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Estimating Patient and Family Costs and CO2 Emissions for Telehealth and In-Person Health Care Appointments in British Columbia, Canada: Geospatial Mixed Methods Study

Estimating Patient and Family Costs and CO2 Emissions for Telehealth and In-Person Health Care Appointments in British Columbia, Canada: Geospatial Mixed Methods Study

Incorporating a geospatial component allows our method to function for both rural and urban areas and can be applied by other health systems to capture patient costs specific to their region. The advantage of this approach is that it provides a standardized way to calculate these costs that will allow for increased opportunities for economic evaluations and comparisons across different service approaches, such as in-person, telehealth, or hybrid care.

Graham Mainer-Pearson, Kurtis Stewart, Kim Williams, John Pawlovich, Scott Graham, Linda Riches, Sonya Cressman, Kendall Ho

J Med Internet Res 2025;27:e56766

A Geospatial Drug Abuse Risk Assessment and Monitoring Dashboard Tailored for School Students: Development Study With Requirement Analysis and Acceptance Evaluation

A Geospatial Drug Abuse Risk Assessment and Monitoring Dashboard Tailored for School Students: Development Study With Requirement Analysis and Acceptance Evaluation

The government must focus on reducing teens who use drugs, and a geospatial dashboard can help through monitoring and prevention activities. However, previous dashboards were either agency-specific or not practical. This paper reports developing a geospatial dashboard for monitoring drug or substance abuse in Malaysian schools. Several tools are available to help monitor and manage drug abuse, each with its unique strengths (see Multimedia Appendix 1) [8,9,21-30].

Ahmad Mustafa Al-Aboosi, Siti Norul Huda Sheikh Abdullah, Rozmi Ismail, Khairul Nizam Abdul Maulud, Lutfun Nahar, Khairul Akram Zainol Ariffin, Meng Chun Lam, Muhamad Lazim bin Talib, Suzaily Wahab, Mahadzir Elias

JMIR Hum Factors 2024;11:e48139

Geospatial Imprecision With Constraints for Precision Public Health: Algorithm Development and Validation

Geospatial Imprecision With Constraints for Precision Public Health: Algorithm Development and Validation

The Health Insurance Portability and Accountability Act (HIPAA) mandates privacy protections of personal health information in the United States; it outlines which data elements are considered private, including patient addresses needed for geospatial analysis for place-based epidemiology.

Daniel Harris, Chris Delcher

Online J Public Health Inform 2024;16:e54958

Exploring the Association Between Structural Racism and Mental Health: Geospatial and Machine Learning Analysis

Exploring the Association Between Structural Racism and Mental Health: Geospatial and Machine Learning Analysis

To identify geospatial determinants of health across behavioral indicators, built environment, sociocultural environment, and health care (based on the NIMHD framework), georeferenced data sets were acquired from the United States Census Bureau. The United States Census Bureau anonymizes and deidentifies data before releasing them to the public. Detailed demographic data can be obtained only at the Census Tract level (each tract comprises 4000 residents) and not at an individual level.

Fahimeh Mohebbi, Amir Masoud Forati, Lucas Torres, Terri A deRoon-Cassini, Jennifer Harris, Carissa W Tomas, John R Mantsch, Rina Ghose

JMIR Public Health Surveill 2024;10:e52691

Individual and Geospatial Determinants of Health Associated With School-Based Human Papillomavirus Immunization in Alberta: Population-Based Cohort Study

Individual and Geospatial Determinants of Health Associated With School-Based Human Papillomavirus Immunization in Alberta: Population-Based Cohort Study

To address this coverage gap, it is imperative that we identify individual and geospatial determinants of health associated with being underimmunized with the HPV vaccine so that public health professionals can tailor public health planning and interventions toward priority populations. The primary objective of this study was to describe school-based HPV immunization rates by individual and geospatial determinants of health in Alberta.

