National Public Health Informatics, United States

Yoon, Paula W.; Pollock, Daniel A.; Foldy, Seth

doi:10.1007/978-3-030-41215-9_24

Cited by 4 publications

(4 citation statements)

References 21 publications

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“…20 In addition, nationally, the NNDSS data systems used to transmit notifications from jurisdictions to CDC may have limited interoperability, making data transmission challenging. 21 The unprecedented volume and velocity of COVID-19 cases have strained the limited resources of jurisdictions to investigate individual cases and submit all requested data elements to CDC in a timely manner, particularly when data are not reported to jurisdictions or to CDC in an automated fashion. 7 To improve the completeness and timeliness of case surveillance data and decrease the workload on jurisdictions, CDC and jurisdictional partners are working to increase the use of electronic laboratory reporting and electronic case reporting at public health departments.…”

Section: Discussionmentioning

confidence: 99%

COVID-19 Case Surveillance: Trends in Person-Level Case Data Completeness, United States, April 5–September 30, 2020

et al. 2021

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Objectives To obtain timely and detailed data on COVID-19 cases in the United States, the Centers for Disease Control and Prevention (CDC) uses 2 data sources: (1) aggregate counts for daily situational awareness and (2) person-level data for each case (case surveillance). The objective of this study was to describe the sensitivity of case ascertainment and the completeness of person-level data received by CDC through national COVID-19 case surveillance. Methods We compared case and death counts from case surveillance data with aggregate counts received by CDC during April 5–September 30, 2020. We analyzed case surveillance data to describe geographic and temporal trends in data completeness for selected variables, including demographic characteristics, underlying medical conditions, and outcomes. Results As of November 18, 2020, national COVID-19 case surveillance data received by CDC during April 5–September 30, 2020, included 4 990 629 cases and 141 935 deaths, representing 72.7% of the volume of cases (n = 6 863 251) and 71.8% of the volume of deaths (n = 197 756) in aggregate counts. Nationally, completeness in case surveillance records was highest for age (99.9%) and sex (98.8%). Data on race/ethnicity were complete for 56.9% of cases; completeness varied by region. Data completeness for each underlying medical condition assessed was <25% and generally declined during the study period. About half of case records had complete data on hospitalization and death status. Conclusions Incompleteness in national COVID-19 case surveillance data might limit their usefulness. Streamlining and automating surveillance processes would decrease reporting burdens on jurisdictions and likely improve completeness of national COVID-19 case surveillance data.

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Section: Discussionmentioning

confidence: 99%

COVID-19 Case Surveillance: Trends in Person-Level Case Data Completeness, United States, April 5–September 30, 2020

et al. 2021

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“…Federal PH agencies, such as the U.S. Centers for Disease Control and Prevention (CDC), support state-level efforts and coordinate response across states. 4 During a pandemic, PH and healthcare systems work together to identify and manage disease cases while working to prevent disease spread.…”

Section: Background and Significancementioning

confidence: 99%

Leveraging data visualization and a statewide health information exchange to support COVID-19 surveillance and response: Application of public health informatics

Dixon

Grannis

McAndrews

et al. 2021

Journal of the American Medical Informatics Association

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Objective To support public health surveillance and response to COVID-19 through rapid development and implementation of novel visualization applications for data amalgamated across sectors. Materials and methods We developed and implemented population-level dashboards that collate information on individuals tested for and infected with COVID-19, in partnership with state and local public health agencies as well as health systems. The dashboards are deployed on top of a statewide health information exchange. One dashboard enables authorized users working in public health agencies to surveil populations in detail, and a public version provides higher-level situational awareness to inform ongoing pandemic response efforts in communities. Results Both dashboards have proved useful informatics resources. For example, the private dashboard enabled detection of a local community outbreak associated with a meat packing plant. The public dashboard provides recent trend analysis to track disease spread and community-level hospitalizations. Combined, the tools were utilized 133,637 times by 74,317 distinct users between June 21 and August 22, 2020. The tools are frequently cited by journalists and featured on social media. Discussion Capitalizing on a statewide health information exchange, in partnership with health system and public health leaders, Regenstrief biomedical informatics experts rapidly developed and deployed informatics tools to support surveillance and response to COVID-19. Conclusion The application of public health informatics methods and tools in Indiana holds promise for other states and nations. Yet development of infrastructure and partnerships will require effort and investment after the current pandemic in preparation for the next public health emergency.

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“…For example, methodologies for creating robust national estimates from EHR data have yet to be developed. 20 Furthermore, there is an opportunity to leverage and refine innovations such as artificial intelligence, machine learning, natural language processing, and other methodologies for predictive analytics and the generation of actionable solutions.…”

Section: Resultsmentioning

confidence: 99%

“…4 , 19 With these changes, however, comes a need for new methodologies to manipulate and analyze data in a way that is not only accurate and efficient, but also balances public health's interest in disaggregation of data while minimizing the likelihood of re-identification. 5 , 20 , 21 Methodological approaches to allow for the disaggregation and analysis of data by geography or population characteristics could also have far-reaching implications for advancing health equity.…”

Section: Discussionmentioning

confidence: 99%

The Issues of Interoperability and Data Connectedness for Public Health

et al. 2022

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An unprecedented amount of data is being collected across a diversity of sectors, which, if harnessed, could transform public health decision-making. Yet significant challenges stand in the way of such a vision, including the need to establish standards of data sharing and interoperability, the need for innovation in both methodological approaches and workforce models, and the need for data stewardship and governance models to ensure the protection and integrity of the public health data system. As with other articles in this supplement, this article builds from a literature review, environmental scan, and deliberations from the National Commission to Transform Public Health Data Systems. The article summarizes some of the challenges around data sharing and reuse and identifies where the technology and data sectors can contribute to fill current gaps to promote interoperability and data stewardship.

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National Public Health Informatics, United States

Cited by 4 publications

References 21 publications

COVID-19 Case Surveillance: Trends in Person-Level Case Data Completeness, United States, April 5–September 30, 2020

COVID-19 Case Surveillance: Trends in Person-Level Case Data Completeness, United States, April 5–September 30, 2020

Leveraging data visualization and a statewide health information exchange to support COVID-19 surveillance and response: Application of public health informatics

The Issues of Interoperability and Data Connectedness for Public Health

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