scholarly journals FHIR PIT: an open software application for spatiotemporal integration of clinical data and environmental exposures data

2020 ◽  
Author(s):  
Hao Xu ◽  
Steven Cox ◽  
Lisa Stillwell ◽  
Emily Pfaff ◽  
James Champion ◽  
...  
Keyword(s):  
Environmental Health ◽  
Clinical Data ◽  
Environmental Exposures ◽  
Data Sources ◽  
Spatiotemporal Data ◽  
Use Case ◽  
Software Application ◽  
Individual Level ◽  
Health And Disease ◽  
The Impact

Abstract Background: Informatics tools to support the integration and subsequent interrogation of spatiotemporal data such as clinical data and environmental exposures data are lacking. Such tools are needed to support research in environmental health and any biomedical field that is challenged by the need for integrated spatiotemporal data to examine individual-level determinants of health and disease. Results: We have developed an open-source software application—FHIR PIT (Health Level 7 Fast Healthcare Interoperability Resources Patient data Integration Tool)—to enable studies on the impact of individual-level environmental exposures on health and disease. FHIR PIT was motivated by the need to integrate patient data derived from our institution’s clinical warehouse with a variety of public data sources on environmental exposures and then openly expose the data via ICEES (Integrated Clinical and Environmental Exposures Service). FHIR PIT consists of transformation steps or building blocks that can be chained together to form a transformation and integration workflow. Several transformation steps are generic and thus can be reused. As such, new types of data can be incorporated into the modular FHIR PIT pipeline by simply reusing generic steps or adding new ones. We have validated FHIR PIT in the context of a driving use case designed to investigate the impact of airborne pollutant exposures on asthma. Specifically, we replicated published findings demonstrating racial disparities in the impact of airborne pollutants on asthma exacerbations.Conclusions: While FHIR PIT was developed to support our driving use case, the software can be used to integrate any type and number of spatiotemporal data sources at a level of granularity that enables individual-level study. We expect FHIR PIT to facilitate research in environmental health and numerous other biomedical disciplines.

scholarly journals FHIR PIT: an open software application for spatiotemporal integration of clinical data and environmental exposures data

2020 ◽  
Author(s):  
Hao Xu ◽  
Steven Cox ◽  
Lisa Stillwell ◽  
Emily Pfaff ◽  
James Champion ◽  
...  
Keyword(s):  
Environmental Health ◽  
Clinical Data ◽  
Environmental Exposures ◽  
Data Sources ◽  
Spatiotemporal Data ◽  
Use Case ◽  
Software Application ◽  
Individual Level ◽  
Health And Disease ◽  
The Impact

Abstract Background Informatics tools to support the integration and subsequent interrogation of spatiotemporal data such as clinical data and environmental exposures data are lacking. Such tools are needed to support research in environmental health and any biomedical field that is challenged by the need for integrated spatiotemporal data to examine individual-level determinants of health and disease. Results We have developed an open-source software application—FHIR PIT (Health Level 7 Fast Healthcare Interoperability Resources Patient data Integration Tool)—to enable studies on the impact of individual-level environmental exposures on health and disease. FHIR PIT was motivated by the need to integrate patient data derived from our institution’s clinical warehouse with a variety of public data sources on environmental exposures and then openly expose the data via ICEES (Integrated Clinical and Environmental Exposures Service). FHIR PIT consists of transformation steps or building blocks that can be chained together to form a transformation and integration workflow. Several transformation steps are generic and thus can be reused. As such, new types of data can be incorporated into the modular FHIR PIT pipeline by simply reusing generic steps or adding new ones. We have validated FHIR PIT in the context of a driving use case designed to investigate the impact of airborne pollutant exposures on asthma. Specifically, we replicated published findings demonstrating racial disparities in the impact of airborne pollutants on asthma exacerbations. Conclusions While FHIR PIT was developed to support our driving use case, the software can be used to integrate any type and number of spatiotemporal data sources at a level of granularity that enables individual-level study. We expect FHIR PIT to facilitate research in environmental health and numerous other biomedical disciplines.

scholarly journals FHIR PIT: an open software application for spatiotemporal integration of clinical data and environmental exposures data

