Evidence map›Paper›PMID 40494963›Full record

ArticleNPJ digital medicine2025

Economic analysis of an AI-enabled ECG alert system: impact on mortality outcomes from a pragmatic randomized trial.

Ping-Hsuan Hsieh, Chin Lin, Chin-Sheng Lin, Wei-Ting Liu, Tsung-Kun Lin, Dung-Jang Tsai, Yi-Jen Hung, Yuan-Hao Chen, Chih-Yuan Lin, Shih-Hua Lin and 1 more

Registry-linked trialAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05118035 (Applying an Artificial Intelligence-Enabled Electrocardiographic System for Reducing Mortality), which is not on this map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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.

NCT05118035 nacompletednot on this map

Applying an Artificial Intelligence-Enabled Electrocardiographic System for Reducing Mortality: a Pragmatic Randomized Clinical Trial

TypeinterventionalSponsorNational Defense Medical Center, TaiwanRan2021 to 2022Enrolled15,965ConditionsCardiovascular Diseases, Intensity Care, MoralityArmsAI-enabled ECG-based Screening Tool
3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Review
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

11 authors.

Ping-Hsuan HsiehSchool of Pharmacy, National Defense Medical Center, Taipei, Taiwan, ROC.
Chin LinSchool of Medicine, National Defense Medical Center, Taipei, Taiwan, ROC.
Chin-Sheng LinDivision of Cardiology, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC.
Wei-Ting LiuDivision of Cardiology, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC.
Tsung-Kun LinDepartment of Pharmacy Practice, Tri-Service General Hospital, Taipei, Taiwan, ROC.
Dung-Jang TsaiSchool of Medicine, National Defense Medical Center, Taipei, Taiwan, ROC.
Yi-Jen HungDivision of Endocrinology and Metabolism, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC.
Yuan-Hao ChenDepartment of Neurological Surgery, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC.
Chih-Yuan LinDivision of Cardiovascular Surgery, Department of Surgery, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC.
Shih-Hua LinDivision of Nephrology, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC.
Chien-Sung TsaiDivision of Cardiovascular Surgery, Department of Surgery, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC. sung1500@mail.ndmctsgh.edu.tw.

Funding

National Science and Technology Council NSTC 113-2320-B-016-011
6 · The paper itself

Abstract

Findings from a previous study (ClinicalTrials.gov: NCT05118035) demonstrated that an AI-enabled electrocardiogram (AI-ECG), combining AI reports and physician alerts, effectively identified hospitalized patients at high risk of mortality and reduced all-cause mortality. This study evaluates its cost-effectiveness from the health payer's perspective in Taiwan over a 90-day post-intervention period. Cost data were obtained from electronic health records of participating hospitals, and incremental cost-effectiveness ratios (ICERs) per death averted were calculated. Non-parametric bootstrap techniques were used to address uncertainty. Among 15,965 patients, 90-day all-cause mortality was 3.6% in the intervention group versus 4.3% in controls. Medication and ICU costs were higher in the AI-ECG group, but overall medical cost was similar ($6204 vs. $5803). The ICER was $59,500 (95% CI: $-4657 to $385,950) per death averted. The cost-effectiveness acceptability curve showed that 95% of the probability mass lies below a willingness-to-pay threshold of $409,321, supporting favorable cost-effectiveness despite uncertainty.

Identifiers

PMID40494963
PMCPMC12152136

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Registered trials

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.