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Public health surveillance is the foundation of effective public health practice. Public health surveillance is defined as the ongoing systematic collection, analysis, and interpretation of data, closely integrated with the dissemination of these data to the public health practitioners, clinicians, and policy makers responsible for preventing and controlling disease and injury.1 Ideally, surveillance systems should support timely, efficient, flexible, scalable, and interoperable data acquisition, analysis, and dissemination. However, many current systems rely on disease-specific approaches that inhibit efficiency and interoperability (eg, manual data entry and data recoding that place a substantial burden on data partners) and use slow, inefficient, out-of-date technologies that no longer meet user needs for data management, analysis, visualization, and dissemination.2–4 Advances in information technology, data science, analytic methods, and information sharing provide an opportunity to substantially enhance surveillance. As a global leader in public health surveillance, the Centers for Disease Control and Prevention (CDC) is working with public health partners to transform and modernize CDC’s surveillance systems and approaches. Here, we describe recent enhancements in surveillance data analysis and visualization, information sharing, and dissemination at CDC and identify the challenges ahead.
Examples of Enhanced Data Collection
CDC is making progress on improving surveillance data for public health action at the local, state, and federal levels (Table 1). Examples include advancing data timeliness, leveraging existing data platforms to address emerging needs, using nontraditional data sources, and improving the representativeness of data through better population coverage.
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Table 1. Examples of data collection enhancements at the Centers for Disease Control and Prevention
Understanding the causes of deaths is an important element of surveillance to guide disease prevention. In 2011, only 10% of death reports reached CDC’s National Center for Health Statistics (NCHS) within 10 days of death, limiting the ability to use these data for prompt mortality surveillance. Supported by federal investments and technical support, state vital registration programs improved mortality reporting in 2016 to 50% of death reports reaching NCHS within 10 days of death (unpublished data, D. Atkinson, 2016). With improved timeliness, death reports are now being used for better mortality surveillance of health conditions ranging from influenza to prescription drug overdoses.5,6 For example, NCHS reports on influenza-related deaths became the primary national source of data in 2016, replacing the longstanding 122 Cities Influenza and Pneumonia Mortality System.7
Another data enhancement has taken place in national surveys, which contribute to improving public health surveillance. For example, the National Health and Nutrition Examination Survey added new measures on sodium excretion (in 2016) and transfats (in 2012) that aim to improve national surveillance on these risk factors for heart disease and stroke.8,9
Established in 1995, the Emerging Infections Program is a US network of public health agencies and academic partners that conducts active surveillance and applied research. In the past several years, the Emerging Infections Program expanded population coverage and was instrumental in activities such as evaluating the 7-valent pneumococcal conjugate vaccine after licensure; honing strategies for preventing severe disease in newborns caused by group B streptococcus; developing methods to estimate 2009 H1N1 influenza cases, hospitalizations, and deaths; and defining the rapidly changing epidemiology and growing burden of antimicrobial-resistant infections and prescription drug overdose.10 Timely molecular characterization of infectious disease pathogens through whole-genome sequencing is now essential to infectious disease investigations and surveillance, and the method has improved markedly through investments in advanced molecular detection.11 In 2016, an outbreak of human immunodeficiency virus (HIV) in southern Indiana demonstrated the power of these tools to understand the origin and transmission patterns in a complex regional outbreak.12 The use of whole-genome sequencing also increased the rapidity of detecting even small Listeria foodborne outbreaks and is poised to transform PulseNet, the major foodborne outbreak detection system, which currently relies on pulsed-field gel electrophoresis typing of foodborne pathogens.
