New York City and state legal authorities related to syndromic surveillance.
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Bioterrorism↗
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Syndromic surveillance using minimum transfer of identifiable data: the example of the National Bioterrorism Syndromic Surveillance Demonstration Program.
Several health plans and other organizations are collaborating with the Centers for Disease Control and Prevention to develop a syndromic surveillance system with national coverage that includes more than 20 million people. A principal design feature of this system is reliance on daily reporting of counts of individuals with syndromes of interest in specified geographic regions rather than reporting of individual encounter-level information. On request from public health agencies, health plans and telephone triage services provide additional information regarding individuals who are part of apparent clusters of illness. This reporting framework has several advantages, including less sharing of protected health information, less risk that confidential information will be distributed inappropriately, the prospect of better public acceptance, greater acceptance by health plans, and less effort and cost for both health plans and public health agencies. If successful, this system will allow any organization with appropriate data to contribute vital information to public health syndromic surveillance systems while preserving individuals' privacy to the greatest extent possible.
Bioterrorism↗
A systems overview of the Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE II).
The Electronic Surveillance System for the Early Notification of Community-Based Epidemics, or ESSENCE II, uses syndromic and nontraditional health information to provide very early warning of abnormal health conditions in the National Capital Area (NCA). ESSENCE II is being developed for the Department of Defense Global Emerging Infections System and is the only known system to combine both military and civilian health care information for daily outbreak surveillance. The National Capital Area has a complicated, multijurisdictional structure that makes data sharing and integrated regional surveillance challenging. However, the strong military presence in all jurisdictions facilitates the collection of health care information across the region. ESSENCE II integrates clinical and nonclinical human behavior indicators as a means of identifying the abnormality as close to the time of onset of symptoms as possible. Clinical data sets include emergency room syndromes, private practice billing codes grouped into syndromes, and veterinary syndromes. Nonclinical data include absenteeism, nurse hotline calls, prescription medications, and over-the-counter self-medications. Correctly using information marked by varying degrees of uncertainty is one of the more challenging aspects of this program. The data (without personal identifiers) are captured in an electronic format, encrypted, archived, and processed at a secure facility. Aggregated information is then provided to users on secure Web sites. When completed, the system will provide automated capture, archiving, processing, and notification of abnormalities to epidemiologists and analysts. Outbreak detection methods currently include temporal and spatial variations of odds ratios, autoregressive modeling, cumulative summation, matched filter, and scan statistics. Integration of nonuniform data is needed to increase sensitivity and thus enable the earliest notification possible. The performance of various detection techniques was compared using results obtained from the ESSENCE II system.
Bioterrorism↗
Use of ambulance dispatch data as an early warning system for communitywide influenzalike illness, New York City.
In 1998, the New York City Department of Health and the Mayor's Office of Emergency Management began monitoring the volume of ambulance dispatch calls as a surveillance tool for biologic terrorism. We adapted statistical techniques designed to measure excess influenza mortality and applied them to outbreak detection using ambulance dispatch data. Since 1999, we have been performing serial daily regressions to determine the alarm threshold for the current day. In this article, we evaluate this approach by simulating a series of 2,200 daily regressions. In the influenza detection implementation of this model, there were 71 (3.2%) alarms at the 99% level. Of these alarms, 64 (90%) occurred shortly before or during a period of peak influenza in each of six influenza seasons. In the bioterrorism detection implementation of this methodology, after accounting for current influenza activity, there were 24 (1.1%) alarms at the 99% level. Two occurred during a large snowstorm, 1 is unexplained, and 21 occurred shortly before or during a period of peak influenza activity in each of six influenza seasons. Our findings suggest that this surveillance system is sensitive to communitywide respiratory outbreaks with relatively few false alarms. More work needs to be done to evaluate the sensitivity of this approach for detecting nonrespiratory illness and more localized outbreaks.
Ambulances↗
Clinical evaluation of the Emergency Medical Services (EMS) ambulance dispatch-based syndromic surveillance system, New York City.
