Case-based Surveillance Capabilities and Technology Recommendations

Data Modernization Initiative
Case-based surveillance capabilities and technology
recommendations

August 2021

Case-based surveillance capabilities and technology recommendations

Table of Contents
Acknowledgements ................................................................................................................................ 2
Acronyms ................................................................................................................................................ 3
Executive Summary ................................................................................................................................ 4
Methods.................................................................................................................................................. 4
Recommendations .................................................................................................................................. 4
Background ............................................................................................................................................. 5
Methods ................................................................................................................................................. 5
Table 1. Listening session focus areas and themes by partner group ................................................ 6
Surveillance System Functions and Priorities .......................................................................................... 8
Interoperability ....................................................................................................................................... 8
Data quality ............................................................................................................................................. 8
Managing case records ............................................................................................................................ 8
Recommendations .................................................................................................................................. 8
Conclusion ............................................................................................................................................ 11
Appendix 1: Listening session participants ........................................................................................... 12
Appendix 2: Listening session key questions ........................................................................................ 13
Appendix 3: Discussion prompts by participant group .......................................................................... 14

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Case-based surveillance capabilities and technology recommendations

Acknowledgements
This project was supported by cooperative agreement number 6-NU38OT000316, funded by the Centers
for Disease Control and Prevention. Its contents are solely the responsibility of the authors and do not
necessarily represent the official views of the Centers for Disease Control and Prevention or the
Department of Health and Human Services.

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Case-based surveillance capabilities and technology recommendations

Acronyms
APIs

Application programming interfaces

AI

Artificial intelligence

APHL

Association of Public Health Laboratories

ASTHO

Association of State and Territorial Health Officials

CDC

Centers for Disease Control and Prevention

CSELS

Center for Surveillance, Epidemiology, and Laboratory Services

CoAg

Cooperative agreement

CSTE

Council of State and Territorial Epidemiologists

DMI

Data Modernization Initiative

DHIS

Division of Health Informatics and Surveillance

EHR

Electronic health record

FHIR

Fast Healthcare Interoperability Resources

HIE

Health information exchange

IIS

Immunization information system

MPI

Master patient indexes

PHII

Public Health Informatics Institute

RLS

Record locator services

RCKMS

Reportable Conditions Knowledge Management System

STLT

State, tribal, local and territorial

TEFCA

Trusted Exchange Framework and Common Agreement

USCDI

U.S. Core Data for Interoperability

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Case-based surveillance capabilities and technology recommendations

Executive Summary
The Centers for Disease Control and Prevention (CDC) has invested in a data modernization initiative (DMI)
to improve public health surveillance. Through the DMI, surveillance systems will contain more timely,
accurate and comprehensive data through enhanced interoperability across the public health ecosystem.
The CDC engaged the Public Health Informatics Institute (PHII) to identify the capabilities and technical
requirements of future surveillance systems that will meet those specifications. PHII identified five key
partner groups—public health jurisdictions, public health associations, public health informatics,
technology and the CDC—that routinely interact with current surveillance systems and could inform what
is needed to enhance their flexibility, scalability and interoperability with healthcare and public health.

Methods
PHII developed recommendations for future surveillance systems based on three distinct information
gathering methods. First, we reviewed previous assessments of case-based surveillance systems and
similar publications to understand the evolution of current functions and capabilities. Following the
review of literature, each of the five key partner groups participated in a listening session to discuss critical
components of future surveillance systems. Finally, using the information gathered from these sources,
PHII developed recommendations for future surveillance systems. An expert panel reviewed the
recommendations and offered feedback that shaped the final recommendations for case-based
surveillance presented in this paper.

Recommendations
The recommendations reflect a forward path for system technological functions and capabilities as well
as opportunities to evolve case-based surveillance strategies and approaches. Note that these
recommendations address both social and technical aspects of surveillance systems; the current challenge
is as much about the nature of people and organizations as it is about technology.
1. Establish automation through integration of surveillance systems and case management systems.
2. Balance the push and pull of data from electronic health records (EHR) to public health
departments.
3. Use artificial intelligence (AI) to automate processes and predict trends.
4. Establish uniform system standards and functionality to promote cross-jurisdictional
interoperability by creating functional requirements to collect the same information across
programs.
5. Harmonize data across public health programs by using common data models and standardized
data sets.
6. Ensure flexibility and modularity of systems development and maintenance.
7. Support scalable systems so they are readily available as the demand of the moment changes,
including the use of cloud technologies.
8. Improve entity and patient matching to improve overall data quality.
9. Improve partnerships and cross jurisdictional coordination.
10. Support intensive data access required for dedicated query systems (e.g., data lakes, data
warehouses).
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Case-based surveillance capabilities and technology recommendations
11. Streamline or simplify data transport.
In addition to the surveillance system recommendations, socio-technical recommendations emerged
during this process. There was also a need to strike the right balance between creating systems that can
accommodate the unique requirements of individual jurisdictions as well as promote interoperability
across agencies and industries.
●

