ReviewThe open medical informatics journal2018
A Review of Data Quality Assessment in Emergency Medical Services.
Review in The open medical informatics journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
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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.
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Who cites it
22 citing papers in PubMed.
- Research on the Quality Evaluation Indicators of Real-World Data in the Review of Anti-Tumor Drugs for Chinese Regulatory Frameworks.Therapeutic innovation & regulatory science · 2026Article
- Machine learning models powered by emergency medical services data enhance stroke triage in prehospital settings.Scientific reports · 2026Article
- Article
- Assessing Data Completeness in Emergency Medical Team Reports: Analysis of the Response to Cyclone Idai in Mozambique using the WHO Minimum Data Set.Archives of academic emergency medicine · 2025Article
- Implementation of major trauma app: usability and data completeness.BMC emergency medicine · 2024Article
- Frameworks, Dimensions, Definitions of Aspects, and Assessment Methods for the Appraisal of Quality of Health Data for Secondary Use: Comprehensive Overview of Reviews.JMIR medical informatics · 2024Review
- Consensus-based recommendations for strengthening emergency care at primary health care level: a Delphi study.Global health action · 2023Article
- Database quality assessment in research in paramedicine: a scoping review.Scandinavian journal of trauma, resuscitation and emergency medicine · 2023Article
- Data completeness and consistency in individual medical records of institutional births: retrospective crossectional study from Northwest Ethiopia, 2022.BMC health services research · 2023Article
- Data Quality in Health Research: Integrative Literature Review.Journal of medical Internet research · 2023Review
- A New Strategy for Evaluating the Quality of Laboratory Results for Big Data Research: Using External Quality Assessment Survey Data (2010-2020).Annals of laboratory medicine · 2023Article
- Emergency department-based injury surveillance information system: a conceptual model.BMC emergency medicine · 2023Article
- Data quality assessment in emergency medical services: an objective approach.BMC emergency medicine · 2023Article
- Lifting Hospital Electronic Health Record Data Treasures: Challenges and Opportunities.JMIR medical informatics · 2022Article
- Article
- Evaluation of freely available data profiling tools for health data research application: a functional evaluation review.BMJ open · 2022Review
- Developing a systematic approach to assessing data quality in secondary use of clinical data based on intended use.Learning health systems · 2022Article
- Can Prehospital Data Improve Early Identification of Sepsis in Emergency Department? An Integrative Review of Machine Learning Approaches.Applied clinical informatics · 2022Review
- An automated data cleaning method for Electronic Health Records by incorporating clinical knowledge.BMC medical informatics and decision making · 2021Article
- Data Quality Assessment in Emergency Medical Services: What Are the Stakeholders' Perspectives?Perspectives in health information managemen · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionData quality is an important issue in emergency medicine. The unique characteristics of emergency care services, such as high turn-over and the speed of work may increase the possibility of making errors in the related settings. Therefore, regular data quality assessment is necessary to avoid the consequences of low quality data. This study aimed to identify the main dimensions of data quality which had been assessed, the assessment approaches, and generally, the status of data quality in the emergency medical services.
methodsThe review was conducted in 2016. Related articles were identified by searching databases, including Scopus, Science Direct, PubMed and Web of Science. All of the review and research papers related to data quality assessment in the emergency care services and published between 2000 and 2015 (n=34) were included in the study.
resultsThe findings showed that the five dimensions of data quality; namely, data completeness, accuracy, consistency, accessibility, and timeliness had been investigated in the field of emergency medical services. Regarding the assessment methods, quantitative research methods were used more than the qualitative or the mixed methods. Overall, the results of these studies showed that data completeness and data accuracy requires more attention to be improved.
conclusionIn the future studies, choosing a clear and a consistent definition of data quality is required. Moreover, the use of qualitative research methods or the mixed methods is suggested, as data users' perspectives can provide a broader picture of the reasons for poor quality data.
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