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*If you have questions about the NSSP CoP, its highly collaborative user groups, the NSSP CoP Slack Workspace (a collaboration platform), or syndromic surveillance, please email

Community Highlights

NSSP Community of Practice Monthly Call

This month’s trending topic, “What’s New with ESSENCE,” highlights demonstrations of new features and resources in ESSENCE, reflecting NSSP’s dedication to advancing and modernizing syndromic surveillance. Note: Given the number of demos during this month’s call, we encourage you to view the recording on the NSSP Community of Practice Knowledge Repository.

New Feature: CCSR Categories and ICD-10 Categorization Syndromes in ESSENCE

  • Technical Description: Wayne Loschen (JHUAPL) demonstrated the recently added filters available in ESSENCE2’s emergency department (ED) data query. The four filters include 1) ICD Chapter, 2) ICD Section, 3) ICD Diagnosis, and 4) ICD Clinical Classification Software Refined (CCSR) Category. Currently, the filters are dynamically joined to a reference table. Going forward, the filters will be transitioned to the reference table earlier in the data flow process to improve query performance.
  • New Rnssp-associated Template: Kelley Carey (CDC) gave an overview of the “ED ICD-10 Category Volumes Template” and demonstrated how these new filters can assist with visualizing what occurs across a facility over a specific period. The new filters allow the 70,000+ ICD-10 codes to be queried in groups based on the ICD-10 and CCSR hierarchies. Public health practitioners can visually examine the leading causes of ED visits outside various categories. The template generates heat maps for each filter and allows users to select top conditions by frequency or volume either nationally, regionally, or within their site. Currently, users can stratify by any age group in ESSENCE, and the NSSP team is adding new functionality to stratify by race and gender. To learn more about the template, please visit the Rnssp Package GitHub website:
  • Potential Practical Use: Natasha Close (WA) described how Washington plans to use the newly added categories of data that are being filtered. Close highlighted the potential benefits of using these filters to categorize ED visits and inform decisions on where to allocate resources and understand trends across facilities. Another notable benefit is that the new filters could provide information for conditions that might not have a syndrome definition.

Advancements in Analytics

  • Word Alerts Feature Demo: Wayne Loschen (JHUAPL) demonstrated the “Word Alert” feature (currently in ESSENCE2 under the alert list). Word Alert lets the system separate words from a patient’s chief complaint to highlight important key terms that appear with frequency but are not part of existing syndromes and subsyndromes. Users have the option to select their region of interest, and a word cloud will populate. They can also see which date(s), count(s), and region(s) exhibit these key terms and then view the information in a summary table or detailed table.
  • County Trend Analysis as a Leading Indicator for COVID-19 National Trends: Michael Sheppard (CDC) presented graphs showing county trends, which currently serve as the best measure of burden and trend for COVID-19. Note: Reviewing the graphs in the recording is highly encouraged.
  • Exploring the Future of Asyndromic Methods: Wayne Loschen (JHUAPL) also shared two presentations: 1) Unsupervised Machine Learning Techniques: Novel Threat Discovery, which demonstrates the use of mathematics to create a clustering of words, and 2) Supervised Machine Learning: Refined Syndrome Definition, which demonstrates how mathematics can be used to build syndromes. Note: Reviewing the PowerPoint slides in the recording is highly encouraged.
What is asyndromic surveillance?

Asyndromic surveillance represents an approach to syndromic surveillance that relies on the data itself to define what is new, different, and important. The goal of asyndromic surveillance is to identify unexpected, unforeseen, or emerging issues. This technique complements the long-standing practice of using preestablished categories to determine what is of concern for surveillance purposes.

Use Cases for NSSP Laboratory Data: Stephanie Dietz (CDC) gave an overview of the laboratory data (from Laboratory A) available in NSSP–ESSENCE. She described various data types (i.e., specimen data, patient data, and provider data) and the data use agreement between CDC and Laboratory A. The inclusion of laboratory data complements syndromic surveillance and case-based disease surveillance. These data provide notable benefits such as an awareness of increases in test orders before results are received, a better understanding of test volume, and the ability to integrate with other data sources in ESSENCE to create visualizations and alerts. Dietz also described various use cases for laboratory data that state and local health departments are using. These include opioid surveillance in Arizona, tickborne disease surveillance, HIV testing across specific geographic areas (e.g., Georgia and New York City), and respiratory surveillance in King County, Washington.

