Evidence map›Paper›PMID 42462507›Full record

ArticleClinics (Sao Paulo, Brazil)2026

Logistic challenges in implementing a multispecialty robotic surgery program at university hospitals.

Antonio Jose Rodrigues Pereira, Ricardo Zugaib Abdalla, Ivan Cecconello, William Carlos Nahas, Evelinda Marramon Trindade, Ana Maria Malik

Abstract read
In one paragraph

Article in Clinics (Sao Paulo, Brazil), 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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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

6 authors.

Antonio Jose Rodrigues PereiraBusiness Administration São Paulo School of Business Administration of Getulio Vargas Foundation, São Paulo, SP, Brazil; Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo (HCFMUSP), São Paulo, SP, Brazil.
Ricardo Zugaib AbdallaGastroenterology Department, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo (HCFMUSP), São Paulo, SP, Brazil. Electronic address: ricardo.abdalla@hc.fm.usp.br.
Ivan CecconelloGastroenterology Department, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo (HCFMUSP), São Paulo, SP, Brazil.
William Carlos NahasUrology Department, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo (HCFMUSP), São Paulo, SP, Brazil.
Evelinda Marramon TrindadeHospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo (HCFMUSP), São Paulo, SP, Brazil.
Ana Maria MalikBusiness Administration São Paulo School of Business Administration of Getulio Vargas Foundation, São Paulo, SP, Brazil; Medicine (Preventive Medicine) from the Universidade de São Paulo, São Paulo, SP, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe integration of innovative, high-cost technologies like robotic surgery presents significant managerial and logistical challenges within public university hospitals. While previous research often highlights clinical outcomes, pragmatic studies on the administrative and organizational complexities of implementation are scarce. This manuscript aims to address this gap by analyzing the multifaceted logistical issues encountered during the establishment of a multispecialty robotic surgery program.

objectiveThis study's primary objective is to evaluate the managerial and logistical aspects of adopting a surgical robot in a public hospital, focusing on the administrative processes, institutional adjustments, and systemic challenges that impact patient care and institutional sustainability. The authors sought to identify key lessons learned from this experience and enumerate the institutional knowledge gained during the integration of this technology. MATERIALS AND

methodsThis study utilized a mixed-methods approach, combining an analysis of institutional data and semi-structured interviews with managers and professionals involved in the decision-making and adoption process. Data collected included demographic details, surgical times, and postoperative outcomes, which served as management indicators. The study's framework was informed by organizational and diffusion of innovation theories to reconstruct the history of the decision-making process.

resultsThe implementation of robotic surgery required substantial adjustments to hospital infrastructure, work processes, and personnel training. Key logistical difficulties documented included dependency on a single supplier, delays in importing materials, high costs without market competition, and extensive training requirements. While robotic surgery demonstrated clinical advantages, such as lower complication rates (4.2%vs. 5.2%) and reduced blood loss (266.2 mL vs. 598.2 mL), its successful adoption was contingent on detailed planning and effective management to minimize these logistical challenges and optimize benefits. The study also revealed a protracted learning curve for the surgical teams, although operative times showed a decreasing trend with increased experience.

conclusionThe successful implementation of robotic surgery in a public teaching hospital requires a dedicated focus on logistical planning, stakeholder engagement, and adaptive management. Preemptive modeling of costs, diversified supplier relationships, and phased training are essential for sustainability. These findings provide valuable guidance for similar institutions aiming to integrate disruptive surgical technologies.

Indexed as

Cost analysisHealthcare managementImplementation scienceInfrastructureLogistical challengesMultispecialty programOperational efficiencyOrganizational changePatient outcomesPublic hospitalRobotic surgeryStakeholder engagementSurgical innovationTechnology adoptionTraining

Identifiers

PMID42462507
PMCPMC13383944

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.