2019 ◽  
Author(s):  
Hao Xu ◽  
Steven Cox ◽  
Lisa Stillwell ◽  
Emily Pfaff ◽  
James Champion ◽  
...  
Keyword(s):  
Environmental Health ◽  
Clinical Data ◽  
Environmental Exposures ◽  
Data Sources ◽  
Spatiotemporal Data ◽  
Use Case ◽  
Software Application ◽  
Individual Level ◽  
Health And Disease ◽  
The Impact

Abstract Background Informatics tools to support the integration and subsequent interrogation of spatiotemporal data such as clinical data and environmental exposures data are lacking. Such tools are needed to support research in environmental health and any biomedical field that is challenged by the need for integrated spatiotemporal data to examine individual-level determinants of health and disease. Results We have developed an open-source software application—FHIR PIT (Health Level 7 Fast Healthcare Interoperability Resource Patient data Integration Tool)—to enable studies on the impact of individual-level environmental exposures on health and disease. FHIR PIT was motivated by the need to integrate patient data derived from our institution’s clinical warehouse with a variety of public data sources on environmental exposures and then openly expose the data via ICEES (Integrated Clinical and Environmental Exposures Service). FHIR PIT consists of transformation steps or building blocks that can be chained together to form a transformation and integration workflow. Several transformation steps are generic and thus can be reused. As such, new types of data can be incorporated into the modular FHIR PIT pipeline by simply reusing generic steps or adding new ones. We have validated FHIR PIT in the context of a driving use case designed to investigate the impact of airborne pollutant exposures on asthma. Specifically, we replicated published findings demonstrating racial disparities in the impact of airborne pollutants on asthma exacerbations. Conclusions While FHIR PIT was developed to support our driving use case, the software can be used to integrate any type and number of spatiotemporal data sources at a level of granularity that enables individual-level study. We expect FHIR PIT to facilitate research in environmental health and numerous other biomedical disciplines.

scholarly journals Understanding the coverage of Statistics New Zealand's Integrated Data Infrastructure

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Gareth Minshall ◽  
Antony Gomez ◽  
Bycroft Christine
Keyword(s):  
New Zealand ◽  
Census Data ◽  
Target Population ◽  
Data Sources ◽  
Multiple Sources ◽  
Unique Identifier ◽  
Data Infrastructure ◽  
Individual Level ◽  
Education Data ◽  
The Impact

ABSTRACTObjectivesStatistics New Zealand’s Integrated Data Infrastructure (IDI) combines information from a range of government agencies (such as tax, health and education data) in order to provide the insights government needs to improve social and economic outcomes for New Zealanders. New Zealand has no national population register or unique identifier used in common across these multiple data sources, and probabilistic linkages are a feature of the IDI. A challenge for researchers is to understand the impact of linkage errors and coverage issues present in the linked data, and to develop the rules necessary to define their target population. We outline the statistical infrastructure Statistics New Zealand is developing to help researchers navigate these issues. ApproachA method has been developed to identify NZ residents at a given time from the much larger number of individuals present in the IDI. Census data linked to the IDI offers insight into the coverage of key population groups and the quality of the attribute information held in the IDI (e.g. location and ethnicity). We are assessing ways that Statistics New Zealand could use these findings to assist researchers in forming their population of interest and assess the potential for bias. ResultsThe derived administrative resident population is compared with the official population figures and patterns of under- and over-coverage are identified at an aggregate, and individual level. Some coverage discrepancies may be improved through reducing linkage errors. Comparison with census data reveals some significant quality issues with location and ethnicity variables in administrative collections. Work is underway to improve methods for combining information from multiple sources of varying quality. ConclusionIdentifying NZ residents at a given time, and quantifying errors in administrative data sources will assist researchers ability to recognise and adjust for these errors in their analysis. Simply quantifying (often for the first time) the limitations of administrative sources also provides impetus to improving the collection of these variables at source.

scholarly journals Green-Blue Spaces and Mental Health: A Longitudinal Data Linkage Study

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Daniel A Thompson ◽  
Mark Nieuwenhuijsen ◽  
James White ◽  
Rebecca Lovell ◽  
Mathew White ◽  
...  
Keyword(s):  
Mental Health ◽  
Administrative Data ◽  
Data Linkage ◽  
Well Being ◽  
Data Sources ◽  
Household Level ◽  
Individual Level ◽  
The Impact ◽  
Over Time ◽  
Sector Data

