Heterogeneity and Interoperability in Local Public Health Information Systems : Journal of Public Health Management and Practice

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Heterogeneity and Interoperability in Local Public Health Information Systems

Bosco, Laura J. MPhil; Alford, Aaron A. PhD; Feeser, Karla MPH

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Journal of Public Health Management and Practice 27(5):p 529-533, September/October 2021. | DOI: 10.1097/PHH.0000000000001404
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The growing streams of digital health information present opportunities for improving public health through better disease surveillance, faster communication, more targeted interventions, and overall improved management of public health systems.1 The COVID-19 pandemic, however, has exposed challenges that remain for collecting and communicating timely, accurate, and complete public health data across the United States' fragmented and often outdated public health data systems.2 In particular, interoperability across digital surveillance and health care information systems severely hampered the national response.3

As the US government and public health systems are turning toward postpandemic planning and recovery, it is useful to understand the heterogeneity and interoperability of public health information systems used during the COVID-19 response. In this article, we present evidence from NACCHO's 2020 Forces of Change survey focused on the electronic infrastructure of local health departments (LHDs). In particular, we focus on describing the local adoption of interoperable systems and characterizing the breadth of electronic platforms used by LHDs.

Why Interoperable Public Health Surveillance Is Important

Public health surveillance systems collect, analyze, interpret, and communicate health-related data required for the “planning, implementation, and evaluation of public health practice.”4 Robust surveillance systems serve valuable public health functions, including supporting earlier detection of infectious outbreaks; informing policy maker, first-responder, and preparedness responses; bolstering public communications and reducing public fears; and guiding strategic redirection of public health resources.5*

In the United States, public health surveillance is the purview of diverse, overlapping actors, involving the federal government, local jurisdictions, and private organizations such as hospitals, laboratories, and outpatient care facilities. Efficient information flows between the many extant systems are important. Interoperability is the extent to which systems and devices can automatically exchange data and interpret that shared data.6 In the case of public health surveillance data, this most frequently refers to the electronic transfer of clinical information. The uptake of electronic health record systems, electronic laboratory reporting, and health information exchanges has increased over the last decade but unevenly across jurisdictions.7 Many LHDs, particularly smaller and more rural jurisdictions, lack the resources, informatics capacity, or governing authority to implement necessary technological changes to ensure interoperability.

In 2018, the US Department of Health and Human Services released A 10-Year Vision to Achieve an Interoperable Health IT Infrastructure, which emphasized the importance of “advanc[ing] the connectivity of electronic health information and interoperability of health information technology.”8 In 2020, however, reliance on manual processes for data transmission and incomplete data sources remained particular challenges, hampering public health authorities' ability to respond the COVID-19 pandemic.9


Data for this article are primarily drawn from the 2020 Forces of Change survey, which aims to assess the effect of trends in public health on LHD infrastructure and practice, identify infrastructure challenges, and explore opportunities to strengthen public health capacity. A statistically representative sample was drawn from the LHD population using a stratified random sampling design that grouped LHDs by state and the size of the population served. For stratification by the size of population served, 3 categories were used: small (<50 000 people served), medium (50 000-499 999 people served), and large (≥500 000 people served). Because LHDs with large population sizes represent a relatively small portion of all LHDs, these LHDs were oversampled to ensure a sufficient number of responses for the analysis.

The 2020 Forces of Change survey included a set of core questions sent to a census of LHD population and a module questionnaire sent to the statistically representative sample. The questionnaire was distributed using Qualtrics from October 2020 to March 2021 (n = 583; 24% response rate). Questions specific to information technology and interoperability were included in the module, which was sent to 905 LHDs (n = 236; 31% response rate). Rhode Island was excluded from the study because it has no LHDs. Responses were self-reported; NACCHO did not independently verify responses. Nationally representative estimates were weighted to account for nonresponse by the size of population served.

LHD Informatics Capacity and Actions

The interoperability of local public health information systems has improved since previous iterations of this survey, but most systems remain only partially interoperable. In 2020, fewer LHDs report that “none” of their systems are interoperable—decreasing from 34% of LHDs in 2018 to 25% in 2020, and more report that “all” of their systems are interoperable—increasing from 3% to 13% over the same period. The vast majority of LHDs, however, continue to report that their systems remain “some”-where in between—some systems are interoperable and others not (Figure).

Interoperability of Information Systems, 2018 and 2020aAbbreviation: LHD, local health department.aQuestion wording was consistent across years: “How interoperable are the information systems used by your LHD?”