NSSP Updates

  • Reprocessing of the Negation of Topics in COVID-like Illness (CLI) Categories: Karl Soetebier (interim NSSP lead) discussed a previous communication that was shared with the community on reprocessing Chief Complaint Discharge Diagnosis (CCDD) categories: ILI syndrome negating coronavirus DD v1 and the CDC EVALI v1 manual limit to ages 11–34. This reprocessing corrected flaws in the two syndrome definitions and has been completed.
  • Logic behind New ESSENCE Field Combining Race and Ethnicity: Jourdan DeVies (CDC contractor) described two recently added categories for calculating race and ethnicity that are available in ESSENCE2: Calculated race and ethnicity combined narrow and Calculated race and ethnicity combined broad. These categories are mutually exclusive and make use of the calculated race and ethnicity fields NSSP introduced earlier this year to facilitate analyses across groups. Please review the recording to learn more about where to find the groups in the query portal.

NSSP CoP Core Committee

  • Krystal Collier (AZ)—Core Committee Chair
  • Yushiuan Chen (Tri-County, CO)—Core Committee Deputy Chair
  • Jade Hodge (KS)—Data Quality Subcommittee Co-Chair
  • Diksha Ramnani (WI)—Data Quality Subcommittee Co-Chair
  • Teresa Hamby (NJ)—Knowledge Repository Curation Subcommittee Chair
  • Bill Smith (Maricopa Co., AZ)—Syndromic Surveillance and Public Health Emergency Preparedness, Response, and Recovery Co-Chair
  • Fatema Mamou (MI)—Syndromic Surveillance and Public Health Emergency Preparedness, Response, and Recovery Co-Chair
  • Rasneet Kumar (Tarrant Co., TX)—Syndrome Definition Subcommittee Co-Chair
  • Rosa Ergas (MA)— Syndrome Definition Subcommittee Co-Chair
  • Natasha Close (WA)—Technical Subcommittee Co-Chair
  • Caleb Wiedeman (TN)—Technical Subcommittee Co-Chair

Data Quality (DQ) Subcommittee

  • The Data Quality Subcommittee has a new co-chair: Jade Hodge (KS). The subcommittee is seeking another chair to work alongside Jade. Please email for details.
  • The October 2021 DQ Subcommittee call featured a preview of sessions on data quality that will be held during the upcoming 2021 Syndrome Surveillance Symposium. Presenters shared details about their presentations. Krystal Collier (AZ) shared a timeline for the one-pager project and led a group activity to collect feedback and information from call attendees to further assist with completing the one-pagers.
  • Link to previous call recordings and other resources from the DQ Subcommittee here.

Knowledge Repository (KR) Curation Subcommittee

  • Do you have syndromes, resources, or anything else related to syndromic surveillance to add to the KR? If so, please email
  • Email if you have issues with the KR.

Syndrome Definition (SD) Subcommittee

  • The Syndrome Definition Subcommittee’s October call included an NSSP update on developing and disseminating a document to encourage participation and increase transparency about efforts to develop syndrome definitions. The document will allow partners to volunteer to test and upvote syndromes. Noreen Ajayi (NCIRD/CDC) joined the call to discuss influenza-like illness and respiratory syndrome development and updates. Nimi Idaikkadar (NCIPC/CDC) discussed the traumatic brain injury syndrome and solicited feedback from attendees. Lastly, Rosa Ergas (MA) discussed the OD2A Dose Technical Committee.
  • Check out previous call recordings and other resources from the SD Subcommittee here.