●

Socio-technical recommendations for future surveillance systems: There was resounding
agreement that identifying the correct technology and defining the correct capabilities will only
address some of the limitations of current surveillance systems. People, policies, procedures and
funding all impact the system and the ability to apply technology to the full extent necessary to
modernize surveillance systems.
Finding the right balance: Critical decisions must be made that will impact the speed of
implementation and the way in which future efforts to further modernize systems unfold.
These decisions will often present trade-offs and create tension in selecting one option over
another.

Background
The COVID-19 pandemic highlighted the need for timely and accurate surveillance data for federal,
state, local, tribal and territorial public health agencies. The Centers for Disease Control and
Prevention’s (CDC) Data Modernization Initiative (DMI) is part of a national effort to develop integrated
public health data and surveillance systems to support the COVID-19 response and prepare for future
public health emergencies. Case-based surveillance systems play a significant role in conducting both
routine and emergency public health functions. With increasing demands to access and report data in
near real-time, surveillance programs need to modernize their systems to adapt to changing needs and
leverage new technologies.
The Public Health Informatics Institute (PHII) received funding through CDC’s data modernization
cooperative agreement (CoAg) to develop recommendations for state, tribal, local and territorial (STLT)
health departments. This report identifies critical case-based surveillance system capabilities and
supporting technology standards needed to modernize public health surveillance during the next five to
ten years.

Methods
To develop this report and recommendations, PHII conducted a series of listening sessions with experts
on public health surveillance technology. PHII convened an expert panel in June 2021 to provide
feedback on the recommendations.
The listening sessions involved key partners from public health jurisdictions, public health associations,
CDC, and experts in public health informatics and technology. They shared input on priorities, key
capabilities and future technologies for case-based surveillance systems. Prior to the listening sessions,
PHII reviewed past assessments of case-based surveillance systems and prior recommendations for
capabilities. This information was used to develop key questions and discussion points for the listening
sessions.
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Case-based surveillance capabilities and technology recommendations
Next, PHII and staff from the Center for Surveillance, Epidemiology, and Laboratory Services (CSELS) at
CDC identified thought leaders from the public and private sectors and invited them to participate in a
60-minute listening session. Six listening sessions were conducted in April and May 2021. Thirty-seven
participants representing five partner groups participated (Appendix 1). Participants were assigned to
listening sessions based on their partner group to encourage discussion and information sharing. Each
session began with an overview of the project, the goals for the listening session and description of the
format, followed by a participant-led discussion. To guide the discussion, participants were provided
with key questions that the recommendations will address and talking points that were customized for
each partner group (Appendices 2 and 3). All sessions were recorded with verbal permission from the
participants. Audio files were transcribed using Speechpad and qualitative data analysis techniques—
including coding and grouping of keywords— were used to identify themes.
Following the listening sessions, an expert panel convened for one 90-minute session. The panel was
composed of leaders in the fields of public health, informatics, information technology and surveillance
systems. A summary of the themes and recommendations that emerged during the listening sessions
was provided to the panel for review prior to their session. During the meeting, the panel discussed the
findings from the listening sessions and suggested refinements to the recommendations.
PHII enlisted staff with expertise in evaluation and public health information technology to listen to all
sessions conducted as a part of this project. These experts participated in the synthesis of the listening
sessions to draft the recommendations.

Findings
PHII reviewed the transcripts from the participant discussions and highlighted key focus areas for each
of the five partner groups. Within each focus area, themes were identified and grouped based on
similarity and categorized in the final recommendations. Table 1 below outlines the key focus areas and
themes that emerged during listening sessions.

