilities 
653 |a Primary care 
653 |a Deterioration 
653 |a Quality of life 
653 |a Electronic health records 
653 |a Cost analysis 
653 |a Long term health care 
653 |a Information storage 
653 |a Cost control 
653 |a Multimedia 
653 |a Clinics 
653 |a Quality adjusted life years 
653 |a Medical referrals 
653 |a Cost reduction 
653 |a Thresholds 
653 |a Hospitals 
653 |a Gross Domestic Product--GDP 
653 |a Probability 
653 |a Computerized medical records 
653 |a Medical personnel 
653 |a Return on investment 
653 |a Decision trees 
653 |a Family physicians 
653 |a Tests 
653 |a Health information 
653 |a Hospitalization 
653 |a Utility functions 
653 |a Systematic review 
653 |a Coordination 
653 |a Practitioner patient relationship 
653 |a Time 
653 |a Physicians 
653 |a Archives & records 
653 |a Health care industry 
653 |a Costs 
653 |a Data 
653 |a Adoption of innovations 
653 |a Health services 
653 |a Effectiveness 
653 |a Medical decision making 
653 |a Information technology 
653 |a Health care 
700 1 |a Sukmanee, Jarawee 
700 1 |a Khai Wee Soon 
700 1 |a Lim, Julian 
700 1 |a Jared Louis Andre D'Souza 
700 1 |a Teerawattananon, Yot 
773 0 |t Journal of Medical Internet Research  |g vol. 27 (2025), p. e70484 
786 0 |d ProQuest  |t Library Science Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3222369255/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text + Graphics  |u https://www.proquest.com/docview/3222369255/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3222369255/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch