Evidence map›Paper›PMID 40432049›Full record

ArticleVaccines2025

Vaccination Schedules Recommended by the Centers for Disease Control and Prevention: From Human-Readable to Machine-Processable.

Xia Jing, Hua Min, Yang Gong, Mytchell A Ernst, Aneesa Weaver, Chloe Crozier, David Robinson, Dean F Sittig, Paul G Biondich, Samuil Orlioglu and 9 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Vaccines, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Xia JingDepartment of Public Health, College of Behavioral, Social and Health Sciences, Clemson University, Clemson, SC 29634, USA.ORCID 0000-0002-1916-4588
Hua MinDepartment of Health Administration and Policy, College of Public Health, George Mason University, Fairfax, VA 22030, USA.ORCID 0000-0003-2422-0043
Yang GongDepartment of Clinical and Health Informatics, McWilliams School of Biomedical Informatics, The University of Texas Health Sciences Center at Houston, Houston, TX 77030, USA.
Mytchell A ErnstDepartment of Public Health, College of Behavioral, Social and Health Sciences, Clemson University, Clemson, SC 29634, USA.
Aneesa WeaverDepartment of Public Health, College of Behavioral, Social and Health Sciences, Clemson University, Clemson, SC 29634, USA.
Chloe CrozierSchool of Computing, College of Engineering, Computing and Applied Sciences, Clemson University, Clemson, SC 29634, USA.
David RobinsonIndependent Consultant, Cumbria CA13 0RU, UK.
Dean F SittigDepartment of Clinical and Health Informatics, McWilliams School of Biomedical Informatics, The University of Texas Health Sciences Center at Houston, Houston, TX 77030, USA.ORCID 0000-0001-5811-8915
Paul G BiondichDepartment of Pediatrics, School of Medicine, Indiana University, Indianapolis, IN 46202, USA.
Samuil OrliogluSchool of Computing, College of Engineering, Computing and Applied Sciences, Clemson University, Clemson, SC 29634, USA.
Akash Shanmugan BoobalanSchool of Computing, College of Engineering, Computing and Applied Sciences, Clemson University, Clemson, SC 29634, USA.
Kojo AbanyieDepartment of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15206, USA.ORCID 0000-0003-1552-0327
Richard D BoyceDepartment of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15206, USA.
Adam WrightDepartment of Medicine, School of Medicine, Vanderbilt University, Nashville, TN 37232, USA.
Christian NøhrDepartment of Sustainability and Planning, The Technical Faculty of IT and Design, Danish Center for Health Informatics, Aalborg University, 9000 Aalborg, Denmark.ORCID 0000-0003-1299-7365
Timothy D LawOhio Musculoskeletal and Neurologic Institute, Ohio University, Athens, OH 45701, USA.
Arild FaxvaagDepartment of Neuromedicine and Movement Science, School of Medicine, Norwegian University of Science and Technology, 7491 Trondheim, Norway.ORCID 0000-0002-6510-7306
Lior RennertDepartment of Public Health, College of Behavioral, Social and Health Sciences, Clemson University, Clemson, SC 29634, USA.ORCID 0000-0001-5275-7273
Ronald W GimbelDepartment of Public Health, College of Behavioral, Social and Health Sciences, Clemson University, Clemson, SC 29634, USA.ORCID 0000-0001-8185-4013

Funding

Tissue Structural and Neural Remodeling in Human Sacroiliac JointP20GM121342 · NIGMS · CLEMSON UNIVERSITY · PI Jeryl Jones · 2018 to 2026
$24.7M
Open, interoperable, and configurable clinical decision support modules for OpenMRS, OpenEMR, and beyondR01GM138589 · NIGMS · CLEMSON UNIVERSITY · PI JING, XIA · 2020 to 2024
$1.9M
NIGMS NIH HHS P20 GM121342NIGMS NIH HHS R01 GM138589NIH HHS 3R01GM138589-03S1NIH HHS P20GM121342NIH HHS R01GM138589
6 · The paper itself

Abstract

backgroundReusable, machine-processable clinical decision support system (CDSS) rules have not been widely achieved in the medical informatics field. This study introduces the process, results, challenges faced, and lessons learned while converting the United States of America Centers for Disease Control and Prevention (CDC)-recommended immunization schedules (2022) to machine-processable CDSS rules.

methodsWe converted the vaccination schedules into tabular, charts, MS Excel, and clinical quality language (CQL) formats. The CQL format can be automatically converted to a machine-processable format using existing tools. Therefore, it was regarded as a machine-processable format. The results were reviewed, verified, and tested.

resultsWe have developed 465 rules for 19 vaccines in 13 categories, and we have shared the rules via GitHub to make them publicly available. We used cross-review and cross-checking to validate the CDSS rules in tabular and chart formats. The CQL files were tested for syntax and logic with hypothetical patient HL7 FHIR resources. Our rules can be reused and shared by the health IT industry, CDSS developers, medical informatics educators, or clinical care institutions. The unique contributions of our work are twofold: (1) we created ontology-based, machine-processable, and reusable immunization recommendation rules, and (2) we created and shared multiple formats of immunization recommendation rules publicly which can be a valuable resource for medical and medical informatics communities.

conclusionsThese CDSS rules can be important contributions to informatics communities, reducing redundant efforts, which is particularly significant in resource-limited settings. Despite the maturity and concise presentation of the CDC recommendations, careful attention and multiple layers of verification and review are necessary to ensure accurate conversion. The publicly shared CDSS rules can also be used for health and biomedical informatics education and training purposes.

Indexed as

CDSS rulesCenters for Disease Control and Prevention (CDC)clinical decision support systems (CDSS)clinical quality language (CQL)machine-processablevaccination rulesvaccination schedules

Identifiers

PMID40432049
PMCPMC12116024

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.