Table 1. Listening session focus areas and themes by partner group
Partner group
Public health
jurisdictions

Discussion Focus Areas and Themes
●
●
●
●

●
●
●

Automate processes to reduce program burden and streamline
ingesting large amounts of data
Use artificial intelligence (AI) to streamline data processes and
conduct predictive analytics
Harmonize data across programs to improve data consistency and
completeness
Configure systems to support core surveillance system functionality
while allowing jurisdictions to adjust to their needs and supporting
flexibility as new use cases arise, such as data exchange with
immunization information systems (IIS)
Leverage Fast Healthcare Interoperability Resources (FHIR) and
application programming interfaces (APIs) to facilitate data exchange
Integrate reporting platforms including data lakes and data
warehouses
Facilitate patient record matching across systems and data sources
through the use of master patient index
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Case-based surveillance capabilities and technology recommendations

Public health
associations

●

Enhance workforce capacity to support more and better training for
public health informaticians with epidemiology and information
technology skills; increase ability for jurisdictions to compete with
the private sector to recruit and retain staff

●

Standardize system functionality expectations similar to IIS
functional standards
Integrate with case management systems
Use data lakes to allow jurisdictions to control the flow of
surveillance data into the system
Reduce or eliminate funding siloes to facilitate collaboration across
systems and programs to achieve common goals
Harmonize data to increase consistency in data collection across
programs

●
●
●
●
CDC

●
●

●

●
●
●

Surveillance system
vendors

●

●
●
●
●
Electronic health
record vendors

●

Case-based surveillance system should seek to adopt FHIR and
RESTful APIs
Case-based surveillance systems should be flexible, agile and
sustainable:
○ Flexibility in data formats and transport methods
○ Processing data without a lot of software
development/coding
○ Reduce processing burden on system and programs
○ Store data for streamlined access and analysis without
adding load to system
Case-based surveillance systems should adopt common data models,
core data sets and common data sets such as United States Core
Data for Interoperability (USCDI)
Case-based surveillance systems should be more standardized across
jurisdictions
AI should be used to “sniff” messages and make decisions based on
what is detected
Case-based surveillance systems should be more modular while
being conscious of challenges with swapping components and the
impact of changes on interoperability
Harmonize data across systems and jurisdictions, including a
standardized format and structure to improve consistency and
completeness of data
Standardize data transports to facilitate interfaces with other data
systems
Address policies that hinder data flow within and across jurisdictions
Leverage AI for predictive analytics
Reassess the purpose of surveillance systems to address modern
needs for real-time flow of data and more timely reporting
Develop a standardized case-based surveillance platform and
potentially integrate case-based surveillance systems across
programs

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Case-based surveillance capabilities and technology recommendations

●
●
●
●
●

Take advantage of FHIR and leverage health information exchanges
(HIEs) for data exchange
Develop a centralized approach for data exchange
Leverage AI for predictive analytics
Encourage public health to participate in standards definition forums
Build public health informatics expertise, especially at the policy level

Surveillance System Functions and Priorities
During the listening sessions, the participants highlighted interoperability, data quality and management
of case records as key case-based surveillance system functionalities that should be prioritized for
enhancement and support in the near future.

Interoperability
Case-based surveillance systems must be able to establish, re-establish and modify interfaces with other
information systems for the electronic exchange of case and demographic data. The interface should
enable the surveillance system to facilitate electronic data exchange with other information systems,
including electronic health records systems (EHRs), electronic laboratory systems (ELRs) and vital
records, including electronic birth and death records systems. The surveillance system should be able to
interface with internal health department systems such as syndromic surveillance systems as well as
external systems. It should also be able to exchange data electronically, as well as monitor and
troubleshoot data exchange.

Data quality
The case-based surveillance system should be capable of ensuring data quality through patient, event
and entity matching and deduplication functions. The system should be able to identify and manage
duplicate and potential duplicate patient records and event entries such as laboratory results and
electronic case reports.

Managing case records
Case-based surveillance systems should be able to integrate data from multiple health information
databases or systems into a single repository. Specifically, the surveillance system should be able to link
cases across multiple systems and data sources whether the data is being submitted directly to the
system or accessed from an external data repository.

Recommendations
These recommendations are a synthesis of the information gathered from the listening sessions and
expert panel participants. They reflect a forward path for system technological functions and capabilities
as well as opportunities to evolve case-based surveillance strategies and approaches. Note that these
recommendations are socio-technical in nature: the current challenge is as much about the nature of
people and organizations as it is about technology.

