Evidence map›Paper›PMID 42488222›Full record

ArticleFrontiers in pediatrics2026

Asymmetric surge optimization during peak seasons: a discrete-event simulation of centralized fast-track operating rooms at a China National Children's Medical Center.

Yu Chen, Weihong Xu, Nanping Shen, Jiwen Sun, Bin Ji, Siyuan Wang, Wei Chen

Abstract read
In one paragraph

Article in Frontiers in pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Yu Chen *Department of Anesthesiology, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Weihong Xu *Department of Anesthesiology, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Nanping ShenDepartment of Nursing, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jiwen SunDepartment of Nursing, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Bin JiDepartment of Anesthesiology, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Siyuan WangDepartment of Anesthesiology, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Wei ChenDepartment of Anesthesiology, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Holiday-related effects result in a substantial surge in the volume of pediatric surgeries. Managing operating room (OR) capacity during summer holiday is immensely challenging for a China National Children's Medical Center. A surge of pediatric surgeries is inherently asymmetric, characterized by a disproportionate increase in short elective procedures, while the volume of complex surgeries remains relatively stable. Traditional mixed-acuity scheduling or naive departmental segregation often results in severe capacity fragmentation. This study employs discrete-event simulation (DES) to propose and evaluate an asymmetric, centralized fast-track OR allocation strategy. Methods: Using retrospective, de-identified operational data from Shanghai Children's Medical Center, a National Children's Medical Center in China, we constructed a DES model representing the workflow of diverse surgical departments. Following a retrospective iterative calibration ensuring <2% baseline error, we introduced a Prospective Simulation Probing (PSP) mechanism under a dynamic safety-buffer policy to determine variance-penalized daily capacities. In the primary optimized scenario, fast-track turnover was modeled as Triangle (10, 12.5, 15) minutes rather than regular-OR Triangle (25, 27.5, 30) minutes, corresponding to a 15-minute mean reduction; 5- and 10-minute reduction scenarios were tested separately. OR days were first allocated to secure historical complex surgery volumes, after which residual days were pooled into a centralized fast-track center. Uncertainty was summarized as mean, SD, median, and 95% simulation intervals; sensitivity analyses varied turnover reduction, bounded fast-track demand, and edge-case fast-track classification. Results: Simulation revealed that simplistic departmental segregation penalized low-volume specialties, reducing their throughput due to idle-time waste. Conversely, the asymmetric centralized pooling model protected severe, slow-track case throughput while increasing fast-track capacity. The optimized 15-minute turnover-reduction scenario yielded a mean total throughput of 3,588.7 cases (median 3,589; 95% simulation interval, 3,562-3,614), corresponding to a 38.29% increase over the historical baseline of 2,595 cases (95% interval for increase, 37.26%-39.27%). Under the more conservative 10-minute reduction scenario, mean throughput was 3,208.3 cases, a 23.63% increase. Conclusions: DES modeling suggests that overcoming pediatric surgery surge requires separating short fast-track procedures from complex surgeries while explicitly protecting complex-care access. Consolidating short procedures into dedicated, homogeneous ORs can reduce non-operative turnover waste and increase throughput; however, implementation depends on staffing flexibility, sufficient fast-track demand, and local cost considerations.

Indexed as

discrete event simulationhospital managementoperating room efficiencypediatric surgerysurgery schedule management

Identifiers

PMID42488222
PMCPMC13388461

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.