Community of Practice Updates

Updated April 5, 2023

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Policy for Federal Access to NSSP Data

During the November 2022 CoP Monthly meeting, Acting NSSP Lead Karl Soetebier informed the community of efforts to make NSSP data more accessible and to improve collaboration toward common goals.

In early December 2022, Soetebier updated site administrators of NSSP’s ongoing work related to data use. He explained how expanded access to NSSP data during the COVID-19 public health emergency enabled innovation in areas such as trend indicators and classification, anomaly detection, and text mining by age and geography. The ability to work this way routinely, outside the context of a public health emergency, is not permitted by the current data use agreement.

In early 2023, to build on public health response innovations and to continue to enhance data use, CDC has been working on designing a new NSSP agreement that will incorporate lessons learned from the COVID-19 response. The new agreement will enable close collaboration between sites and CDC. The agreement will also enable new innovations and services for sites, maximize responsible use of data and provide timelier synthesis of findings and recommendations, and help respond to the top concerns raised by public health departments in the Federal Access to National Syndromic Surveillance Program Data: Review and Implementation Strategies.

After gathering valuable input, CDC has carefully decided to change from a data use agreement (DUA) to a memorandum of understanding (MOU) with sites to better reflect the collaborative nature of the agreement. By refocusing the DUA as an MOU, the collaborative and participatory goals of the partnership across federal, state, and local public health authorities become more transparent.

To inform community members throughout this process, we will make a new Policy for Federal Access to NSSP Data web page available in spring 2023. It will contain information on the development and long-term benefits we hope to achieve, so stay tuned!

Just released! Review of Federal Access Policies for NSSP Data

Federal Access to National Syndromic Surveillance Program Data: Review and Implementation Strategies.

In February 2023, The Council of State and Territorial Epidemiologists (CSTE) posted the Federal Access to National Syndromic Surveillance Program Data: Review and Implementation Strategies.

CSTE collaborated with CDC and Texas A&M University School of Public Health to develop this report. They brought together epidemiologists in leadership positions or with decision-making power who represented state, tribal, local or territorial (STLT) public health departments to identify considerations and implementation strategies for permitting federal access to NSSP data.​

For additional context and details about the process and findings, listen to author/contractor Cason Schmit’s presentation for the October 2022 NSSP CoP monthly call. Please direct questions about the report to

NSSP CoP Monthly Meeting

The National Syndromic Surveillance Program (NSSP) Community of Practice (CoP) met on February 22, 2023. On average, 100 to 120 people participate in these monthly meetings. Recordings for CoP monthly calls are posted in the Knowledge Repository.

NSSP Update

Karl Soetebier, acting NSSP lead, thanked CSTE for publishing the report on federal access to NSSP data. The report provides a public look at the considerations NSSP is giving to a new agreement. Karl then launched into program updates:

  • Laboratory data: Provider specialty has been added to table builder. Specimen type is now a text field that can be queried. NSSP continues to clean up culture testing and specimen type as well.
  • Chief complaint and discharge diagnoses categories: NSSP has not added new categories since December 2022, but many categories show updated dates. This is due to the addition of fact sheets, links, and edits in ESSENCE.
  • Newly posted to the Knowledge Repository: The full fact sheet and technical brief for CDC Chickenpox v2 and preliminary fact sheet and technical brief for CDC Broad Acute Respiratory DD v1.
  • A chat has been set up on Slack to collect queries, tools, and tips related to surveillance for acute environmental or chemical exposures. Several such exposures have occurred in recent weeks, and this chat is a place where public health jurisdictions that have experience working on similar environmental exposures can come together to share their successes and challenges with colleagues who are currently responding to these events. You can find this chat at the following Slack channel: #environmental-health-and-severe-weather.
  • NSSP is pleased to announce that v0.2.0 of Rnssp has been released (information about what’s new can be found in Technical Updates and at GitHub). To learn more, consider joining the NSSP R User Group call and the new Analytic Tools for Health Surveillance Subcommittee call.
  • The Selected Causes of Death Lists, created by the National Center for Health Statistics (NCHS) and vetted through the World Health Organization, are in the process of being added to the mortality data source in NSSP. NCHS created the lists to provide consistent grouping and ranking standards. NSSP is adding these lists to the Mortality Data Source to help identify deaths quickly. The three lists include Comprehensive Cause of Death, Concise Cause of Death (less granularity), and Infant Deaths. Once NSSP tests its queries against these data, the lists will be moved into production and details will be provided to the community.