Surveillance data enhancement has also benefited the monitoring of injuries, risk factors for heart disease, and health care–associated infections. The National Violent Death Reporting System integrates data from state and local medical examiner, coroner, law enforcement, toxicology, and vital statistics records to support surveillance for fatal injuries. Through a recent expansion to 42 states, an enhanced web interface, and improved data analysis tools, the National Violent Death Reporting System is improving the usefulness of surveillance data to guide national and state violent death prevention efforts.13 Led by CDC and the Centers for Medicare & Medicaid Services, the Million Hearts program has advanced heart disease risk factor surveillance by better using health care quality data.14,15 Similarly, CDC’s National Healthcare Safety Network is improving the nation’s surveillance data on health care–associated infections through expansion from 300 facilities in the 1990s to 17 000 participating medical facilities in 2016, and through linkage of its data to the Centers for Medicare & Medicaid Services quality reporting system.16
Enhancements to Data Analysis and Visualization
In the past several years, CDC has made strides toward providing better tools to support access to, analysis of, and visualization of surveillance data (Table 2). At an agency level, the website data.cdc.gov provides access to a broad range of data sets at CDC along with a standards-compliant application programming interface for sharing data and information with nongovernmental users.17 CDC’s WISQARS (Web-based Injury Statistics Query and Reporting System) is an interactive, online database to analyze data on fatal and nonfatal injuries, violent deaths, and costs of injuries.18 Recently, WISQARS added a mobile application to improve access and visualization for the media, public health professionals, and the public. Sortable Risk Factors and Health Indicators is an interactive tool that allows users to analyze data sets comprising behavioral risk factors and health indicators.19 The tool compiles data from various published CDC and federal sources into a format that allows users to view, sort, and analyze data at the state, territorial, regional, and national levels. In 2015, NCHS added a data visualization hub to allow for improved data visualization of selected NCHS data sets.20 The National Environmental Public Health Tracking Network (hereinafter, Tracking Network) is a system of integrated health, exposure, and environmental hazard information and data that is accessible to users through an interactive public web portal.21 Recently, the Tracking Network enhanced its web query interface to make it more user-friendly and to allow analysis and visualization of selected data at the subcounty, county, state, and national levels. The new web interface improves public health practitioners’ and decision makers’ ability to identify and address environmental public health issues.
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Table 2. Examples of enhancement to online tools for data analysis and visualization at the Centers for Disease Control and Prevention (CDC)
The Behavioral Risk Factor Surveillance System (BRFSS) now collects survey data from 400 000 participants representing all 50 states, the District of Columbia, and 3 US territories on health-related risk behaviors, chronic health conditions, and use of preventive services.22,23 With updated online analytic and visualization tools (ie, Selected Metropolitan/Micropolitan Area Risk Trends of BRFSS), the BRFSS now allows users to assess prevalence, trends, chronic disease indicators, and, increasingly, city- and county-level data. Another survey, the Youth Risk Behavior Surveillance System, has expanded coverage and upgraded analytic tools online.24,25 Analysts can filter and sort data by race/ethnicity, sex, grade, or site; create customized tables and graphs; and perform statistical tests by site and health topic. For policy surveillance, CDC’s Prevention Status Reports highlight the status of public health policies and practices designed to address important public health problems and concerns.26 Created in 2013, Prevention Status Reports use a simple, 3-level rating scale to show the extent to which states have implemented certain policies or practices in accordance with supporting evidence and expert recommendations.
Enhanced Tools for Information Dissemination
CDC also has made efforts to improve the dissemination of surveillance information (Table 3). Often called “the voice of CDC,” the Morbidity and Mortality Weekly Report (MMWR) is the agency’s primary vehicle for scientific publication of epidemiologic and surveillance data, health information, and recommendations.27MMWR has grown in recent years to >250 000 electronic subscribers and receives >23 million page views annually. In 2015, MMWR received its first Journal Impact Factor with the highest score among 239 journals receiving an impact factor for the first time.
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Table 3. Enhancements to tools for information dissemination at the Centers for Disease Control and Prevention (CDC)
CDC Vital Signs, a CDC-wide monthly communication initiative launched in 2010, includes an MMWR Early Release report on a topic, a graphic fact sheet and website, a media release, and social media tools.28 Reports cover topics such as colorectal and breast cancer screening, obesity, alcohol and tobacco use, HIV testing, motor vehicle safety, cardiovascular disease, teen pregnancy, health care–associated infections, and foodborne disease. In 2009, CDC launched Public Health Grand Rounds, a monthly webcast created to share epidemiologic and surveillance data and intervention strategies and to foster discussion on major public health issues to an audience beyond CDC.29
CDC Surveillance Strategy
In 2014, CDC initiated a strategy to improve surveillance systems at CDC with state and local health agency partners.3 In addition to the aforementioned progress on mortality reporting, the strategy focused on 3 other principal initiatives: notifiable diseases, electronic laboratory reporting (ELR), and syndromic surveillance based on emergency department visits. The National Notifiable Disease Surveillance System (NNDSS), a partnership among states, CDC, and the Council of State and Territorial Epidemiologists, is undergoing a much-needed modernization.30,31 NNDSS is a data reporting system for >100 notifiable conditions that has been supported by 25-year-old, outdated electronic message standards.30 Since 2014, CDC programs from across the agency have partnered to harmonize many common data elements, standardize data content and structure, and build new electronic messaging systems that allow more timely and effective data transfer. In December 2016, ten states, representing approximately 25% of the US population, began to transmit data to CDC using the new standards.31 The improvements will simplify notifiable disease reporting from states to CDC and allow for more efficient and timely data analysis and reporting.