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Case-based surveillance capabilities and technology recommendations

Establish automation
through integration

As the public health mission evolves, so should the systems that support it.
Public health surveillance systems should bridge the difference between
“case management” and “surveillance” systems; few systems can
completely automate the surveillance process end to end. However, an
integrated reporting platform can be created by adding two systems
together (e.g., contact tracing and immunization data to case management
systems). As public health surveillance needs have become more
immediate, there is a need to enhance systems that were not designed to
be real-time. In addition, these systems should be built to require less
human interaction. Finally, programs can help each other by sharing
investments and deploying shared services rather than replicating all
aspects of their technical implementations.

Balance “push” and
“pull”

Systems should query (“pull”) EHRs for necessary data rather than always
expecting EHRs to push data to them. While not replacing traditional public
health reporting (“push”), this shift will allow surveillance systems to better
control the flow of certain data into the systems and reduce processing and
storage burden.

Use artificial
intelligence (AI)

As the ability to access and ingest large amounts of data across multiple
sources has increased, there is a need to be more predictive and less
reactive. Artificial intelligence is a method that can be used to conduct
automated processes, reducing the need for manual intervention by
program staff. Predictive analytics conducted by AI could also be used to
anticipate disease outbreaks and detect trends more quickly. While AI may
be a helpful solution for public health surveillance, foundational
improvements to systems are more urgent.

Establish uniform
system standards and
functionality

Uniform surveillance system standards would facilitate easier data
exchange with trading partners. System integration problems are based on
inconsistent standards across programs. This refers to everything from
standard functional requirements, to standard ways of collecting the same
information across programs, to technical standards for implementation.
Public health participation in standards development and selection will only
improve the “fit” of standards for public health needs. More centralized
services, for example, the Reportable Conditions Knowledge Management
System (RCKMS) would allow a balance of jurisdictional flexibility with
uniformity. Continued adoption of FHIR in public and private settings could
potentially address uniformity as well as facilitate interoperability.

Harmonize data across
programs

Public health program silos (e.g., disease-specific programs) still exist, even
after years of attempting to reduce and eliminate them. Informatics needs
to span programs and make them more coherent through more common
data models. Data today is coming rapidly from different and often nontraditional sources, requiring cleaning and preparation before it can be
absorbed. The use of common standardized data sets such as USCDI may
help improve data consistency and completeness. Much of what we do with
data rises and falls with common understanding of the meaning of the data,
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Case-based surveillance capabilities and technology recommendations

which is often inconsistent. Improved semantic interoperability by using
consistent terminology will ultimately enhance data sharing and use.
Ensure flexibility and
modularity of systems

An agile approach to system development and maintenance is needed to
quickly meet the demands of a rapidly changing, dynamic world. Thinking
in terms of functions instead of systems promotes modularity and flexibility.
A mitigating strategy may include a core system supplemented by a “lite,”
more flexible version to help deal with immediate, urgent needs. Modular
systems should also be considered. Use of microservices (an architecture
that assembles systems out of small building blocks) allows additional
functionality and choice in addressing emergent needs. Modularity would
have to be genuine and substitutable with components that are truly
interoperable through application program interfaces (APIs).

Support scalable
systems

Systems should be readily scalable as the demands of the moment change.
Cloud technologies—now essentially a commodity service—enable this
well.

Improve entity and
patient matching

The answer to patient matching may be the use of full agency master
patient indexes (MPI), supported by record locator services (RLS). Improved
matching will improve overall data quality, especially across programs and
potentially across jurisdictions. In addition, there is the need for better
directories for healthcare (and other) organizations relevant to public
health data.

Improve partnerships
Data must move between jurisdictions effectively, and agencies must
and cross jurisdictional consider data sharing outside their borders as a fundamental requirement
for their systems. National health information exchange efforts (such as
coordination
eHealth Exchange, CommonWell Health Alliance, Carequality, and soon
TEFCA) help make this possible through common standards and broad
clinical participation. Jurisdictions could establish vendor user groups to
share resources and experiences of surveillance systems.
Support intensive data
access required for
dedicated query
systems

Transactional surveillance and case management systems cannot bear the
load of increased demand for data for various audiences. Data warehouses
and data lakes are needed to manage the flow of data into the system and
allow collection of data for specific purposes rather than ingesting large
amounts of information regardless of case report type.

