Dataset Information

Complete bibliographic data, cluster assignments and combined citation network of emergency response operations research extant literature.

ABSTRACT: The Emergency Response Operations Management (EROM) Literature Sample is a collection of 644 papers winnowed from over 5,000 related articles through application of a binary classification tree, collecting the state-of-the-art in decision models of emergencies in progress. References are scraped from each of these 644 publications, to create a dataset describing a total of 14,821 papers linked by 23,175 citation relationships, the analysis of which is presented in, "Modeling Emergency Response Operations: A Theory Building Survey" in Computers and Operations Research[1]. Bibliographic research communities are identified within the data set by framing the task of network partitioning as a cluster ensemble problem from machine learning [2]. This data may be used in several ways, including as an extended reference section for [1], as all 644 papers studied could not be individually cited there. Other examples of potential reuse are further study of a particular research cluster, comparative study of the structural characteristics of this bibliographic network with literature in other fields, and as a test-bed for the further development of robust clustering algorithms.

SUBMITTER: Minas JP

PROVIDER: S-EPMC7334296 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Publications

Complete bibliographic data, cluster assignments and combined citation network of emergency response operations research extant literature.

Minas J P JP Simpson N C NC Tacheva Z Y ZY

Data in brief 20200621

The Emergency Response Operations Management (EROM) Literature Sample is a collection of 644 papers winnowed from over 5,000 related articles through application of a binary classification tree, collecting the state-of-the-art in decision models of emergencies in progress. References are scraped from each of these 644 publications, to create a dataset describing a total of 14,821 papers linked by 23,175 citation relationships, the analysis of which is presented in, "Modeling Emergency Response O ...[more]

PMID: 32642518

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Project description:BackgroundAcademic and non-academic emergency departments (EDs) are regularly compared in clinical operations benchmarking despite suggestion that the two groups may differ in their clinical operations characteristics. and outcomes. We sought to describe and compare clinical operations characteristics of academic versus non-academic EDs.MethodsWe performed a descriptive, comparative analysis of academic and non-academic adult and general EDs with 40,000+ annual encounters, using the Academy of Academic Administrators of Emergency Medicine (AAAEM)/Association of Academic Chairs of Emergency Medicine (AACEM) and Emergency Department Benchmarking Alliance (EDBA) survey results. We defined academic EDs as primary teaching sites for emergency medicine (EM) residencies and non-academic EDs as sites with minimal resident involvement. We constructed the academic and non-academic cohorts from the AAAEM/AACEM and EDBA surveys, respectively, and analyzed metrics common to both surveys.ResultsEighty and 454 EDs met inclusion criteria for academic and non-academic EDs, respectively. Academic EDs had more median annual patient encounters (73,001 vs 54,393), lower median proportion of pediatric patients (6.3% vs 14.5%), higher median proportion of EMS patients (27% vs 19%), and were more commonly designated as Level I or II Trauma Centers (94% vs 24%). Median patient arrival-to-provider times did not differ (26 vs 25 min). Median length-of-stay was longer (277 vs 190 min) for academic EDs, and left-before-treatment-complete was higher (5.7% vs 2.9%). MRI utilization was higher for academic EDs (2.2% patients with at least one MRI vs 1.0 MRIs performed per 100 patients). Patients-per-hour of provider coverage was lower for academic EDs with and without consideration for advanced practice providers and residents.ConclusionsDemographic and operational performance measures differ between academic and non-academic EDs, suggesting that the two groups may be inappropriate operational performance comparators. Causes for the differences remain unclear but the differences appear not to be attributed solely to the academic mission.

Project description:ObjectivesEpidemiological research on the association between diesel exhaust exposure and lung cancer risk has some methodological challenges that give rise to different conclusions and intense debates. This raises the question about the role of selective citation and of citation bias in particular. Our aim was to investigate the occurrence and prevalence of selective citation in this field.DesignCitation analysis.SettingWeb of Science Core Collection.ParticipantsWe identified 96 publications in this network, with 4317 potential citations. For each publication, we extracted characteristics such as study conclusion and funding source. Some of these characteristics are related to the study content: study design, sample size, method of diesel exposure assessment, type of diesel technology under investigation, and whether smoking had been adjusted for.Primary and secondary outcome measuresWhether a citation occurs or not, measured and analysed according to the preregistered protocol. Exploratively we analysed the association between funding source and study conclusion.ResultsMethodological content of a study was clearly related to citation, studies using more sophisticated methods were more likely to be cited. There was some evidence for citation bias: supportive publications had a higher chance of being cited than non-supportive ones, but after adjustment for study quality, this effect decreased substantially (adjusted OR 1.3, 95% CI 1.0 to 1.7). Explorative analyses indicated that three quarters of non-profit funded publications had a supportive study conclusion against only one quarter of the industry-funded publications.ConclusionsThere is evidence for selective citation within this field, but the evidence for citation bias was weak. It seems that factors related to the methodology had more impact on citation than the conclusion of a study. Interestingly, publications that were funded by industry were more skeptical about a causal relationship between diesel exhaust and lung cancer compared to non-profit-funded publications.

Dataset Information

Complete bibliographic data, cluster assignments and combined citation network of emergency response operations research extant literature.

Publications

Complete bibliographic data, cluster assignments and combined citation network of emergency response operations research extant literature.

Similar Datasets

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