Improving Acceptance Outcomes: Upholding Research Quality and Integrity at BHTY
Due to a significant increase in submissions to Blockchain in Healthcare Today (BHTY), we are reinforcing our editorial standards to ensure the most effective use of editorial leadership and peer reviewer time.
Submissions have grown across a broader global author base, including many authors from emerging regions and those for whom English is not a first language. To reduce unnecessary revisions, delays, and frustration, we are outlining clear expectations designed to support authors in producing high quality manuscripts that meaningfully inform BHTY’s international readership.
At the same time, the scholarly publishing landscape continues
to experience an influx of low quality submissions, pay-to-review schemes, unethical practices, and a rising number of post publication retractions. By clarifying our standards and best practices, we aim to protect the integrity of the journal, strengthen the peer review process, and improve the overall quality, transparency, and value of the submission experience for authors and reviewers alike.
Best
Practices
Categories for papers are below. Refer to Information for Authors for types of papers, definitions, and examples published in the
journal.
- Original Research
- Proof of Concept/Pilots/Methodologies
- Use Case
- Narrative/Systematic Reviews/Meta-Analysis
- Clinical Case Studies
- Technical Briefs & Short Reports
- Opinion, Perspective, Point of View
After you have identified your article category, and before you begin formatting your manuscript, to ensure clarity, rigor, and optimal presentation for peer review, please review the appropriate guidance below for developing each relevant component of your
paper.
A significant number of manuscript rejections result from avoidable formatting and structural issues. Articles reporting original research are generally organized using the IMRAD structure: Introduction, Methods, Results, and Discussion. For an overview of the IMRAD format, please visit https://blog.amwa.org/imrad-format-explained
For additional resources to help authors strengthen article quality and enhance the success of their submission, please see below. Should you have questions or need more guidance, please email the managing editor, John
Russo, PharmD, at r.russo@partnersindigitalhealth.com
NOTE
- Cover Letters are REQUIRED with your manuscript submission and must contain all the elements stated on the Manuscript Preparation page.
- We strongly encourage you provide a link to where your study data is stored for
reference.
What Triggers an Automatic Desk Rejection:
- For manuscripts claiming Original Data Collection:
- Ethics/IRB approval number and institution (required field and verified)
- Informed consent process
description (for human subjects)
- Data availability statement
- Do NOT claim "original research" and mimic clinical trial reporting structure while presenting no original data, claims of multi-center data collection with no ethics approval or pre-registration
- Do NOT submit papers about AI/ML implementation without any actual
models or validation.
- For any manuscript claiming Prospective Study Design include:
- Pre-registration number (ClinicalTrials.gov, PROSPERO, OSF, etc.)
- Protocol availability or justification for absence
- For AI/ML
prediction model papers:
- TRIPOD-AI checklist (mandatory attachment as a supplementary file)
- Code/model availability statement
- Validation cohort description
- For all Submission Cover Letters (REQUIRED):
- Explicit article type selection and why it qualifies as such
- AI writing tool disclosure in the cover letter with which tools were used, the percentage of use, and what was human verified
- Confirmation that structured abstract elements (if used) match actual study design
Red Flags for Authors and Reviewers
- Mismatch between structured abstract format and declared article type
- Claims of multi-center data without institutional specifics
- "Results" sections that describe capabilities rather than measured outcomes
- References to unpublished work
- Excessive arXiv/preprint citations, or thesis sources
- Grandiose claims without specificity ("significantly improved," "revolutionized," "paradigm shift") without data to support the claim
- Perfect grammar, yet lacks semantic substance
- No actual study population
- No ethics approval
- No statistical methods
- No measured outcomes
- "Results" section restates the hypothesis rather than reporting findings
We thank our authors, reviewers, and readers for their continued cooperation and commitment to advancing high quality scholarship in this rapidly evolving field. As market challenges and opportunities emerge, we will keep our community informed of updates and best practices. We also welcome your thoughts, questions, and constructive feedback, which may be submitted to info@partnersindigitalhealth.com. Your engagement helps strengthen the rigor, relevance, and impact of BHTY for our global audience and the broader marketplace
Thank you.