Health Evidence and Healthcare-Related Statistic Analysis
A special issue of Healthcare (ISSN 2227-9032). This special issue belongs to the section "Health Informatics and Big Data".
Deadline for manuscript submissions: 31 May 2025 | Viewed by 146
Special Issue Editor
Special Issue Information
Dear Colleagues,
The effective application of statistical methods is essential not only for advancing our understanding of public health challenges but also for directly enhancing healthcare outcomes. In recognition of the critical role that healthcare plays in translating statistical findings into actionable improvements in patient care and disease management, we invite you to contribute a paper to this Special Issue, titled “Health Evidence and Healthcare-Related Statistic Analysis” of Healthcare.
This Special Issue will gather innovative research that leverages statistical methodologies to improve our shared understanding, diagnosis, and treatment of diseases relevant to both public health and clinical practice. We particularly encourage submissions that demonstrate how healthcare systems utilize statistical findings, such as those related to prevalence, incidence, and epidemiology, to inform evidence-based decision-making and enhance the quality of care delivered to patients.
In this Special Issue, original research articles and reviews are welcome. Research areas may include, but are not limited to, the following:
- Innovative statistical methodologies that improve disease understanding, diagnosis, or treatment within healthcare settings;
- Statistical analyses that contribute to our understanding of public health indicators (e.g., prevalence, incidence) and their application in clinical practice to improve patient care;
- Interdisciplinary research that combines statistical methods with healthcare-related fields (e.g., epidemiology, clinical research, bioinformatics) to address health-related challenges;
- Healthcare applications of statistical findings, focusing on how these insights are used to guide treatment protocols, disease prevention strategies, or health policies.
We encourage submissions that focus on a wide range of diseases and conditions relevant to both public health and clinical practice, with an emphasis on how statistical analysis can lead to tangible improvements in healthcare outcomes.
I look forward to receiving your contributions.
Dr. Rodrigo Assar
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Healthcare is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- statistical methods in healthcare
- public health indicators
- healthcare decision-making
- evidence-based medicine
- epidemiology in clinical practice
- health outcomes analysis
- healthcare quality improvement
- health outcomes analysis
- interdisciplinary health research
- clinical data analytics
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