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

  • 1Saw Swee Hock School of Public Health, National University Health System, National University of Singapore, Singapore, Singapore.
  • 2Schaeffer Center for Health Policy and Economics, University of Southern California, Los Angeles, United States.
  • 3Health Intervention and Technology Assessment Program, Ministry of Public Health, Nonthaburi, Thailand.
  • 4National University Polyclinics Singapore, Singapore, Singapore.
  • 5Ng Teng Fong General Hospital, Singapore, Singapore.

Abstract

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.

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