Community Highlights

First Meeting of the Analytic Tools for Routine Health Surveillance Subcommittee

Co-chairs: Michael Sheppard (CDC), Diksha Ramnani (Monterey Co., CA), Caleb Wiedeman (TN), Kacey Potis (WA), and Howard Burkom (JHU APL)

The CoP featured the subcommittee’s first meeting, held February 9, 2023. Howard Burkom introduced the topic by stating that the expectation was for a dozen people to attend. But surprisingly, about four times that many people joined. He said the format for upcoming meetings would be practically oriented. A health department (the “problem owner”) would describe an issue, describe the public health relevance, and explain how the problem has been handled previously. This would be followed by open discussion. Members or co-chairs could suggest related methods and propose possible improvements.

Upcoming topics include: Calculating/Displaying Population Rates and Other Ratios/Percentages, Sparse Data Alerting Methods, Multiyear Regression Models, and Spatiotemporal Cluster Detection.

To join this subcommittee, simply update your profile. A new Slack channel has been created for this subcommittee: #analytic-tools.

If you have questions about the NSSP CoP, its highly collaborative user groups, the NSSP CoP Slack workspace, or syndromic surveillance, please email

JHU APL: Johns Hopkins University Applied Physics Laboratory

Comparing Overdose ED Data Systems in Michigan: Surprises Abound!

This presentation is an excellent example of how a public health jurisdiction can examine data acquired from different data systems; contrast the strengths, weaknesses, and results of each; and identify data quality improvements. As anyone who works with syndromic data can attest, syndromic data are not always complete and need context and interpretation. What better way to understand your data than by examining it periodically from different perspectives and digging into outliers and anomalies? The results from this analysis have already presented opportunities to collaborate with others to make changes and have informed long-term surveillance goals.


Presenter Gabrielle Stroh-Steiner is the lead epidemiologist for the Overdose Data to Action (OD2A) Program in Michigan. She has worked with the program and with syndromic surveillance for about 5 years. In this presentation, she discusses an analysis in which her public health jurisdiction compares three emergency department (ED) data systems used for overdose surveillance and then shares the lessons learned. The reason for initiating this analysis is that Michigan uses each data source for different purposes in overdose surveillance and wanted to make sure data from the different systems aligned and were being reported accurately. Although this analysis was conducted in early 2022, the results and implications hold true today.

Overview of Michigan Data Sources

Michigan uses three ED data sources for overdose surveillance:

  • Michigan Health and Hospital Association (MHA)—Data are comprehensive, high quality, slower (6- to 9-month lag and not useful as an alerting mechanism), and missing one key hospital.
  • Michigan Syndromic Surveillance System (MSSS)—Data are timely and well understood. Coverage is slightly lower. MSSS onboards each facility.
  • MiCelerity, a Michigan-designed system implemented in 2020—Data are timely, identifiable, flexible, and owned by the unit. Since the data source is new, the unit is still learning about its limitations.

MHA data are billing and discharge data collected and purchased quarterly. MHA does all data cleaning and maintenance.

MSSS and MiCelerity are both ADT-based systems. Despite system similarities, a key difference is that MSSS collects data from all state ED visits, whereas MiCelerity only collects substance use-related data. MiCelerity receives data from the health information exchange (HIE); consequently, if an ADT message contains an ICD-10 CM code related to overdose, it will trigger the go-between HIE to send data to the system. MSSS functions a little differently in its collection of ADT data from electronic health records.


The analysis compared the most recent year of data available for the three systems: July 2020–June 2021. They looked at 86 facilities that reported to all three data systems. They calculated the frequency of (1) all drug overdose (T36-T50), (2) Opioid overdose (T40.0-T40.4, T40.6), and (3) Unspecified drug overdose (T50.9). Then they compared frequency by time, facility, geography, and demographic groups. They used line graphs, scatter plots, and correlation coefficients.