Since 1998, the New York City Department of Health has used New York City Emergency Medical Services (EMS) ambulance dispatch data to monitor for a communitywide rise in influenzalike illness (ILI) as an early detection system for bioterrorism. A clinical validation study was conducted during peak influenza season at six New York City emergency departments (EDs) to compare patients with ILI brought in by ambulance with other patients to examine potential biases associated with ambulance dispatch-based surveillance. We also examined the utility of 4 EMS call types (selected from 52) for case detection of ILI. Clinical ILI was defined as fever (temperature higher than 100 degrees F) on history or exam, along with either cough or sore throat. Of the 2,294 ED visits reviewed, 522 patients (23%) met the case definition for ILI, 64 (12%) of whom arrived by ambulance. Patients with ILI brought in by ambulance were older, complained of more severe symptoms, and were more likely to undergo diagnostic testing, be diagnosed with pneumonia, and be admitted to the hospital than patients who arrived by other means. The median duration of symptoms prior to presenting to the ED, however, was the same for both groups (48 hours). The selected call types had a sensitivity of 58% for clinical ILI, and a predictive value positive of 22%. Individuals with symptoms consistent with the prodrome of inhalational anthrax were likely to utilize the EMS system and usually did so early in the course of illness. While EMS-based surveillance is more sensitive for severe illness and for illness affecting older individuals, there is not necessarily a loss of timeliness associated with EMS-based (versus ED-based) surveillance.
Adolescent↗
Biosurveillance applying scan statistics with multiple, disparate data sources.
Researchers working on the Department of Defense Global Emerging Infections System (DoD-GEIS) pilot system, the Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE), have applied scan statistics for early outbreak detection using both traditional and nontraditional data sources. These sources include medical data indexed by International Classification of Disease, 9th Revision (ICD-9) diagnosis codes, as well as less-specific, but potentially timelier, indicators such as records of over-the-counter remedy sales and of school absenteeism. Early efforts employed the Kulldorff scan statistic as implemented in the SaTScan software of the National Cancer Institute. A key obstacle to this application is that the input data streams are typically based on time-varying factors, such as consumer behavior, rather than simply on the populations of the component subregions. We have used both modeling and recent historical data distributions to obtain background spatial distributions. Data analyses have provided guidance on how to condition and model input data to avoid excessive clustering. We have used this methodology in combining data sources for both retrospective studies of known outbreaks and surveillance of high-profile events of concern to local public health authorities. We have integrated the scan statistic capability into a Microsoft Access-based system in which we may include or exclude data sources, vary time windows separately for different data sources, censor data from subsets of individual providers or subregions, adjust the background computation method, and run retrospective or simulated studies.
Bioterrorism↗
WSARE: What's Strange About Recent Events?
This article presents an algorithm for performing early detection of disease outbreaks by searching a database of emergency department cases for anomalous patterns. Traditional techniques for anomaly detection are unsatisfactory for this problem because they identify individual data points that are rare due to particular combinations of features. Thus, these traditional algorithms discover isolated outliers of particularly strange events, such as someone accidentally shooting their ear, that are not indicative of a new outbreak. Instead, we would like to detect groups with specific characteristics that have a recent pattern of illness that is anomalous relative to historical patterns. We propose using an anomaly detection algorithm that would characterize each anomalous pattern with a rule. The significance of each rule would be carefully evaluated using the Fisher exact test and a randomization test. In this study, we compared our algorithm with a standard detection algorithm by measuring the number of false positives and the timeliness of detection. Simulated data, produced by a simulator that creates the effects of an epidemic on a city, were used for evaluation. The results indicate that our algorithm has significantly better detection times for common significance thresholds while having a slightly higher false positive rate.
Algorithms↗
Enhanced drop-in syndromic surveillance in New York City following September 11, 2001.
After the 2001 World Trade Center disaster, the New York City Department of Health was under heightened alert for bioterrorist attacks in the city. An emergency department (ED) syndromic surveillance system was implemented with the assistance of the Centers for Disease Control and Prevention to ensure early recognition of an increase or clustering of disease syndromes that might represent a disease outbreak, whether natural or intentional. The surveillance system was based on data collected 7 days a week at area EDs. Data collected were translated into syndromes, entered into an electronic database, and analyzed for aberrations in space and time within 24 hours. From September 14-27, personnel were stationed at 15 EDs on a 24-hour basis (first staffing period); from September 29-October 12, due to resource limitations, personnel were stationed at 12 EDs on an 18-hour basis (second staffing period). A standardized form was used to obtain demographic information and classify each patient visit into 12 syndrome categories. Seven of these represented early manifestations of bioterrorist agents. Data transfer and analysis for time and space clustering (alarms) by syndrome and age occurred daily. Retrospective analyses examined syndrome trends, differences in reporting between staffing periods, and the staff's experience during the project. A total of 67,536 reports were received. The system captured 83.9% of patient visits during the first staffing period, and 60.8% during the second staffing period (P < 0.01). Five syndromes each accounted for more than 1% of visits: trauma, asthma, gastrointestinal illness, upper/lower respiratory infection with fever, and anxiety. Citywide temporal alarms occurred eight times for three of the major bioterrorism-related syndromes. Spatial clustering alarms occurred 16 times by hospital location and 9 times by ZIP code for the same three syndromes. No outbreaks were detected. On-site staffing to facilitate data collection and entry, supported by daily analysis of ED visits, is a feasible short-term approach to syndromic surveillance during high-profile events. The resources required to operate such a system, however, cannot be sustained for the long term. This system was changed to an electronic-based ED syndromic system using triage log data that remains in operation.
