Public Health

In the U.S., federal programs are accelerating the meaningful use of electronic health record (EHR) technology and encouraging greater standardization in how governmental public health agencies (PHAs) establish surveillance data partnerships with healthcare providers. To qualify for the benefits of these federal programs (a.k.a., Meaningful Use), healthcare professionals and hospitals must determine: 1) Whether their jurisdictional PHA collects health data for immunization or cancer registries, reportable diseases, and/or syndromic surveillance; and 2) If the PHA does collect this data, then they must register for data on-boarding with the PHA and actively work with them to establish on-going data exchange. These requirements are predicated on participating state and local PHAs either establishing new or expanding the capacity of their existing public health data reporting services. To assist state and local PHAs in this effort, the U.S. Centers for Disease Control and Prevention (CDC) facilitates a national task force, known as the Stage 2 MU Public Health Reporting Requirements Task Force, which has recommended guidelines and clarified requirements for these new processes.

Objective

To exchange lessons learned and refine national guidelines for public health agencies to declare Meaningful Use readiness, register eligible professionals and hospitals for the public health meaningful use objectives, on-board data providers, and perform "on-going" data submission.

A new TB case can be classified as: 1) a source case for transmission leading to other, secondary active TB cases; 2) a secondary case, resulting from recent transmission; or 3) an isolated case, uninvolved in recent transmission (i.e. neither source nor recipient). Source and secondary cases require more intense intervention due to their involvement in a chain of transmission; thus, accurate and rapid classification of new patients should help public health personnel to effectively prioritize control activities. However, currently accepted method for the classification, DNA fingerprint analysis, takes many weeks to produce the results; therefore, public health personnel often solely rely on their intuition to identify the case who is most likely to be involved in transmission. Various clinical and socio-demographic features are known to be associated with TB transmission. By using these readily available data at the time of diagnosis, it is possible to rapidly estimate the probabilities of the case being source, secondary, and isolated.

Objective

To develop and validate a prediction model which estimates the probability of a newly diagnosed tuberculosis (TB) case being involved in ongoing chain of transmission, based on the case's clinical and socio-demographic attributes available at the time of diagnosis.

Emergency management during a disaster entails innumerable challenges. Each disaster uniquely shapes the types and timing of information needed both to manage the disaster and to measure the impact on available resources, the environment, and community systems. Traditional public health surveillance methods typically preclude providing a real-time, comprehensive estimate of public health impacts related to the disaster while the disaster is unfolding. Traditional methods can also be resource intensive, costly, require active cooperation of medical systems involved in a disaster response, and are often conducted post-disaster.

Syndromic surveillance of emergency department chief complaints and over-the-counter medication sales was reinstituted in the Austin area in the fall of 2010. In 2011, the Austin area was hit with three natural disasters: a winter ice storm; a summer of extreme heat/extended drought; and a week of significant wildfires. Each disaster varied greatly in type, size, intensity, and duration. The Austin/Travis County Health and Human Services Department, in partnership with Austin/Travis County EMS, was able for the first time to provide near-real time data to emergency managers on the potential health impact during each of the 2011 disasters using the syndromic and EMS electronic data systems. The data were used to provide situational awareness and guide selected response actions during the course of the disaster, as well as, document potential areas for future mitigation efforts.

Objective

Using case studies of three natural disasters that occurred in the Austin, Texas Metro area in 2011, demonstrate the role syndromic surveillance and emergency medical services data played during the response to each different type of disaster.

There is national recognition of the need for cross-programmatic data and system coordination and integration for surveillance, prevention, response, and control implementation. To accomplish this public health must develop an informatics competency and create an achievable roadmap, supported by performance measures, for the future. Within the New York State Department of Health, Office of Public Health (OPH), a cross-organizational and cross-functional Public Health Information Management Workgroup (PHIM-WG) was formed to align public health information and technology goals, objectives, strategies, and resources across OPH. In June 2011, the OPH Performance Management Initiative, funded by the Centers for Disease Control and Prevention, offered strategic planning workshops to PHIM-WG.

Objective 

To develop strategic objectives necessary to optimize the collection, integration, and use of information across public health programs and internal and external partners for improving the overall health and safety of people and their communities.

With an estimated 500 million people infected each year, dengue ranks as one of the most significant mosquito-borne viral human diseases, and one of the most rapidly emerging vectorborne diseases. A variety of obstacles including bureaucracy and lack of resources have interfered with timely detection and reporting of dengue cases in many endemic countries. Surveillance efforts have turned to modern data sources, such as Internet search queries, which have been shown to be effective for monitoring influenza-like illnesses. However, few have evaluated the utility of web search query data for other diseases, especially those of high morbidity and mortality or where a vaccine may not exist.

