Online Journal of Public Health Informatics
A leading peer-reviewed, open access journal dedicated to the dissemination of high-quality research and innovation in the field of public health informatics.
Editor-in-Chief:
Edward K. Mensah PhD, MPhil, Associate Professor Emeritus of Health Economics and Informatics, Health Policy and Administration Division, School of Public Health, University of Illinois Chicago (UIC), USA
Recent Articles
![Inferring Population HIV Viral Load From a Single HIV Clinic’s Electronic Health Record: Simulation Study With a Real-World Example Article Thumbnail](https://asset.jmir.pub/assets/3d06781e90f34fb710250366e2145630.png 480w,https://asset.jmir.pub/assets/3d06781e90f34fb710250366e2145630.png 960w,https://asset.jmir.pub/assets/3d06781e90f34fb710250366e2145630.png 1920w,https://asset.jmir.pub/assets/3d06781e90f34fb710250366e2145630.png 2500w)
![Acceptability of a Digital Adherence Tool Among Patients With Tuberculosis and Tuberculosis Care Providers in Kilimanjaro Region, Tanzania: Mixed Methods Study Article Thumbnail](https://asset.jmir.pub/assets/1aa394dddaded2e3f25d99bef3129db2.png 480w,https://asset.jmir.pub/assets/1aa394dddaded2e3f25d99bef3129db2.png 960w,https://asset.jmir.pub/assets/1aa394dddaded2e3f25d99bef3129db2.png 1920w,https://asset.jmir.pub/assets/1aa394dddaded2e3f25d99bef3129db2.png 2500w)
![Bringing the Public Health Informatics and Technology Workforce Together: The PHIAT Conference Article Thumbnail](https://asset.jmir.pub/assets/20ed683dd2630130c4a98aa500efd712.png 480w,https://asset.jmir.pub/assets/20ed683dd2630130c4a98aa500efd712.png 960w,https://asset.jmir.pub/assets/20ed683dd2630130c4a98aa500efd712.png 1920w,https://asset.jmir.pub/assets/20ed683dd2630130c4a98aa500efd712.png 2500w)
The field of public health informatics has undergone significant evolution in recent years, and advancements in technology and its applications are imperative to address emerging public health challenges. Interdisciplinary approaches and training can assist with these challenges. In 2023, the inaugural Public Health Informatics and Technology (PHIAT) Conference was established as a hybrid 3-day conference at the University of California, San Diego, and online. The conference’s goal was to establish a forum for academics and public health organizations to discuss and tackle new opportunities and challenges in public health informatics and technology. This paper provides an overview of the quest for interest, speakers and topics, evaluations from the attendees, and lessons learned to be implemented in future conferences.
![e-Cigarette Tobacco Flavors, Public Health, and Toxicity: Narrative Review Article Thumbnail](https://asset.jmir.pub/assets/f6403d0c1df838c401fe7de01d52e771.png 480w,https://asset.jmir.pub/assets/f6403d0c1df838c401fe7de01d52e771.png 960w,https://asset.jmir.pub/assets/f6403d0c1df838c401fe7de01d52e771.png 1920w,https://asset.jmir.pub/assets/f6403d0c1df838c401fe7de01d52e771.png 2500w)
Recently, the US Food and Drug Administration implemented enforcement priorities against all flavored, cartridge-based e-cigarettes other than menthol and tobacco flavors. This ban undermined the products’ appeal to vapers, so e-cigarette manufacturers added flavorants of other attractive flavors into tobacco-flavored e-cigarettes and reestablished appeal.
![Geospatial Imprecision With Constraints for Precision Public Health: Algorithm Development and Validation Article Thumbnail](https://asset.jmir.pub/assets/15c73ddbfe604881d9182cdf5013042e.png 480w,https://asset.jmir.pub/assets/15c73ddbfe604881d9182cdf5013042e.png 960w,https://asset.jmir.pub/assets/15c73ddbfe604881d9182cdf5013042e.png 1920w,https://asset.jmir.pub/assets/15c73ddbfe604881d9182cdf5013042e.png 2500w)
![Intention to Use Mobile-Based Partograph and Its Predictors Among Obstetric Health Care Providers Working at Public Referral Hospitals in the Oromia Region of Ethiopia in 2022: Cross-Sectional Questionnaire Study Article Thumbnail](https://asset.jmir.pub/assets/fea5d400ce0c54f87fbad9a92972a294.png 480w,https://asset.jmir.pub/assets/fea5d400ce0c54f87fbad9a92972a294.png 960w,https://asset.jmir.pub/assets/fea5d400ce0c54f87fbad9a92972a294.png 1920w,https://asset.jmir.pub/assets/fea5d400ce0c54f87fbad9a92972a294.png 2500w)
A partograph is a pictorial representation of the relationship between cervical dilatation and the time used to diagnose prolonged and obstructed labor. However, the utilization of paper-based partograph is low and it is prone to documentation errors, which can be avoided with the use of electronic partographs. There is only limited information on the proportion of intention to use mobile-based partographs and its predictors.