Jennifer Malkin, Geneviève Jessiman-Perreault, Amanda Alberga Machado, Gary Teare, Joanne Snider, Syed Farhan Tirmizi, Erik Youngson, Ting Wang, Jessica Law, Thilina Bandara, Mika Rathwell, Cordell Neudorf, Lisa Allen Scott

JMIR Public Health Surveill 2024;10:e45508

Effects of Internal and External Factors on Hospital Data Breaches: Quantitative Study

Effects of Internal and External Factors on Hospital Data Breaches: Quantitative Study

Geospatial effects on health care breaches have been explored for states and regions by a few researchers. Raghupathiet al [39] analyzed state-level health care data breaches reported to the HHS OCR. Their results indicated that hacking and server breaches affected most individuals. They also revealed that the number of breaches, the number of affected individuals, and the types of breaches varied by state [39].

Diane Dolezel, Brad Beauvais, Paula Stigler Granados, Lawrence Fulton, Clemens Scott Kruse

J Med Internet Res 2023;25:e51471

A Trauma-Informed, Geospatially Aware, Just-in-Time Adaptive mHealth Intervention to Support Effective Coping Skills Among People Living With HIV in New Orleans: Development and Protocol for a Pilot Randomized Controlled Trial

A Trauma-Informed, Geospatially Aware, Just-in-Time Adaptive mHealth Intervention to Support Effective Coping Skills Among People Living With HIV in New Orleans: Development and Protocol for a Pilot Randomized Controlled Trial

These benefits can be augmented by in-app geospatial awareness, building on prior work that leverages GPS to (for example) alert m Health users to the proximity of HIV and sexual and reproductive health clinics [58,59] or, in contrast, use real-time GPS coordinates to (1) describe routine activity paths and (2) apply this geospatial awareness at a hyperlocal level to address the potential of spatial-environmental stressors to evoke traumatic stress and drive Co C churn and, alternatively, identify restorative

Simone J Skeen, Stephanie Tokarz, Rayna E Gasik, Chelsea McGettigan Solano, Ethan A Smith, Momi Binaifer Sagoe, Lauryn V Hudson, Kara Steele, Katherine P Theall, Gretchen A Clum

JMIR Res Protoc 2023;12:e47151

Using Twitter Data to Estimate the Prevalence of Symptoms of Mental Disorders in the United States During the COVID-19 Pandemic: Ecological Cohort Study

Using Twitter Data to Estimate the Prevalence of Symptoms of Mental Disorders in the United States During the COVID-19 Pandemic: Ecological Cohort Study

Geospatial differences were compared on the basis of random effects. Analysis was conducted in R (version 4.0.3; R Foundation for Statistical Computing) and Geo Pandas. The significant level was set as α=.05 (2-sided). Overall, 49 contiguous states, except for Alaska and Hawaii, were included for the analysis. Table 2 summarizes the CDC-reported and Twitter-based prevalence of symptoms of anxiety, depression, and overall mental disorders across the 4 phases.

Ruilie Cai, Jiajia Zhang, Zhenlong Li, Chengbo Zeng, Shan Qiao, Xiaoming Li

JMIR Form Res 2022;6(12):e37582

Using Machine Learning to Efficiently Vaccinate Homebound Patients Against COVID-19: A Real-time Immunization Campaign

Using Machine Learning to Efficiently Vaccinate Homebound Patients Against COVID-19: A Real-time Immunization Campaign

Next, we projected the data points onto a geospatial visualization for easy interpretability by the scheduling team and providers. Using the Google Maps API, we generated an HTML page that contained pins with distinct numbers and colors representing the cluster to which a patient belonged as well as the patient’s name. Our process was iterative: every week after patients were scheduled and immunized, we updated our census to reflect the remaining number of patients who were unvaccinated.

Anish Kumar, Jennifer Ren, Katherine A Ornstein, Peter M Gliatto

J Med Internet Res 2022;24(7):e37744

Investigating Health Context Using a Spatial Data Analytical Tool: Development of a Geospatial Big Data Ecosystem

Investigating Health Context Using a Spatial Data Analytical Tool: Development of a Geospatial Big Data Ecosystem

We can gain efficiencies through integrated heterogeneous public information sources and the establishment of context through geospatial measures, such as proximity, adjacency, network analysis, and spatial analysis. These then form a new complex of attributes within a single geoenabled knowledgebase.

Timothy Haithcoat, Danlu Liu, Tiffany Young, Chi-Ren Shyu

JMIR Med Inform 2022;10(4):e35073