Evidence map›Paper›PMID 41749726›Full record

ArticleBioengineering (Basel, Switzerland)2026

Operations Research for Pediatric Elective Surgery Planning: Example of a Mathematical Model.

Martina Doneda, Sara Costanzo, Giuliana Carello, Amulya Kumar Saxena, Gloria Pelizzo

Abstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

5 authors.

Martina DonedaDepartment of Information, Management and Production Engineering, University of Bergamo, 24044 Dalmine, Italy.ORCID 0000-0002-1660-3100
Sara CostanzoPediatric Surgery Department, Buzzi Children's Hospital, 20154 Milan, Italy.ORCID 0000-0002-4367-7607
Giuliana CarelloDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy.
Amulya Kumar SaxenaDepartment of Pediatric Surgery, Chelsea Children's Hospital, Chelsea and Westminster Hospital NHS Foundation Trust, Imperial College London, London SW10 9NH, UK.ORCID 0000-0002-7635-7490
Gloria PelizzoPediatric Surgery Department, Buzzi Children's Hospital, 20154 Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The management of operating rooms (ORs) is one of the most studied topics in operations research applied to healthcare. In particular, scheduling elective surgeries in a pediatric and teaching hospital can be a challenge because disruptions occur frequently. The aim of our research was to create a mathematical programming model to schedule day hospital (DH) patients, considering possible disruptions and defining how to best manage the rescheduling process. Our study originates from a collaboration between a high-volume pediatric surgery department and operations research practitioners. The possible disruptions we consider are emergencies and same-day cancellations of planned hospital operations. Elective DH surgeries are scheduled considering the waiting list and the patients' clinical priorities, generating a nominal schedule. This schedule is optimized in conjunction with a series of back-up schedules to guarantee that OR activity immediately recovers in case of a disruption. An ILP-based approach to the problem is proposed. We enumerate a representative subset of the possible emergency and no-show scenarios, and for each of them a back-up plan is designed. The approach reschedules patients, minimizing disruptions with respect to the nominal schedule, and applies an as-soon-as-possible policy in case of emergencies to ensure that all patients receive timely care. The approach is shown to be effective in managing disruptions, ensuring that the waiting list is managed properly, with a balanced mix of urgent and less urgent patients. It provides an effective solution for scheduling patients in a pediatric hospital, considering the unique features of such facilities.

Indexed as

disruption/restorationpediatric surgerysurgery schedulingteaching hospital

Identifiers

PMID41749726
PMCPMC12937738

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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.