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Public Health Surveillance in Electronic Health Records: Lessons From PCORnet

Supporting Files Public Domain
File Language:
English


Details

  • Journal Article:
    Preventing Chronic Disease (PCD)
  • Personal Author:
  • Description:
    Introduction

    PCORnet, the National Patient-Centered Clinical Research Network, is a large research network of health systems that map clinical data to a standardized data model. In 2018, we expanded existing infrastructure to facilitate use for public health surveillance. We describe benefits and challenges of using PCORnet for surveillance and describe case studies.

    Methods

    In 2018, infrastructure enhancements included addition of a table to store patients’ residential zip codes and expansion of a modular program to generate population health statistics across conditions. Chronic disease surveillance case studies conducted in 2019 assessed atrial fibrillation (AF) and cirrhosis. In April 2020, PCORnet established an infrastructure to support COVID-19 surveillance with institutions frequently updating their electronic health record data.

    Results

    By August 2023, 53 PCORnet sites (84%) had a 5-digit zip code available on at least 95% of their patient populations. Among 148,223 newly diagnosed AF patients eligible for oral anticoagulant (OAC) therapy, 43.3% were on any OAC (17.8% warfarin, 28.5% any novel oral anticoagulant) within a year of the AF diagnosis. Among 60,268 patients with cirrhosis (2015–2019), common documented etiologies included unknown (48%), hepatitis C infection (23%), and alcohol use (22%). During October 2022 through December 2023, across 34 institutions, the proportion of COVID-19 patients who were cared for in the inpatient setting was 9.1% among 887,051 adults aged 20 years or older and 6.0% among 139,148 children younger than 20 years.

    Conclusions

    PCORnet provides important data that may augment traditional public health surveillance programs across diverse conditions. PCORnet affords longitudinal population health assessments among large catchments of the population with clinical, treatment, and geographic information, with capabilities to deliver rapid information needed during public health emergencies.

  • Subjects:
  • Source:
    Prev Chronic Dis. 2024; 21
  • DOI:
  • ISSN:
    1545-1151
  • Pubmed ID:
    38991533
  • Pubmed Central ID:
    PMC11262136
  • Document Type:
  • Volume:
    21
  • Collection(s):
  • Main Document Checksum:
    urn:sha-512:47508c3c5c1523e20d48fd0bb8932832110f49ad8a4ef4f069c96f7cd872412a248af22b2186545d2f0d7aa3bda383493fc8d647bc5b5e2689e61c70bcae6ce0
  • Download URL:
  • File Type:
    Filetype[PDF - 463.72 KB ]
File Language:
English
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