IntroductionA growing evidence base indicates health benefits are associated with access to green-blue spaces (GBS), such as beaches and parks. However, few studies have examined associations with changes in access to GBS over time. Objectives and ApproachWe have linked cross-sector data collected within Wales, United Kingdom, quarterly from 2008 to 2019, to examine the impact of GBS access on individual-level well-being and common mental health disorders (CMD). We created a longitudinal dataset of GBS access metrics, derived from satellite and administrative data sources, for 1.4 million homes in Wales. These household-level metrics were linked to individuals using the Welsh Demographic Service Dataset within the Secure Anonymised Information Linkage (SAIL) Databank. Linkage to Welsh Longitudinal General Practice data within SAIL enabled us to identify individual-level CMD over time. We also linked individual-level self-reported GBS use and well-being data from the National Survey for Wales (NSW) to routine data for cross-sectional survey participants. ResultsWe created a longitudinal cohort panel capturing all 2.84 million adults aged 16+ living in Wales between 2008 and 2019 and with a general practitioner (GP) registration. Individual-level health data and household-level environmental metrics were linked for each quarter an individual is in the study. Household addresses were linked to 97% of the cohort, creating 110+ million rows of anonymously linked cross-sector data. The cohort provides an average follow-up period of 8 years, during which 565,168 (20%) adults received at least one CMD diagnosis or symptom. Conclusion / ImplicationsThis example of multi-sectoral data linkage across multiple environmental and administrative data sources has created a rich data source, which we will use toquantify the impact of changes in GBS access on individual–level CMD and well-being. This evidence will inform policy in the areas of health, planning and the environment.

scholarly journals Harmonic analysis PQM data in 150kV grid of TSO TenneT in Brabant, The Netherlands

2021 ◽  
Vol 19 ◽  
pp. 298-303
Author(s):  
W.L. Broekman ◽  
◽  
J.B.M. van Waes ◽  
V. Cuk ◽  
J.F.G. Cobben
Keyword(s):  
The Netherlands ◽  
Data Processing ◽  
Power Quality ◽  
Data Sources ◽  
Use Case ◽  
Multiple Use ◽  
Transmission Grid ◽  
The Impact ◽  
Measured Response ◽  
Insight Into

This paper aims to provide an insight into the measured background changes of harmonics due to operational changes in a typical Dutch transmission grid. Multiple use cases on different locations throughout a meshed 150kV grid have been considered. The nodes that were studied had measured exceedances of planning levels or were indicated to be critical for the future in earlier studies. This study provides an insight into the measured response of harmonics with respect to different operational changes such as specific scheduled outages that occurred and the impact of capacitor banks. Per use-case, individual conclusions are reported. The analysis was conducted on data of power quality meters (PQM) and various other data sources provided by the Dutch TSO TenneT. Data-processing, visualization, and computations were performed using Python. These results are useful for model validation, planning purposes, and maintaining power quality.

scholarly journals Evolution of DOHaD: the impact of environmental health sciences

2014 ◽  
Vol 6 (2) ◽  
pp. 55-64 ◽  
Author(s):  
A. C. Haugen ◽  
T. T. Schug ◽  
G. Collman ◽  
J. J. Heindel
Keyword(s):  
Environmental Health ◽  
Early Life ◽  
Communicable Disease ◽  
Environmental Exposures ◽  
Later Life ◽  
Health Sciences ◽  
Environmental Chemical ◽  
Chemical Exposures ◽  
Environmental Health Sciences ◽  
The Impact

Environmental exposures have a significant influence on the chronic health conditions plaguing children and adults. Although the Developmental Origins of Health and Disease (DOHaD) paradigm historically has focused on nutrition, an expanding body of research specifically communicates the effects of chemical exposures on early-life development and the propagation of non-communicable disease across the lifespan. This paper provides an overview of 20 years of research efforts aimed at identifying critical windows of susceptibility to environmental exposures and the signaling changes and epigenetic influences associated with disease progression. DOHaD grants funded by the National Institute of Environmental Health Sciences (NIEHS) in 1991, 2001 and 2011 are identified by grant-analysis software, and each portfolio is analyzed for exposures, disease endpoints, windows of exposure, study design and impact on the field based on publication data. Results show that the 1991 and 2001 portfolios comprised metals, PCBs and air pollutants; however, by 2011, the portfolio has evolved to include or expand the variety of endocrine disruptors, pesticides/persistent organic pollutants and metals. An assortment of brain-health endpoints is most targeted across the portfolios, whereas reproduction and cancer increase steadily over the same time period, and new endpoints like obesity are introduced by 2011. With mounting evidence connecting early-life exposures to later-life disease, we conclude that it is critical to expand the original DOHaD concept to include environmental chemical exposures, and to continue a research agenda that emphasizes defining sensitive windows of exposure and the mechanisms that cause disease.

