FHIR PIT: a geospatial and spatiotemporal data integration pipeline to support subject-level clinical research.

IF 3.3 3区 医学 Q2 MEDICAL INFORMATICS
Karamarie Fecho, Juan J Garcia, Hong Yi, Griffin Roupe, Ashok Krishnamurthy
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引用次数: 0

Abstract

Background: Environmental exposures such as airborne pollutant exposures and socio-economic indicators are increasingly recognized as important to consider when conducting clinical research using electronic health record (EHR) data or other sources of clinical data such as survey data. While numerous public sources of geospatial and spatiotemporal data are available to support such research, the data are challenging to work with due to inconsistencies in file formats and spatiotemporal resolutions, computational challenges with large file sizes, and a lack of tools for patient- or subject-level data integration.

Results: We developed FHIR PIT (HL7® Fast Healthcare Interoperability Resources Patient data Integration Tool) as an open-source, modular, data-integration software pipeline that consumes EHR data in FHIR® format and integrates the data at the level of the patient or subject with environmental exposures data of varying spatiotemporal resolutions and file formats. We applied FHIR PIT to generate "integrated feature tables" containing patient- or subject-level EHR data integrated with environmental exposures data on two cohorts: one on patients with asthma and related common pulmonary disorders; and a second on patients with primary ciliary dyskinesia and related rare pulmonary disorders. The data were then exposed via the open Integrated Clinical and Environmental Exposures Service, which was then queried to explore relationships between exposures to two representative airborne pollutants (particulate matter and ozone) and annual emergency department or inpatient visits for respiratory issues. We found that hospitalizations for respiratory issues were more common among patients exposed to relatively high levels of particulate matter and ozone and were higher overall among patients with primary ciliary dyskinesia than among patients with asthma.

Conclusions: Our manuscript describes a major release of FHIR PIT v1.0 and includes a technical demonstration use case and a clinical application on the use of FHIR PIT to support research on environmental exposures and health outcomes related to asthma and primary ciliary dyskinesia. For application of the tool to common data models (CDMs) other than FHIR, we offer open-source conversion tools to map from the PCORnet, i2b2, and OMOP CDMs to FHIR.

FHIR PIT:一个支持学科级临床研究的地理空间和时空数据集成管道。
背景:人们日益认识到,在使用电子健康记录(EHR)数据或其他临床数据来源(如调查数据)进行临床研究时,空气污染物暴露等环境暴露和社会经济指标是需要考虑的重要因素。虽然有许多地理空间和时空数据的公共来源可用于支持此类研究,但由于文件格式和时空分辨率的不一致、大文件大小的计算挑战以及缺乏用于患者或主题级数据集成的工具,这些数据的处理具有挑战性。结果:我们开发了FHIR PIT (HL7®快速医疗互操作性资源患者数据集成工具)作为一个开源的、模块化的数据集成软件管道,它使用FHIR®格式的EHR数据,并将患者或受试者级别的数据与不同时空分辨率和文件格式的环境暴露数据集成在一起。我们应用FHIR PIT生成“综合特征表”,其中包含两个队列的患者或受试者水平的电子病历数据,以及环境暴露数据:一个队列是哮喘和相关常见肺部疾病患者;第二项是针对原发性纤毛运动障碍和相关罕见肺部疾病的患者。然后通过开放的综合临床和环境暴露服务公布这些数据,然后对该服务进行查询,以探索暴露于两种代表性空气污染物(颗粒物和臭氧)与每年急诊或因呼吸问题住院之间的关系。我们发现,呼吸问题住院治疗在暴露于相对高水平颗粒物和臭氧的患者中更为常见,并且原发性纤毛运动障碍患者的总体发生率高于哮喘患者。结论:我们的手稿描述了FHIR PIT v1.0的主要版本,包括一个技术演示用例和FHIR PIT的临床应用,以支持与哮喘和原发性纤毛运动障碍相关的环境暴露和健康结果的研究。为了将该工具应用于除FHIR之外的公共数据模型(cdm),我们提供了从PCORnet、i2b2和OMOP cdm到FHIR的开源转换工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.20
自引率
5.70%
发文量
297
审稿时长
1 months
期刊介绍: BMC Medical Informatics and Decision Making is an open access journal publishing original peer-reviewed research articles in relation to the design, development, implementation, use, and evaluation of health information technologies and decision-making for human health.
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