Dataset Information

A novel approach for exposing and sharing clinical data: the Translator Integrated Clinical and Environmental Exposures Service.

ABSTRACT:

Objective

This study aimed to develop a novel, regulatory-compliant approach for openly exposing integrated clinical and environmental exposures data: the Integrated Clinical and Environmental Exposures Service (ICEES).

Materials and methods

The driving clinical use case for research and development of ICEES was asthma, which is a common disease influenced by hundreds of genes and a plethora of environmental exposures, including exposures to airborne pollutants. We developed a pipeline for integrating clinical data on patients with asthma-like conditions with data on environmental exposures derived from multiple public data sources. The data were integrated at the patient and visit level and used to create de-identified, binned, "integrated feature tables," which were then placed behind an OpenAPI.

Results

Our preliminary evaluation results demonstrate a relationship between exposure to high levels of particulate matter ≤2.5 µm in diameter (PM2.5) and the frequency of emergency department or inpatient visits for respiratory issues. For example, 16.73% of patients with average daily exposure to PM2.5 >9.62 µg/m3 experienced 2 or more emergency department or inpatient visits for respiratory issues in year 2010 compared with 7.93% of patients with lower exposures (n = 23 093).

Discussion

The results validated our overall approach for openly exposing and sharing integrated clinical and environmental exposures data. We plan to iteratively refine and expand ICEES by including additional years of data, feature variables, and disease cohorts.

Conclusions

We believe that ICEES will serve as a regulatory-compliant model and approach for promoting open access to and sharing of integrated clinical and environmental exposures data.

SUBMITTER: Fecho K

PROVIDER: S-EPMC6748811 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A novel approach for exposing and sharing clinical data: the Translator Integrated Clinical and Environmental Exposures Service.

Fecho Karamarie K Pfaff Emily E Xu Hao H Champion James J Cox Steve S Stillwell Lisa L Peden David B DB Bizon Chris C Krishnamurthy Ashok A Tropsha Alexander A Ahalt Stanley C SC

Journal of the American Medical Informatics Association : JAMIA 20191001 10

<h4>Objective</h4>This study aimed to develop a novel, regulatory-compliant approach for openly exposing integrated clinical and environmental exposures data: the Integrated Clinical and Environmental Exposures Service (ICEES).<h4>Materials and methods</h4>The driving clinical use case for research and development of ICEES was asthma, which is a common disease influenced by hundreds of genes and a plethora of environmental exposures, including exposures to airborne pollutants. We developed a pip ...[more]

PMID: 31077269

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Project description:BackgroundSharing patient data can help drive scientific advances and improve patient care, but service users are concerned about how their data are used. When the National Health Service proposes to scrape general practitioner records, it is very important that we understand these concerns in some depth.ObjectiveThis study aims to investigate views of mental health service users on acceptable data sharing to provide clear recommendations for future data sharing systems.MethodsA total of 4 focus groups with 4 member-checking groups were conducted via the internet between October 2020 and March 2021, with a total of 22 service users in the United Kingdom. Thematic analysis was used to identify the themes.ResultsSix main themes, with several subthemes were identified, such as the purpose of data sharing-for profit, public good, and continuation of care; discrimination through the misattribution of physical symptoms to mental health conditions (ie, diagnostic overshadowing) alongside the discrimination of individuals or groups within society (ie, institutional discrimination); safeguarding data by preserving anonymity and confidentiality, strengthening security measures, and holding organizations accountable; data accuracy and informed consent-increasing transparency about data use and choice; and incorporating service user involvement in system governance to provide insight and increase security.ConclusionsThis study extends the limited research on the views and concerns of mental health service users regarding acceptable data sharing. If adopted, the recommendations should improve the confidence of service users in sharing their data. The five recommendations include screening to ensure that data sharing benefits the public, providing service users with information about how their data are shared and what for, highlighting the existing safeguarding procedures, incorporating service user involvement, and developing tailored training for health care professionals to address issues of diagnostic overshadowing and inaccurate health records. Adopting such systems would aid in data sharing for legitimate interests that will benefit patients and the National Health Service.

Project description:BACKGROUND:Sharing research data uses resources effectively; enables large, diverse data sets; and supports rigor and reproducibility. However, sharing such data increases privacy risks for participants who may be re-identified by linking study data to outside data sets. These risks have been investigated for genetic and medical records but rarely for environmental data. OBJECTIVES:We evaluated how data in environmental health (EH) studies may be vulnerable to linkage and we investigated, in a case study, whether environmental measurements could contribute to inferring latent categories (e.g., geographic location), which increases privacy risks. METHODS:We identified 12 prominent EH studies, reviewed the data types collected, and evaluated the availability of outside data sets that overlap with study data. With data from the Household Exposure Study in California and Massachusetts and the Green Housing Study in Boston, Massachusetts, and Cincinnati, Ohio, we used k-means clustering and principal component analysis to investigate whether participants' region of residence could be inferred from measurements of chemicals in household air and dust. RESULTS:All 12 studies included at least two of five data types that overlap with outside data sets: geographic location (9 studies), medical data (9 studies), occupation (10 studies), housing characteristics (10 studies), and genetic data (7 studies). In our cluster analysis, participants' region of residence could be inferred with 80%-98% accuracy using environmental measurements with original laboratory reporting limits. DISCUSSION:EH studies frequently include data that are vulnerable to linkage with voter lists, tax and real estate data, professional licensing lists, and ancestry websites, and exposure measurements may be used to identify subgroup membership, increasing likelihood of linkage. Thus, unsupervised sharing of EH research data potentially raises substantial privacy risks. Empirical research can help characterize risks and evaluate technical solutions. Our findings reinforce the need for legal and policy protections to shield participants from potential harms of re-identification from data sharing. https://doi.org/10.1289/EHP4817.

Dataset Information

A novel approach for exposing and sharing clinical data: the Translator Integrated Clinical and Environmental Exposures Service.

Objective

Materials and methods

Results

Discussion

Conclusions

Publications

A novel approach for exposing and sharing clinical data: the Translator Integrated Clinical and Environmental Exposures Service.

Similar Datasets

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