Reported levels of interoperability varied depending on the size of the LHD. Small LHDs serving populations of 50 000 or fewer were more likely to report either that “all” of their systems were interoperable (13%) or that “none” of their systems were (25%). Far fewer large LHDs reported that “none” of their systems were interoperable (11%), but large LHDs were also less likely to report that “all” of their systems were integrated. The disjuncture likely reflects differences in the number and sophistication of information systems available for use at LHDs, in the first place.

During the pandemic, LHDs were using a staggering array of surveillance systems to collect, manage, or share COVID-19 data (Table 1). Ninety-six percent of LHDs reported use of at least one information management system in 2020, with the average LHD reporting that it used 2.5 systems. The most widely used systems were geographically bounded or relatively low-tech applications. Eighty-six percent of LHDs used state disease surveillance systems for COVID-19 data, 21% used local surveillance systems, and 40% used Microsoft Excel. Both trends present challenges for interoperability.

The use of surveillance applications generally increased significantly during the pandemic. In 2018, just over half of LHDs reported using a public health surveillance application and usage rates varied significantly by department size. Eighty percent of large LHDs reported using at least one application compared with just 39% of small LHDs. In 2020, large LHDs continued to report more extensive and diverse use of public health information applications. A plurality of large LHDs reported also using geographic information systems (69%), statistical software (69%), and the federally supported Electronic Surveillance System for Early Notification of Community-based Epidemics (ESSENCE) (58%). Small and medium LHDs were much less likely to report using any of the previously established surveillance-specific applications (eg, ESSENCE, ILINet, and the BioSense platform) to manage COVID-19 data.

TABLE 1 - Public Health Surveillance Applications, 2020 and 2018a
All LHDs Size of Population Served by LHDs
<50 000 50 000-499 999 500 000+
At least one application used (2020) 96% (n = 232) 93% (n = 138) 99% (n = 75) 100% (n = 19)
State disease surveillance system 86% 83% 90% 95%
Microsoft Excel 40% 38% 40% 69%
Locally disease surveillance system 21% 17% 22% 54%
Geographic Info. System (GIS) 16% 5% 25% 69%
Statistical software (eg R, Stata) 15% 6% 22% 69%
ILINet 13% 8% 20% 31%
ESSENCE 13% 7% 17% 58%
COVID-NET 6% 4% 10% 15%
BioSense platform 6% 4% 4% 32%
MTX or other text message system 3% 1% 4% 5%
Other digital contact tracing tools 23% 19% 27% 42%
Other 5% 4% 4% 17%
None 4% 7% 1% 0%
At least one application used (2018) 53% (n = 564) 39% 68% 80%
ESSENCE 18% 8% 29% 35%
Syndromic System State 16% 16% 18% 10%
Locally developed system 13% 6% 21% 24%
Abbreviation: LHD, local health department.
aThe wording of the questions varied across survey years. In 2018, the survey asked, “What syndromic surveillance application(s) does your LHD currently use?” In 2020, the survey asked, “Which of the following information management applications does your LHD use for collecting, managing, or sharing health information, specifically for COVID-19?” For 2018, the table presents the 3 categories most frequently selected. For 2020, all option choices are presented.

Information systems were important to manage the extensive number of surveillance activities LHDs conducted in 2020 and thus data sources available. Nearly all LHDs (96%) reported conducting at least one type of surveillance activity for COVID-19. The majority conducted contact tracing (87%), school-based (73%) and congregate living (57%) surveillance, and setting up immediate case notification systems (68%) (Table 2). Larger LHDs again reported greater breadth of activity here. A plurality of large LHDs reported also collecting mortality data, implementing testing-based cluster identification, and conducting laboratory surveillance.

TABLE 2 - Public Health Surveillance Activities Conducted for COVID-19 Pandemic, 2020a
All LHDs Size of Population Served by LHDs
<50 000 50 000-499 999 500 000+
Any surveillance activity 96% (n = 236) 96% (n = 139) 94% (n = 77) 100% (n = 20)
Contact tracing 87% 86% 87% 95%
School-based surveillance 73% 78% 64% 75%
Immediate case notification system 68% 68% 70% 65%
Surveillance of congregate living 57% 51% 65% 71%
Mortality 43% 40% 47% 60%
Testing-based cluster identification 38% 35% 38% 71%
Laboratory/virologic surveillance 34% 29% 38% 58%
Other surveillance of hospital data 31% 25% 38% 49%
Syndromic surveillance 26% 19% 36% 50%
Hotspot identification through surveillance of sewage systems 13% 12% 12% 34%
Other 2% 2% 1% 0%
None 4% 4% 6% 0%
Abbreviation: LHD, local health department.
aQuestion wording: “What types of surveillance does your LHD conduct specifically for COVID-19 (including both suspected and confirmed cases) in your jurisdiction?”