Objective

We aimed to assess whether web search queries are a viable data source for the early detection and monitoring of dengue epidemics.

Description: The Centers for Disease Control and Prevention (CDC) works to save lives and protect people during major public health events. In an effort to support these processes, CDC established the Countermeasure Tracking Systems (CTS), which is maintained within the Division of Informatics Solutions and Operations, in the Public Health Informatics and Technical Program Office. CTS consists of four system components which interoperate to improve communications and event response efficiency while still functioning independently, recognizing the unique requirements and use cases for each system. Collectively, the data consolidated from these systems can show population coverage, numbers of untreated individuals, drug and equipment shortages, need for resupply and more. The Web-based applications are deployed centrally at CDC and use the CDC's secure data access method for security.

The first of these components is the Inventory Management and Tracking System (IMATS), currently under development. IMATS provides state and local public health providers with a tool to track medical and non-medical countermeasure inventory and supplies during daily operations or an event. The solution tracks quantities of inventory, monitors reorder thresholds, and facilitates warehouse operations including receiving, staging, and storing of inventory.

The Communications Portal is a web based content management system in development which consolidates important event response details into one place and will provide timely and adequate information to states and other jurisdictions. This system is complementary to the IMATS as it manages communications related to, but not limited to, Emergency Use Authorization, Investigational New Drug and recall notices.

Objective

To describe the CDC CTS, and the impact of its four closely related informatics components toward enhancing federal, state, and local public health capacity to track and manage medicine and other medical or non-medical supplies during daily operations and all hazards public health events.

In July 2006, an important heat wave occurred in France, and generated alarm of all the public health services. In Gironde, a department in region Aquitaine, the level of "warning and actions" of the Heat Health Watch Warning System, based on an analysis of weather-mortality relationship, was activated from the 16th and the 27th of July, when the limits of biometeorological indicators were reached [1].

Objective

To assess health impact of heat wave occurred in July 2006 through data from emergency activity and mortality from syndromic surveillance systems in Gironde, a department in south-western France.

One of the significant challenges that multi-user biosurveillance systems have is alarm management. Currently deployed syndromic surveillance systems [1–3] have a single user interface. However, different users have different objectives; the alarms that are important for one category of user are irrelevant to the objectives of another category of user. For example, a physician wants to identify disease on an individual-patient level, a county health authority is interested in identifying disease outbreak as early as possible within his local region, while an epidemiologist at the national level is interested in global situational awareness. The objective of a multi-agent decision support system is not only to recognize patterns of epidemiologically significant events but also to indicate their relevance to particular user groups’ objectives. Thus, instead of simply providing alerts of anomaly detections, the system architecture needs to provide analyzed information supporting multiple users’ decisions.

In Sri Lanka, a major drawback in injury prevention is the lack of complete, accurate and timely data. To fulfill this data need, in 2006, Sri Lanka's Trauma Secretariat piloted an Injury Surveillance System (ISS) in four hospitals. This comprised of two parts: a paper-based data collection tool (Trauma Surveillance Record or TSR) and its corresponding software application. TSR recorded ICD-10 Chapter XIX codes related to the diagnoses of injuries, but did not record the Chapter XX codes pertaining to external causes of morbidity which provide essential knowledge for injury prevention. The software application was built using proprietary technologies that could lead to increased costs and associated dependencies with vendors. The system was unable to comply with the changing data needs of the Ministry of Health (MoH) without a major retooling. Consequently, in 2011, the MoH made changes in the TSR, but the software application was unable to handle those changes. The ISS was evaluated by three independent teams which recommended discontinuing its use and suggested the development of a new system.

Objective

Designing, developing and piloting a web-based Injury Surveillance System for Sri Lanka.

Air pollution is well documented to cause adverse health effects in the population. Epidemiological/toxicological studies have demonstrated that air pollution is associated with various adverse health outcomes, ranging from mortality to subclinical respiratory symptoms. Classical epidemiological studies of the health effects of air pollution are typically retrospective. In order to assess the effectiveness of any public health messages or interventions in a timely manner there is a need to be able to systematically detect any health effects occurring in real-time. The UK syndromic surveillance systems are coordinated by Public Health England (PHE) and are used to monitor infectious diseases in real-time. This study is the first in the UK to explore whether syndromic surveillance systems can detect public health impacts associated with air pollution events.

Objective: This study examined whether the current UK real-time syndromic surveillance systems can detect public health impacts associated with air pollution events such as fires and ambient air pollution episodes.