ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2018
Approaches to Link Geospatially Varying Social, Economic, and Environmental Factors with Electronic Health Record Data to Better Understand Asthma Exacerbations.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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.
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.
Who cites it
10 citing papers in PubMed.
- Augmenting electronic health record data with social and environmental determinant of health measures to understand regional factors associated with asthma exacerbations.PLOS digital health · 2025Article
- Associations between in-home environmental exposures and lung function in a safety net population of children with asthma using electronic health records and geospatial data.Annals of epidemiology · 2025Article
- The Complete Inpatient Record Using Comprehensive Electronic Data (CIRCE) project: A team-based approach to clinically validated, research-ready electronic health record data.Learning health systems · 2025Article
- Racial disparities between measures of area deprivation and financial toxicity, and uterine volume in myomectomy patients.BMC women's health · 2023Article
- Linking Ambient NO2 Pollution Measures with Electronic Health Record Data to Study Asthma Exacerbations.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023Article
- Why Is the Electronic Health Record So Challenging for Research and Clinical Care?Methods of information in medicine · 2021Article
- Consolidated Environmental and Social Data Facilitates Neighborhood-Level Health Studies in Philadelphia.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2021Article
- Geocoding Error, Spatial Uncertainty, and Implications for Exposure Assessment and Environmental Epidemiology.International journal of environmental research and public health · 2020Article
- Impact of Individual versus Geographic-Area Measures of Socioeconomic Status on Health Associations Observed in the Behavioral Risk Factor Surveillance System.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2020Article
- Analysis of Spatial Trends in Smoking Status Among Patients with Obstructive Airway Diseases Highlight Potential for Targeted Smoking Cessation Interventions.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Electronic health record (EHR)-derived data has become an invaluable resource for biomedical research, but is seldom used for the study of the health impacts of social and environmental factors due in part to the unavailability of relevant variables. We describe how EHR-derived data can be enhanced via linking of external sources of social, economic and environmental data when patient-related geospatial information is available, and we illustrate an approach to better understand the geospatial patterns of asthma exacerbation rates in Philadelphia. Specifically, we relate the spatial distribution of asthma exacerbations observed in EHR-derived data to that of known and potential risk factors (i.e., economic deprivation, crime, vehicular traffic, tree cover). Areas of highest risk based on integrated social and environmental data were consistent with an area with increased asthma exacerbations, demonstrating that data external to the EHR can enhance our understanding of negative health-related outcomes.
Indexed as
Identifiers
30815202PMC6371292What Socratic holds
Registered trials
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 Socratic graph.