The most commonly reported surveillance applications used by LHDs may raise some flags of concern, especially for those pursuing interoperable public health systems across the country. The most frequently used surveillance applications during the pandemic were geographically confined or relatively “low-tech.” Presumably, these systems have limited interoperability nationally, though our current study does not measure this directly. In addition, while large LHDs used more sophisticated, national surveillance-specific applications (eg, ILINet, ESSENCE, COVID-NET, BioSense platform), few medium LHDs and fewer still small health departments reported the same.

Today, the CDC maintains more than 100 surveillance systems. In a 2016 estimate, one-third of its grant awards support surveillance-related programs and about a quarter of the CDC's staff conduct surveillance-related activities.2 On the one hand, redundancy, and even proliferation, is important in public health, as one cannot predict the shape of future public health crises, nor the type of data that will prove important to combat it. Absent interoperability, however, prolific systems lead to duplication, strain resources, and increase reporting burdens, which can undermine motivation.10 This is especially true for small LHDs—the plurality (61%) of all US health departments—which only average between 12 and 23 full-time equivalent staff.11

COVID-19 stressed—and stressed the importance of—public health information systems in the United States. In the aftermath, Congress has earmarked significant funding across all levels of government to support the modernization of public health information technology.12 Hamilton and colleagues caution,

Modernization is not just network upgrades; it is a commitment to build a world-class workforce with a new generation of skilled public health data scientists, laboratories, and electronic, interoperable enterprise data systems that are ready for the next public health emergency.9

The 2020 Forces of Change survey underlines the extant opportunity for so improving the use and interoperability of public health information systems at the local level. Information management systems at LHDs are presently heterogeneous and inconsistently interoperable. Investment in the collection and communication of more accurate, timely, and complete data across public health's many actors would not only support a better response in some future health emergency but also benefit the daily actions of local public health officials working across the country.


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2. Sekar K, Napili A. Tracking COVID-19: U.S. Public Health Surveillance and Data. Washington, DC: Congressional Research Service. R46588. https://crsreports.congress.gov/product/pdf/IN/IN11584. Published November 2, 2020. Accessed May 20, 2021.
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4. Wolitski R, Janssen R, Holgrave D, Peterson J. The public health response to the HIV epidemic in the U.S. In: Wormser G, ed. AIDS and Other Manifestations of HIV Infection. Cambridge, MA: Academic Press; 2004:997–1012. Definition accessed: Epidemiological Surveillance. Science Direct. https://www.sciencedirect.com/topics/medicine-and-dentistry/epidemiological-surveillance. Accessed May 27, 2021.
5. Centers for Disease Control and Prevention. National Syndromic Surveillance Program: syndromic surveillance in action. https://www.cdc.gov/nssp/success-stories.html. Published August 2020. Accessed May 20, 201.
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8. Office of the National Coordinator for Health Information Technology. Connecting health and care for the nation: a 10-year vision to achieve an interoperable health IT infrastructure. https://www.healthit.gov/resource/10-year-vision-achie-ve-interoperable-health-it-infrastructure. Published November 13, 2018. Accessed May 22, 2021.
9. Hamilton JJ, Turner K, Cone ML. Responding to the pandemic: challenges with public health surveillance systems and development of a COVID-19 national surveillance case definition to support case-based morbidity surveillance during the early response. J Public Health Manag Pract. 2021;27(suppl 1):S80–S86.
10. Garcia MC, Garrett NY, Singletary V, et al. An assessment of information exchange practices, challenges, and opportunities to support US disease surveillance in 3 states. J Public Health Manag Pract. 2018;24(6):546–533.
11. National Association of County and City Health Officials. 2019 National Profile of Local Health Departments. Washington, DC: National Association of County and City Health Officials; 2020:22, 49.
12. Jercich K. COVID-19 relief package includes health IT expansion. Healthcare IT News. March 11, 2021. https://www.healthcareitnews.com/news/covid-19-relief-package-includes-health-it-expansion. Accessed May 20, 2021.

*Specifically referencing the following 4 success story reports shared on the site: “Syndromic data and collaboration enhance substance overdose surveillance—Nebraska Department of Health and Human Services,” “North Carolina integrates data from disaster medical assistance teams for improved situation awareness,” “Tennessee uses syndromic surveillance to identify potential cases of mumps,” and “Syndromic surveillance shows rise in emergency department visits after cases of Ebola.”

†NACCHO surveys use the HIMSS's definition for interoperability.

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