Journal Indexing

Structured metadata and indexing support for health statistics research.

Indexing and metadata quality ensure that health statistics research is discoverable by clinicians, researchers, and policymakers.

IJHS prepares structured metadata, DOI registration, and standardized keywords to improve visibility across scholarly platforms.

Accurate metadata improves discovery in health databases, institutional repositories, and scholarly search engines.

Well structured manuscripts accelerate peer review and help readers apply statistical insights to real world health decisions.

Summaries that connect statistical findings to health outcomes improve translation to policy and practice.

Use tables and figures to communicate effect sizes, uncertainty, and subgroup comparisons clearly.

Accurate author details, affiliations, and funding statements improve indexing accuracy and citation tracking.

• ORCID identifiers where available
• Clear keywords and abstracts
• Accurate references with DOIs
• Funding and grant acknowledgments

Authors should verify names, affiliations, funding information, and ORCID identifiers to avoid indexing delays.

Provide uncertainty measures such as confidence intervals or credible intervals for key estimates and model outputs.

Report software versions and packages to support reproducibility across analytic environments.

If external validation is performed, describe population differences and implications for generalizability.

Clear statistical reporting improves the interpretability of health evidence for clinicians, policymakers, and research funders.

Explain how missing data were handled and why chosen strategies were appropriate for the study design.

When combining datasets, document linkage procedures and quality checks for matching accuracy.

Describe any model tuning or hyperparameter selection to support reproducibility in machine learning workflows.

We encourage authors to document assumptions and sensitivity analyses so conclusions remain robust across populations.

When presenting predictive models, report calibration, discrimination, and decision curve metrics where relevant.

Highlight ethical safeguards for patient privacy, especially when working with linked or sensitive datasets.

If data access is restricted, describe the approval process for qualified researchers and expected timelines.

Authors can boost visibility by sharing accepted manuscripts through institutional repositories and professional networks.

For indexing verification requests, contact [email protected].

Transparent reporting of data provenance and governance supports reproducibility and ethical compliance in health statistics.

Define statistical terminology clearly for multidisciplinary readers who apply methods in clinical settings.

Include brief rationale for study design choices to support reviewer understanding and methodological transparency.

For time series analyses, describe seasonality handling and any interventions or policy changes considered.