Anticipated Results…

Going into the analyses, the epidemiologists proposed several hypotheses: They anticipated seeing similar all-drug overdose counts over time across all three data sources. They anticipated lower counts of opioid overdoses in MSSS and MiCelerity than in MHA but comparable counts between MSSS and MiCelerity. In general, they anticipated comparable findings between MSSS and MiCelerity. They also anticipated similar patterns across facilities and counties.

Surprise! The Actual Results…

They looked at number of drug overdose by week in each of the data sources and found the first unexpected finding. Over time, the patterns were similar. MiCelerity and MHA data were similar in magnitude of drug overdose ED visits, whereas the syndromic system, MSSS, had on average about 24% fewer drug overdose ED visits.

They looked at opioid overdoses by week to get a glimpse at how drug-specific overdoses look over time. As expected, MiCelerity and the syndromic system, MSSS, had fewer opioid overdoses on average than MHA. Looking at the correlation across data sources, there was a strong positive correlation across all three.

When they looked at the percent of total drug overdoses unspecified over time in each of the three data sources, a significant number of overdoses in MiCelerity and MSSS were unspecified. MHA had the highest percentage of specified overdoses.

Scatter plots of the overdose counts by facility revealed interesting takeaways. In general, larger facilities with more overdoses in one system showed more in the other system—but they observed more variation than anticipated. Also, some facilities were significant outliers. Initially, the team expected the outliers to be mostly under-reporters in the ADT-based systems (MiCelerity, MSSS) compared with MHA, but that wasn’t always true. They also looked at the correlation between data source by facility, including and excluding outliers. Once the outliers were removed, the correlation improved substantially.

Blockquotes It can be a challenge

They looked at drug overdose rate by county, observing more variability than hoped for at the county level. They also looked at drug overdose rate by demographic groups, seeing similar distribution by demographic groups within the three systems. A major difference, however, was by sex in the MHA and syndromic system (MSSS), which might be attributed to reporting by outlier facilities.

  • Trends in drug overdoses (increases/decreases) were well correlated across all three ED data sources. MSSS consistently had on average 20% to 30% fewer drug overdoses than MiCelerity and MHA.
  • Despite using ADT messages, MSSS and MiCelerity were the least correlated by time, facility, and county,
  • MSSS and MiCelerity under-reported opioid overdoses and have higher proportions of unspecified drug overdoses than billing data (MHA).
  • Some facilities in MSSS and MiCelerity under-report, whereas others over-report compared to MHA. There are inconsistencies.
  • Facilities identified as outliers represent targets for improvement efforts to better align reporting.

These conclusions have launched discussion on over- and under-reporting and investigation into whether facility updates and final diagnoses are being received. Can a broader approach be taken to improve data standards? Efforts are already underway to better understand problematic facilities and integration of their data.

Understanding data is one step. But an even bigger challenge is identifying the right people needed to change the current system. “It can be a challenge identifying the right people to talk to at a healthcare system,” Gabrielle said, “and then getting them to dedicate time to look into the issues and want to drill down into individual-level data.” Some steps her team is taking includes working with their HIE, a health information technology advisor, and legal advisors to take a broader approach to improving data. They want to impress upon everyone that accurate data are critical, especially since overdoses are legally reportable to health departments in Michigan. They are also looking at ingestion of other reliable data sources into MiCelerity—including death certificate and EMS data—to provide a more comprehensive picture of the overdose crisis.

At the conclusion of Gabrielle’s presentation, she and Fatima Mamou (MI) fielded questions about onboarding, data collection and reporting, and absence of urgent care data in this analysis. Fatima added details about improvements being made to facility reporting—for example, encouraging facilities to send diagnosis codes after a patient’s visit has been transferred from emergency department to inpatient.

Attendees expressed considerable interest in having three data sources to compare and the nuanced perspective. Where do messages go wrong? What isn’t being sent? What next steps should be tackled? The ensuing discussion acknowledged differences experienced across states, from over-reporting and improving data to the use of syndromic data (in part) for reportable disease.