scholarly journals Open Application of Statistical and Machine Learning Models to Explore the Impact of Environmental Exposures on Health and Disease: An Asthma Use Case

2021 ◽  
Vol 18 (21) ◽  
pp. 11398
Author(s):  
Bo Lan ◽  
Perry Haaland ◽  
Ashok Krishnamurthy ◽  
David B. Peden ◽  
Patrick L. Schmitt ◽  
...  
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Linear Model ◽  
Generalized Linear Model ◽  
Environmental Exposures ◽  
Predictor Variables ◽  
Use Case ◽  
Airborne Particulate ◽  
Particulate Exposure ◽  
The Impact

ICEES (Integrated Clinical and Environmental Exposures Service) provides a disease-agnostic, regulatory-compliant approach for openly exposing and analyzing clinical data that have been integrated at the patient level with environmental exposures data. ICEES is equipped with basic features to support exploratory analysis using statistical approaches, such as bivariate chi-square tests. We recently developed a method for using ICEES to generate multivariate tables for subsequent application of machine learning and statistical models. The objective of the present study was to use this approach to identify predictors of asthma exacerbations through the application of three multivariate methods: conditional random forest, conditional tree, and generalized linear model. Among seven potential predictor variables, we found five to be of significant importance using both conditional random forest and conditional tree: prednisone, race, airborne particulate exposure, obesity, and sex. The conditional tree method additionally identified several significant two-way and three-way interactions among the same variables. When we applied a generalized linear model, we identified four significant predictor variables, namely prednisone, race, airborne particulate exposure, and obesity. When ranked in order by effect size, the results were in agreement with the results from the conditional random forest and conditional tree methods as well as the published literature. Our results suggest that the open multivariate analytic capabilities provided by ICEES are valid in the context of an asthma use case and likely will have broad value in advancing open research in environmental and public health.

Drug Induced Changes in Cell Organelles

1968 ◽  
Vol 26 ◽  
pp. 110-111
Author(s):  
Sarah A. Luse
Keyword(s):  
Clinical Medicine ◽  
Cell Organelles ◽  
Riboflavin Deficiency ◽  
Drug Induced ◽  
New Era ◽  
Health And Disease ◽  
In The Beginning ◽  
Cellular Pathology ◽  
Induced Changes ◽  
The Impact

In the mid-nineteenth century Virchow revolutionized pathology by introduction of the concept of “cellular pathology”. Today, a century later, this term has increasing significance in health and disease. We now are in the beginning of a new era in pathology, one which might well be termed “organelle pathology” or “subcellular pathology”. The impact of lysosomal diseases on clinical medicine exemplifies this role of pathology of organelles in elucidation of disease today.Another aspect of cell organelles of prime importance is their pathologic alteration by drugs, toxins, hormones and malnutrition. The sensitivity of cell organelles to minute alterations in their environment offers an accurate evaluation of the site of action of drugs in the study of both function and toxicity. Examples of mitochondrial lesions include the effect of DDD on the adrenal cortex, riboflavin deficiency on liver cells, elevated blood ammonia on the neuron and some 8-aminoquinolines on myocardium.

The Laryngeal Epithelium in Reflux

2011 ◽  
Vol 21 (3) ◽  
pp. 112-117 ◽  
Author(s):  
Elizabeth Erickson-Levendoski ◽  
Mahalakshmi Sivasankar
Keyword(s):  
Laryngopharyngeal Reflux ◽  
Critical Role ◽  
Structure And Function ◽  
Laryngeal Disease ◽  
Health And Disease ◽  
And Function ◽  
The Impact

The epithelium plays a critical role in the maintenance of laryngeal health. This is evident in that laryngeal disease may result when the integrity of the epithelium is compromised by insults such as laryngopharyngeal reflux. In this article, we will review the structure and function of the laryngeal epithelium and summarize the impact of laryngopharyngeal reflux on the epithelium. Research investigating the ramifications of reflux on the epithelium has improved our understanding of laryngeal disease associated with laryngopharyngeal reflux. It further highlights the need for continued research on the laryngeal epithelium in health and disease.

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