Working with commercial laboratories and state public health agencies, along with the Association of Public Health Laboratories and the Council of State and Territorial Epidemiologists, CDC has made substantial progress on ELR from health care facilities to local and state public health agencies.32 ELR accelerates reportable disease reporting, improves data validity, and better integrates electronic information into state health information systems and NNDSS.3 Since 2010, CDC has provided resources to state, local, and territorial health departments for ELR implementation. Of 20 million laboratory reports for reportable diseases to public health agencies in 2015, 75% were transmitted electronically, up from 54% in 2012. Recent collaborations with large clinical laboratories are expected to increase ELR to >80% during 2017.
CDC launched its BioSense program in 2003 to provide a nationwide integrated public health surveillance system for early detection and assessment of potential bioterrorism-related illness.33 The program evolved from an initial design, in which data flowed from facilities directly to CDC, to one focused on building syndromic surveillance capacity at the local, state, and national levels. In 2015, working with participating state and local health agencies, CDC transitioned BioSense to the National Syndromic Surveillance Program (NSSP) to improve the technological approach to syndromic surveillance and strengthen the syndromic surveillance community of practice. The cloud-based platform that supports the NSSP was upgraded in 2016 to improve the processing of millions of records received daily and to include new analysis and visualization tools and services. Currently, the program captures data from nearly 60% of US hospital emergency department visits, and it has become a model for electronic data exchange between health care agencies and public health. A fuller discussion of progress in syndromic surveillance can be accessed in the accompanying supplementary issue of Public Health Reports.
The CDC Health Informatics Innovation Consortium, created in 2014, is a forum for sharing innovation successes and failures.34 The consortium holds quarterly open webinars and has funded 16 projects (<$50 000 per project) to make important contributions to informatics evolution at CDC. A key benefit of the consortium has been to increase the sharing of lessons learned and to improve collaboration and innovation among agency surveillance programs.
Challenges and Opportunities
Although the examples provided represent progress in enhanced data collection, data analysis, data visualization, and information dissemination, CDC and its partners continue to face major challenges and opportunities to improve public health surveillance. In the future, public health surveillance will depend increasingly on the secondary use of existing data and information found in rapidly evolving health care information systems, as well as nonhealth information systems with data on social determinants. The US Department of Health and Human Services (HHS) vision for the evolution of US health information technology is outlined in the Shared Nationwide Interoperability Roadmap.35,36 Three key areas of focus for CDC to improve public health surveillance and incorporate recommendations from the Roadmap include (1) implementing shared information technology services, (2) developing the surveillance workforce, and (3) harnessing electronic health records and health care information technology systems.
Shared Information Technology Services
To promote public health data interoperability, particularly among CDC, state and local health agencies, and health care systems, CDC needs to foster and catalyze a standards-based, shared health information technology services environment. The use of information technology services and standards from health care, such as HL7 Clinical Document Architecture and Fast Healthcare Interoperability Resources, can promote data harmonization, improve cybersecurity, and more efficiently manage resources.37,38 To accelerate progress, CDC is moving toward greater use of shared digital data services and an interoperable, integrated, cloud-based data platform. Although CDC has identified and begun developing an initial set of prioritized shared digital data services, substantial work remains to develop, deploy, support, and govern the use of shared information technology services both within CDC and with external partners.39 In addition to promoting data interoperability, shared information technology services have the potential to offer new tools for data analytics, data visualization, and information dissemination.