Streamline and
simplify data
transport

Public health should attempt to get as much data through one
communications “pipe” as possible. Clinical care has requested this, and
public health should be able to accommodate. HIEs can be a great help in
this area by providing a single connection to multiple public health systems,
including case-based surveillance systems. Transport should also be
standardized around fewer choices to streamline data exchange while
providing some accommodation to data partners.

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Case-based surveillance capabilities and technology recommendations

Conclusion
These recommendations lend themselves to more standardized, real-time and interoperable systems.
However, the right balance between systems that are modular and interoperable versus those that are
uniform and tightly integrated needs to be considered. System improvements that are speedier and
result in short-term gains by using existing systems versus long-term (and even delayed) gains from
implementing more standards-based solutions is another area for consideration. A balance between
speed, customization and cost needs to be identified during the implementation process to successfully
modernize systems timely and in a way that maximizes cross-entity interoperability.
There was resounding agreement that identifying the correct technology and defining the correct
capabilities will only address some of the limitations of current surveillance systems. The people,
policies, procedures and funding all impact the system and the ability to apply technology to the full
extent necessary to modernize surveillance systems.

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Case-based surveillance capabilities and technology recommendations

Appendix 1: Listening session participants
Partner groups

Number of
participants

Jurisdictions/organizations represented

Public health jurisdictions

14

● Alabama
● Connecticut
● City of Houston
● Massachusetts
● North Carolina
● Oregon
● Utah
● Virginia

Public health member
associations

3

● Association of Public Health Laboratories (APHL)
● Association of State and Territorial Health
Officials (ASTHO)
● Council of State and Territorial Epidemiologists
(CSTE)

Surveillance system vendors

7

● Conduent (Maven)
● Inductive Health
● STC
● Sunquest

Electronic health records vendors

5

● Epic
● Cerner
● Allscripts

Centers for Disease Control and
Prevention

8

● Division of Health Informatics and Surveillance
(DHIS)
● U.S. Digital Services

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Case-based surveillance capabilities and technology recommendations

Appendix 2: Listening session key questions
●
●
●
●
●
●
●

What key functionality is needed in case-based surveillance systems to support surveillance
activities more effectively?
What will make systems flexible and responsive for emergency events?
Which functionality should be integrated into the surveillance system and what should be
addressed outside the surveillance system through interoperable systems or services?
What functionality is essential for data collection and data exchange?
What will allow the systems to take advantage of technology to improve efficiency or
effectiveness?
What technology should surveillance systems be taking advantage of?
What functionality is a priority to improve data integration, data cleaning and data linkage?

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Case-based surveillance capabilities and technology recommendations

Appendix 3: Discussion prompts by participant group
Partner type

Discussion prompts

Public health
jurisdictions

1.

Shared infrastructure, enterprise-wide approaches and cloud solutions in
use or considered for future use
2. Functional enhancements to improve system flexibility and
responsiveness in emergency events
3. Integrating communicable and non-communicable condition surveillance
systems in your jurisdictions
4. Gaps and priorities for future state of case-based surveillance systems

Public health
member
associations

1.

Electronic disease
surveillance system
vendors

1.

Electronic health
records vendors

1.

CDC

1.

Innovative technologies being used or implemented in state and local
public health jurisdictions.
2. Integrating communicable and non-communicable condition surveillance
systems in state and local jurisdictions
3. Gaps and priorities for future state of case-based surveillance systems
Next generation technology that could be adapted or implemented for
public health case-based surveillance systems
2. Case-based surveillance system functions and shared services
3. Standards that should be updated or developed to facilitate the
collection and sharing of surveillance data and case information across
jurisdictions and with CDC
Strengthening partnerships between public health jurisdictions and EHR
vendors to support EHR integration with public health surveillance
systems
2. Interoperability standards that should be updated or developed to
facilitate the collection and sharing of EHR data with public health
jurisdictions and CDC
3. Next generation technology that should be considered for
implementation by public health jurisdictions to facilitate data sharing
with EHRs
4. Opportunities for public health to enhance the value of electronic data
exchange with EHRs
Innovative technologies being used or implemented in state and local
public health jurisdictions
2. Next generation technology that should be considered for
implementation by public health jurisdictions to enhance case-based
surveillance systems
3. Gaps and priorities for future state of case-based surveillance systems
4. Shared services platforms or technologies that CDC is prioritizing to
support public health case-based surveillance data infrastructure at the
jurisdiction level

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