Bioterrorism↗
The bioterrorism preparedness and response Early Aberration Reporting System (EARS).
Data from public health surveillance systems can provide meaningful measures of population risks for disease, disability, and death. Analysis and evaluation of these surveillance data help public health practitioners react to important health events in a timely manner both locally and nationally. Aberration detection methods allow the rapid assessment of changes in frequencies and rates of different health outcomes and the characterization of unusual trends or clusters. The Early Aberration Reporting System (EARS) of the Centers for Disease Control and Prevention allows the analysis of public health surveillance data using available aberration detection methods. The primary purpose of EARS is to provide national, state, and local health departments with several alternative aberration detection methods. EARS helps assist local and state health officials to focus limited resources on appropriate activities during epidemiological investigations of important public health events. Finally, EARS allows end users to select validated aberration detection methods and modify sensitivity and specificity thresholds to values considered to be of public health importance by local and state health departments.
Bioterrorism↗
Syndromic surveillance using automated collection of computerized discharge diagnoses.
The Syndromic Surveillance Information Collection (SSIC) system aims to facilitate early detection of bioterrorism attacks (with such agents as anthrax, brucellosis, plague, Q fever, tularemia, smallpox, viral encephalitides, hemorrhagic fever, botulism toxins, staphylococcal enterotoxin B, etc.) and early detection of naturally occurring disease outbreaks, including large foodborne disease outbreaks, emerging infections, and pandemic influenza. This is accomplished using automated data collection of visit-level discharge diagnoses from heterogeneous clinical information systems, integrating those data into a common XML (Extensible Markup Language) form, and monitoring the results to detect unusual patterns of illness in the population. The system, operational since January 2001, collects, integrates, and displays data from three emergency department and urgent care (ED/UC) departments and nine primary care clinics by automatically mining data from the information systems of those facilities. With continued development, this system will constitute the foundation of a population-based surveillance system that will facilitate targeted investigation of clinical syndromes under surveillance and allow early detection of unusual clusters of illness compatible with bioterrorism or disease outbreaks.
Bioterrorism↗
Investigation of disease outbreaks detected by "syndromic" surveillance systems.
Syndromic surveillance systems can detect potential disease outbreaks quickly and can provide useful tools to assist in outbreak investigation. The steps used to investigate diseases detected through these newer methods are not that different from traditional investigative measures, but the differences and limitations of the systems must be understood. With syndromic surveillance systems, there is often readily available electronic demographic information that can help define the epidemic and direct disease control measures. The diagnosis needs to be confirmed as quickly as possible, however, as specific diagnostic information will be missing with early detection from nonspecific data. It is also important not to disregard smaller, nonsevere rises in disease incidence as they might be a harbinger of a worsening outbreak. The rapidity of most syndromic surveillance systems also requires an equally rapid response, and planning must be done to prioritize alert categories and the response sequence to best utilize the information available in these new systems.
Bioterrorism↗
Epidemiological response to syndromic surveillance signals.
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Bioterrorism↗
Building capacity for risk factor surveillance in developing countries: a new approach.
The need to create surveillance systems that go beyond data release and generate useful, relevant and accessible information has been widely recognized. To reach this goal the design and implementation of surveillance systems should consider not only technical issues but aspects that guarantee their sustainability and utility and more important, the utilization of surveillance data for resource allocation and planning of health programs and interventions. Until now key issues have been neglected, such as political will, community involvement, decision-making processes and accountability in surveillance outcomes. For many years we have faced the same problems, all within an epidemiological mosaic where infectious and communicable diseases coexist, with limited capacity to conduct surveillance, low priority given by decision-makers, lack of resources, scarce utilization of information, competing priority between chronic, infectious diseases and risk factors surveillance. Technical, management and political approaches involving new partnerships, new ways to involve different stakeholders in the process, new methods and tools, ways to overcome resource restrictions and improve surveillance effectiveness, have to be achieved. An alternative approach has been suggested to meet the above problems and to make surveillance socially responsible; relevant and effective, not only for reporting, but for its contribution to produce the needed health changes and sustain these outcomes. The vision, strategies, methods, tools and results of a community-based surveillance system are presented. Three aspects are addressed, the context in which the surveillance is applied; the theory supporting behavioural risk factor surveillance; the perspectives, goals, solutions and lessons learned from previous experience.