For more ways to improve data quality, check out this and other monthly calls in the Knowledge Repository. By sharing these findings with other Community members, the NSSP CoP is strengthening its collaborative knowledge base and building the workforce of tomorrow.

Hot Topics/Open Forum

Anna Frick (AK) kicked off the discussion by asking attendees to contribute more STLT talks—short or long—and to bring thorny issues or questions to the Community. She suggested that if anyone has a partially done project, try tapping the NSSP CoP’s collective mind to make progress.

Several topics were raised:

  • Jade Hodge (KS) asked about state hospital association data and experiences with data quality processes and clearinghouses.
  • Dave Atrubin (FL) noted that the lines are blurring for reporting and that syndromic data, in part, are starting to be used for reportable disease. This new ground needs more consideration. The Michigan presentation is an excellent way to engage others in this discussion.
  • Doug Cretsinger (IA) asked about effective engagement practices for the Community. The Community suggested numerous ways in which this can be achieved, a few of which are shown in Tips for Engaging Staff in SyS.

Tips for Engaging Staff in SyS

join cop woman holding sign

Each of us juggles competing priorities. These tips will help you and your team evolve syndromic surveillance (SyS) and promote the use and integration of emergency department data across your organization.

  • Join the NSSP Community of Practice (CoP). Attend monthly NSSP CoP meetings. By far, this is the best way to connect with your colleagues and learn different approaches to solving common problems. Find ways to introduce these topics into local meetings.
  • Join a subcommittee.
  • Open a Slack account—and use it! Slack gives insight into hot topics and is a resource for consulting others and getting feedback fast.
  • Engage your communications staff. They can publicize your syndromic successes.
  • Check out symposium topics in the Knowledge Repository.
  • Integrate syndromic findings into routine meetings.
  • Set up ESSENCE office hours once a month to encourage exploration, new tools and practice, auto-reporting, etc., and discuss chat topics.
  • Identify grants where syndromic data could be part of the solution. Some response efforts lead to grants.
  • Collaborate by design and intent. Start building relationships across program areas. It takes time to engage others and grow knowledge and interest in syndromic data. Send periodic updates about what you’re doing (include data others don’t realize they need). Brainstorm project ideas, explore data gaps, and look for collaboration opportunities. Consider setting up an internal workgroup that meets regularly.
  • Invite others to CoP NSSP meetings when the topic is in their purview.
  • Identify internal champions and help them pursue agency engagement.

Reminders and Announcements

  •  Join the Community and a subcommittee! Our Community is a great way to meet others working in syndromic surveillance and advance the work of syndromic surveillance at all jurisdictional levels. Become part of the Community or update your NSSP CoP membership to join a subcommittee here. Encourage others to join, too!
    • Join and participate in the Slack workspace. This space is full of rich discussion among colleagues. This is a great opportunity to collaborate with your peers outside of CoP meetings.
    • Submit success stories to be featured in NSSP Update and on the NSSP CoP website. You do great work every day that we want to highlight.
    • Submit a topic for future NSSP CoP monthly calls. These calls are meant for the community, and we want to know what is most important to you.
  •  CSTE Annual Conference 2023: Meet, build relationships, and network with colleagues and experts in areas including informatics, infectious diseases, substance use, chronic disease, and injury control. Join more than 2,500 public health epidemiologists from across the nation in workshops, plenary sessions, oral breakout sessions, roundtable discussions, and poster presentations. The plan is to hold conference sessions in person; however, CSTE will monitor circumstances and public health recommendations of group gatherings.
    • June 25–29, 2023 in Salt Lake City, Utah
    • Registration is now open! An early bird discount is offered for registrations completed by 11:59 PM ET on Thursday, May 4, 2023. To register and learn more, visit the conference site.
Join the NSSP CoP Slack Workspace
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So what are your colleagues discussing?

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Find and Join Channels

  1. Hover cursor over “Channels” on left side of Slack space.
  2. Click the three dots icon that appears next to “Channels” titled “Section Options.”
  3. Select “Browse Channels.”
  4. Find and join any channel that looks interesting!