Syndromic Surveillance and Public Health Emergency Preparedness, Response, and Recovery (SPHERR) Subcommittee

  • During the October 2021 SPHERR call, Gill Capper (MI) presented on syndromic surveillance’s role in assisting Michigan’s climate and health emergency response. Amanda Swanson (AZ) shared a dashboard on drowning and invited attendees to provide feedback.
  • Check out previous call recordings and other resources from the SPHERR Subcommittee

Technical Subcommittee

  • Check out previous call recordings and other resources from the Technical Subcommittee here.

If you have questions about the NSSP CoP, its highly collaborative user groups, the NSSP CoP Slack Workspace (a collaboration platform), or syndromic surveillance, please email icon

cms interoperability graphic

A new CMS rule will benefit public health jurisdictions that participate in NSSP or use a local syndromic surveillance system by requiring facilities to submit syndromic data.

The Centers for Medicare & Medicaid Services (CMS) is promoting sustainability and readiness so that public health agencies are better prepared to respond to emerging health threats. On August 2, 2021, CMS published the final rule for changes to the Medicare Promoting Interoperability Program. The rule revised the requirements for eligible hospitals and critical access hospitals (CAHs) participating in the Medicare Promoting Interoperability Program. These hospitals are now required to have four of the measures associated with the Public Health and Clinical Data Exchange Objective: Syndromic Surveillance Reporting, Immunization Registry Reporting, Electronic Case Reporting, and Electronic Reportable Laboratory Result Reporting. Currently, these measures are optional. Under this change, an eligible hospital or CAH will receive 10 points for the Public Health and Clinical Data Exchange objective if they report a ‘‘yes’’ response for all four measures. The rule will take effect beginning with the reporting period in calendar year 2022.

The final rule requires hospitals with emergency departments (EDs) to attest that they are actively engaged with a public health agency to submit data for measures related to nationwide surveillance for early warning of emerging outbreaks and threats. Hospital submission of syndromic data supports public health agencies as they prepare to respond to both future health threats and long-term COVID-19 recovery.

Public health jurisdictions can declare readiness if they are able to receive messages in a locally administered syndromic surveillance system or if they direct submitters to send messages directly to the NSSP BioSense Platform, which makes data available to the jurisdictions’ authorized users. The NSSP onboarding team will help sites coordinate with the facilities to set up data feeds and begin transmission.

QUICK TIP: Does your website explain the new CMS ruling and how it can benefit public health? Now is a good time to make sure your website links to CMS “Promoting Interoperability Programs.”external icon

CDC Data Modernization Implementation Support: Improving Surveillance Systems New
CDC Resources: Public Health Data Interoperability
FY2022 IPPS/LTCH PPS Final Rule fact sheet
FY2022 IPPS/LTCH PPS Final Rule on the Federal Register

This article includes excerpts from a press release dated August 2, 2021.

CDC's Date Modernization Initiative to Advance Syndromic Surveillance

“Modernization” of our public health data and surveillance systems is one way in which CDC invests in the future of public health.

The CDC Public Health Data Modernization Initiative lays out a path to move us toward integrated systems that provide data more efficiently for public health action. This framework guides decisions for allocating resources to create interoperable systems (federal, state, local, and healthcare), coordinate investments across CDC (and with partners), develop next-generation tools (e.g., modeling, visualization, machine learning), and strengthen predictive analytics and forecasting. One objective of DMI is for syndromic surveillance to give a faster understanding of emerging health threats through electronic reporting of emergency department visits.

“This is a moment in time when our national leaders will seek to identify or build platforms to detect and monitor future health threats,” NSSP Lead Loren Rodgers said during a 2021 NSSP Community of Practice call. “I’d like to challenge the NSSP community to consider our place in a new public health infrastructure. I don’t know of another program that is so purpose-built for this task with the ability to scale to include new data sources and analytics and to share these data with allied [public health] jurisdictions and trusted partners. Our syndromic community exemplifies innovative approaches that other surveillance systems aim to implement.”

CDC’s earlier modernization efforts laid the groundwork that supports NSSP’s current approach to surveillance and—bolstered by CDC’s Data Modernization Initiative—positions the program to better protect our country from all types of public health threats.