![Characterization of Post–COVID-19 Definitions and Clinical Coding Practices: Longitudinal Study Article Thumbnail](https://asset.jmir.pub/assets/36ec64a13a47035650ea5f3b333f60ba.png 480w,https://asset.jmir.pub/assets/36ec64a13a47035650ea5f3b333f60ba.png 960w,https://asset.jmir.pub/assets/36ec64a13a47035650ea5f3b333f60ba.png 1920w,https://asset.jmir.pub/assets/36ec64a13a47035650ea5f3b333f60ba.png 2500w)
Post–COVID-19 condition (colloquially known as “long COVID-19”) characterized as postacute sequelae of SARS-CoV-2 has no universal clinical case definition. Recent efforts have focused on understanding long COVID-19 symptoms, and electronic health record (EHR) data provide a unique resource for understanding this condition. The introduction of the International Classification of Diseases, Tenth Revision (ICD-10) code U09.9 for “Post COVID-19 condition, unspecified” to identify patients with long COVID-19 has provided a method of evaluating this condition in EHRs; however, the accuracy of this code is unclear.
![Deriving Treatment Decision Support From Dutch Electronic Health Records by Exploring the Applicability of a Precision Cohort–Based Procedure for Patients With Type 2 Diabetes Mellitus: Precision Cohort Study Article Thumbnail](https://asset.jmir.pub/assets/27b674f694b3e872116a28f3dcf85b97.png 480w,https://asset.jmir.pub/assets/27b674f694b3e872116a28f3dcf85b97.png 960w,https://asset.jmir.pub/assets/27b674f694b3e872116a28f3dcf85b97.png 1920w,https://asset.jmir.pub/assets/27b674f694b3e872116a28f3dcf85b97.png 2500w)
![Effect of Long-Distance Domestic Travel Ban Policies in Japan on COVID-19 Outbreak Dynamics During Dominance of the Ancestral Strain: Ex Post Facto Retrospective Observation Study Article Thumbnail](https://asset.jmir.pub/assets/c1e929e148dbdb060d8c8191707d0ca5.png 480w,https://asset.jmir.pub/assets/c1e929e148dbdb060d8c8191707d0ca5.png 960w,https://asset.jmir.pub/assets/c1e929e148dbdb060d8c8191707d0ca5.png 1920w,https://asset.jmir.pub/assets/c1e929e148dbdb060d8c8191707d0ca5.png 2500w)
In Japan, long-distance domestic travel was banned while the ancestral SARS-CoV-2 strain was dominant under the first declared state of emergency from March 2020 until the end of May 2020. Subsequently, the “Go To Travel” campaign travel subsidy policy was activated, allowing long-distance domestic travel, until the second state of emergency as of January 7, 2021. The effects of this long-distance domestic travel ban on SARS-CoV-2 infectivity have not been adequately evaluated.
![Applying Machine Learning Techniques to Implementation Science Article Thumbnail](https://asset.jmir.pub/assets/c7d2fdaee7e2c2af048cb917ed337f2b.png 480w,https://asset.jmir.pub/assets/c7d2fdaee7e2c2af048cb917ed337f2b.png 960w,https://asset.jmir.pub/assets/c7d2fdaee7e2c2af048cb917ed337f2b.png 1920w,https://asset.jmir.pub/assets/c7d2fdaee7e2c2af048cb917ed337f2b.png 2500w)
Machine learning (ML) approaches could expand the usefulness and application of implementation science methods in clinical medicine and public health settings. The aim of this viewpoint is to introduce a roadmap for applying ML techniques to address implementation science questions, such as predicting what will work best, for whom, under what circumstances, and with what predicted level of support, and what and when adaptation or deimplementation are needed. We describe how ML approaches could be used and discuss challenges that implementation scientists and methodologists will need to consider when using ML throughout the stages of implementation.
![Machine Learning for Prediction of Tuberculosis Detection: Case Study of Trained African Giant Pouched Rats Article Thumbnail](https://asset.jmir.pub/assets/cfe329c9482ec1013db90505a16eda7b.png 480w,https://asset.jmir.pub/assets/cfe329c9482ec1013db90505a16eda7b.png 960w,https://asset.jmir.pub/assets/cfe329c9482ec1013db90505a16eda7b.png 1920w,https://asset.jmir.pub/assets/cfe329c9482ec1013db90505a16eda7b.png 2500w)
Technological advancement has led to the growth and rapid increase of tuberculosis (TB) medical data generated from different health care areas, including diagnosis. Prioritizing better adoption and acceptance of innovative diagnostic technology to reduce the spread of TB significantly benefits developing countries. Trained TB-detection rats are used in Tanzania and Ethiopia for operational research to complement other TB diagnostic tools. This technology has increased new TB case detection owing to its speed, cost-effectiveness, and sensitivity.