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Call for papers - Datasets to advance emergency healthcare

Guest Editor

Mohammad Amin Bahrami, PhD, Shiraz University of Medical Sciences, Iran

Submission Status: Open   |   Submission Deadline: 2 August 2024

Large-scale datasets are revolutionizing emergency medicine. When combined with new technological advances and data analysis techniques, high-quality health data can help practitioners make life-saving decisions more rapidly and efficiently. This Collection seeks to share and showcase these valuable datasets with scientists and the medical community to help improve patient outcomes and healthcare delivery in emergency medicine.

Meet the Guest Editor

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Mohammad Amin Bahrami, PhD, Shiraz University of Medical Sciences, Iran 

Professor Mohammad Amin Bahrami, with more than 20 years of experience in research and teaching healthcare management and policy, strives to help improve global health through health system improvement.

About the Collection

In a medical emergency, making rapid, well-informed decisions is paramount to achieving the best outcome for a patient. High-quality health data paired with new technological advances can help practitioners make life-saving decisions more rapidly and efficiently. Such data can be employed to identify health patterns and trends, aid the development of predictive models to assess emergency healthcare needs and train machine learning algorithms to diagnose conditions and recommend treatments. 

In this unique Collection for BMC Research Notes, we seek to share and showcase valuable datasets to advance data-driven approaches to emergency healthcare. We invite the submission of Data Note articles describing:

  • Medical Records: Anonymized patient data, including demographics, medical history, diagnoses, treatments, and outcomes 
  • Emergency Medical Services (EMS) Data: Vital signs, symptom descriptions, interventions performed, and transportation details 
  • Disease Outbreak Data: Case counts, geographical spread, transmission dynamics, and population demographics 
  • Trauma Registries: Details on injury mechanisms, severity scores, treatments, and outcomes
  • Population health data sets: Public health statistics from regional and district health authorities and family health services
  • Poison Control Data: Data on toxic exposures, substances involved, patient demographics, symptoms, treatments, and outcomes 
  • Pharmacological Databases: Drug interactions, adverse effects, dosages, and contraindications
  • Emergency Department (ED) Data: Patient volumes, wait times, complaints, and disposition outcomes
  • Telemedicine Data: Teleconsultation encounters, patient outcomes, and satisfaction levels 
  • Historical Incident Data: Mass casualty events, disease outbreaks, terrorist attacks, or significant accidents

We will also consider research and review articles discussing the importance and application of these data sets:

  • Creation and curation of comprehensive emergency medicine datasets 
  • Integration of multi-modal data sources for enhanced diagnosis and treatment 
  • Artificial intelligence and machine learning approaches for real-time data analysis
  • Predictive modelling and risk stratification using large-scale datasets 
  • Optimization of resource allocation and triage systems based on data-driven insights 
  • Evaluation and validation of clinical guidelines and protocols using real-world data 
  • Ethical considerations and privacy issues in emergency medicine dataset utilization

We hope this Collection will help foster a deeper understanding of the potential of such datasets to improve emergency medicine while also addressing the challenges associated with their implementation.

*Any potentially sensitive data submitted to this Collection should be appropriately anonymized or deposited in a controlled access repository. For more information, please see our Research data policy on Sensitive data.

Image credit: ME Image /

There are currently no articles in this collection.

Submission Guidelines

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This Collection welcomes submission of original Research Articles and Data Notes. Should you wish to submit a different article type, please read our submission guidelines to confirm that type is accepted by the journal. Articles for this Collection should be submitted via our submission system, Snapp. During the submission process you will be asked whether you are submitting to a Collection, please select "Datasets to advance emergency healthcare" from the dropdown menu.

Articles will undergo the journal’s standard peer-review process and are subject to all of the journal’s standard policies. Articles will be added to the Collection as they are published.

The Editors have no competing interests with the submissions which they handle through the peer review process. The peer review of any submissions for which the Editors have competing interests is handled by another Editorial Board Member who has no competing interests.