Workforce Development
In recognition of emerging trends in health care delivery, medical care payment, and patterns of morbidity and mortality, public health agencies are decreasing their roles as direct medical providers and pursuing a more prominent role that involves community health assessment, primary prevention, and health promotion.40 Increasingly, public health must address the social determinants of health; to do so, data are needed on housing, transportation, telecommunications, environment, weather, population density, and neighborhood sociodemographic characteristics. To best develop the information needed for rapid and cost-effective decision making, public health surveillance activities increasingly must complement the use of traditional health-based data sources with data on the social determinants of health. At the same time, the public health workforce must continue to adapt. For example, expertise in informatics is needed more broadly across the entire public health workforce, and literacy in multisectoral data, systems science, diplomacy, partnership building, and policy development is needed at every level.41–43 CDC currently has training programs in public health informatics and related disciplines, which will need to adapt to these emerging data and informatics needs.
To extend the capabilities of CDC’s internal information technology workforce, CDC has worked with HHS’s Office of the Chief Technology Officer (IDEA Lab) Entrepreneur-in-Residence program to ask experts from outside the government to join CDC as term-limited employees focused on entrepreneurial approaches to complex problems. To date, CDC has embedded 5 entrepreneurs with specialty in modern software design, data science, and high-complexity data management. This program helps to fill immediate resource gaps in CDC while also developing and extending the skills of CDC staff members.44 Although it is an important first step, it does not meet the growing information technology workforce needs at state and local health departments or represent a long-term, strategic approach to developing an information technology workforce at the federal level. CDC must look for more opportunities to leverage private-sector and entrepreneurial talent and complement the public-sector workforce.
Harnessing Data From Electronic Health Records and Health Information Systems
Electronic case reporting (eCR) is the automated electronic generation and transmission of reports of potential cases of reportable conditions from the electronic health record to state and local public health authorities for review and action. eCR can allow state and local health departments to conduct real-time surveillance without burdening health care providers. As part of fulfilling Medicare requirements for electronic health record implementation, clinicians will need to be able to send electronic case reports to state and local public health agencies by mid-2018.45 Building on the experiences and successes of previous ELR initiatives, CDC and key public health associations, such as the Council of State and Territorial Epidemiologists, Association of State and Territorial Health Officials, Association of Public Health Laboratories, and National Association of County and City Health Officials, have partnered to create tools and to propose a technical framework for eCR that will be interoperable and scalable nationally. The Robert Wood Johnson Foundation has convened leaders among electronic health record vendors, clinical provider systems, and public health to support eCR as an important step toward broader bidirectional information exchange between clinicians and health departments.45 Although initial planning for eCR started in 2016, true integration of eCR into workflows of clinicians and at public health agencies will be essential to realize its potential to support true bidirectional information exchange and improve public health action. Initial work on eCR is focused on reportable infectious diseases, and this approach may offer opportunities for timelier and better quality data on chronic health conditions, environmental health hazards, and injuries.
Conclusion
Although the improvements described here in data collection, visualization, and dissemination are important for CDC, much work remains to be done. Building on these efforts, CDC, working with state and local partners, will need to continue progress in improving interoperability, improving standards development and implementation, and reducing unnecessary duplication and inefficiency. Ultimately, systems are needed that efficiently allow data to move from clinical encounters or primary data collection at a local level to public health departments, and to be appropriately shared with CDC with minimal human effort, while also maintaining privacy and protecting confidentiality of individual data. These systems can make the best use of technology to reduce burden, particularly on data partners, and improve both the quality and timeliness of data collection, analyses, and dissemination. In addition to technology and workforce, a key component of developing these systems will be trust between data partners in local and state health departments and CDC. An important value in the efforts described here has been building trust, which will be key to sustaining and enhancing progress. Trust is key for sharing data but is even more important for how the data and subsequent analyses are shared with partners and the public. Consequently, further advances in surveillance are intimately connected to both data collection and dissemination.
Acknowledgments
The authors thank the following individuals for comments and suggestions on earlier versions of the manuscript: Kathryn Foti, Rima Khabbaz, Robin Ikeda, Patricia Simone, Robin Wagner, Paul Sutton, and Charlie Rothwell.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
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