Marcellus Shale Development, Air Pollution, and Asthma Exacerbations

Unconventional natural gas development (UNGD), the extraction of natural gas from shale, has rapidly grown in Pennsylvania since 2005. Shale gas extraction is a major industrial undertaking with the potential to affect air, water, and soil. Much of the concern over UNGD has centered on water, but air pollution may be of greater concern. There has been little research on the health concerns of the potential air impacts of UNGD. We are engaged in a study to evaluate associations between UNGD and asthma exacerbations. We began by creating a complete database of wells. Starting with data on well location; dates of drilling, perforation, and stimulation; well depth, and production from the Pennsylvania Department of Environmental Protection (DEP), we filled in missing data using the Pennsylvania Internet Record Im aging System/Wells Information System, and then imputed values that were still missing. Our final population includes 6,915 drilled wells by June 2013. Using remote sensing and crowdsourcing technologies, we collected the dates of well flaring and locations of ponds associated with UNGD. Information on compressor stations, which data suggest are an important source of UNGD-related air emissions, is not currently electronically available. We started with a list of compressor stations related to UNGD from DEP (nP6) and made a total of 17 visits to 4 DEP offices, scanning 6,007 documents. These documents were data abstracted into an electronic database. The source of our health data is the Geisinger Health System, which has used electronic health records (EHR) since 2001. These records include information on diagnoses, vital signs, medications, procedures, laboratory tests, tobacco use, and sociodemographics. Using EHR data, we identified 38,646 asthma patients in Pennsylvania and New York. Between 2005 and 2013, we identified the following asthma exacerbations: 446 primary asthma hospitalizations, 4,833 primary or secondary asthma hospitalizations, 1,896 asthma emergency department visits, and 30,516 new oral corticosteroid medication orders. We are assigning patients exposure estimates based on the different phases of UNGD, ponds, and compressor stations. We are using a nested case-control study design to evaluate associations between exposure to UNGD and asthma exacerbations in this cohort of patients

Using electronic health records to enhance surveillance of diabetes in children, adolescents and young adults: a study protocol for the DiCAYA Network

Introduction Traditional survey-based surveillance is costly, limited in its ability to distinguish diabetes types and time-consuming, resulting in reporting delays. The Diabetes in Children, Adolescents and Young Adults (DiCAYA) Network seeks to advance diabetes surveillance efforts in youth and young adults through the use of large-volume electronic health record (EHR) data. The network has two primary aims, namely: (1) to refine and validate EHR-based computable phenotype algorithms for accurate identification of type 1 and type 2 diabetes among youth and young adults and (2) to estimate the incidence and prevalence of type 1 and type 2 diabetes among youth and young adults and trends therein. The network aims to augment diabetes surveillance capacity in the USA and assess performance of EHR-based surveillance. This paper describes the DiCAYA Network and how these aims will be achieved.Methods and analysis The DiCAYA Network is spread across eight geographically diverse US-based centres and a coordinating centre. Three centres conduct diabetes surveillance in youth aged 0–17 years only (component A), three centres conduct surveillance in young adults aged 18–44 years only (component B) and two centres conduct surveillance in components A and B. The network will assess the validity of computable phenotype definitions to determine diabetes status and type based on sensitivity, specificity, positive predictive value and negative predictive value of the phenotypes against the gold standard of manually abstracted medical charts. Prevalence and incidence rates will be presented as unadjusted estimates and as race/ethnicity, sex and age-adjusted estimates using Poisson regression.Ethics and dissemination The DiCAYA Network is well positioned to advance diabetes surveillance methods. The network will disseminate EHR-based surveillance methodology that can be broadly adopted and will report diabetes prevalence and incidence for key demographic subgroups of youth and young adults in a large set of regions across the USA