Child↗
A surveillance information system as a management tool: a report from Papua New Guinea.
To have a very good surveillance system, it is paramount important to have a functional health information system that could be easily used for monitoring and investigation of disease outbreaks. In Papua New Guinea (PNG) a national health information system was developed, trailed and implemented nationwide. Furthermore to have the system working linked to it must be the local health system for sustainability and control. A public health manual for disease surveillance in PNG was developed and is now being used for surveillance. This paper describes how the health information system, particularly surveillance system was developed and implemented on the national scale, how it was integrated with other management information systems and how information has been used to support management decision-making and informed policy decision. It will highlight some of the hurdles that it has encountered while trying to implement the system. PNG has one of the best national health information system as compared to many developing countries but limited information generated from the system. There was also less feedback from all levels of the health sector. We need to improve surveillance on the basic principles of integration, focus, and sharing of work. There must be an appropriate and timely response and feedback. We need to improve on the current system rather than building a new one.
Decision Making, Computer-Assisted↗
[The new indicator set for health reporting activities in the German States].
In May 2003, the third revised version of the indicator set for health reporting activities was confirmed by the health ministries of all German States (Bundesländer). Modeled on the restructured indicator set which has been annotated with meta-data descriptions, most Bundesländer have now started to collect data for their specific health reporting activities. Thanks to the support provided by national data holders and the Federal Statistical Office, it has been possible to further enlarge the database and for the first time also ensure access via the Federal Statistical Office. In this contribution the authors describe the methodological and statistical principles of the indicator set. Another aspect is the benefit of the indicator set for the health reporting activities in the German States.
Aged↗
[Survey among local health departments concerning the implementation of the new infectious disease reporting system].
The Infectious Disease Control Act enacted in Germany in January 2001 led to the establishment of a new reporting system for infectious disease. The implementation of this system was evaluated to identify opportunities for further improvement. In a survey of all German local health departments the following criteria were analyzed: resources (staff and technical equipment), information needs (satisfaction with current offers/further training requirements), data analysis (extent of local data analysis/feedback of national data), and acceptability (case definitions/electronic reporting). In local health departments, 11% of the staff were assigned to the infectious disease reporting system. Data were processed mainly by nonmedical staff (78.4%). A computer work-station is available for most staff members. One-third of the local health departments uses the RKI software "SurvNet@rki" for data transmission. All others use commercial software. Experience with the electronic reporting system was rated as very good/good by 47.1% of local health departments, as satisfactory by 44.5%, and as problematic by 8.4%. Most of the local health departments were satisfied with the offers of information provided by RKI (96.4%) and state health departments (83.7%), respectively. However, 49.1% of the local health departments saw a need for further education and training. The implementation of case definitions was supported by 95% of the local health departments, but transmission criteria were criticized. In summary, the new infectious disease reporting system in Germany was successfully implemented. However, the system could be improved through reduction of software problems concerning electronic data processing and transmission, expansion of current offers of in-formation and provision of special staff training programs, and revision of the case definitions concerning clearness and simpler handling.
Communicable Disease Control↗
The Dutch National Atlas of Public Health.
The Dutch National Atlas of Public Health (http://www.zorgatlas.nl) maps the regional distribution of demand and usage of health care, public health status and influencing factors. The Atlas provides answers to locational questions, e. g. 'Where are the highest mortality rates?', 'Where are the longest waiting lists?' and 'Where are hospitals located?' Maps play a pivotal role in the Atlas. Texts, graphics and diagrams support the interpretation of the maps. The information in the Atlas specifically targets policy makers at the Ministry of Health, Welfare and Sport. For them, the Atlas is a tool for problem detection, policy making and policy evaluation. The Atlas is also aimed at all professionals in health care. In practice, also the general public appears to access and use the Atlas. The Atlas is part of the Dutch Public Health Status and Forecasts (PHSF). The PHSF is made by the National Institute of Public Health and the Environment mandated by the Ministry of Health, Welfare and Sport.
Atlases as Topic↗
[Health surveys in Europe. Overview and activities to harmonize the methods and instruments for comparing the data].
In almost every European country health surveys are conducted in order to describe the health status of the population and to use these data for planning health services and preventive activities. In the last 10-15 years the availability and quality of data from population-based health surveys in Europe have greatly improved, particularly in the countries of Central and Eastern Europe. Nevertheless the design, quality of data and the comparability across countries, nations and cultures remain a challenge. Therefore WHO and EU have started various activities to harmonize the methods and instruments in health surveys. These activities are described in this contribution.
Database Management Systems↗