Introduction
Sustainable public health practice requires the input of information that is up-to-date, accurate, and reflecting originality from diverse sources. Since the emergence of computers and information technologies, healthcare practitioners and institutions have been using them for record-keeping, database management, research, and surveillance. Through a knowledgeable and systematic approach to public health practice and the adoption of information technologies, an effective public health information system can be developed. Public health informatics (PHI) is ‘’the organized application of information and computer science and technology to public health practice, research, and learning to enhance and facilitate public health activities’’ (Yasnoff, et al, 2000). PHI is one of the major branches of Biomedical Informatics. Biomedical Informatics refers to “the scientific field that deals with biomedical information, data, and knowledge including their storage, retrieval, and maximum use for problem-solving and decision-making” (Shortliffe & Cimino, P.24). Hence, PHI involves the collection, storage, and analysis of public health data and its application in health surveillance and epidemiology. It is implemented at the federal, state, and local levels in public health agencies. Its application may include collection and storage of birth, bio, and death records, reports on communicable diseases; laboratories test result, infectious disease surveillance information, statistics, and trends, child immunization and screening information, and analysis of biological threats and hospital preparedness for emergencies.
Utilizing PHI in the healthcare field provides unlimited capacity to model healthier societies that reap the benefit of technological integrations in healthcare provision systems. With increased public threats such as bioterrorism and influenza pandemics, the need for better infrastructure for distributing information on the good practices for healthier communities will always increase, calling for advances in PHI systems (Stout & Washko, 2002). In essence, the need for PHI is mainly caused by rapid advancement in information technology, increased strain on the public health system, and changes in health care delivery (Yasnoff, et al, 2000, P.68). Therefore, future PHI programs will be based on the improvement of the earlier public health practices in terms of their quality, effectiveness, and efficiency.
PHI is oriented to the achievement of specific tasks such as “conceptualization, design, development, deployment, refinement, maintenance and evaluation of communication, surveillance, and information systems relevant to public health” (Yasnoff, et al, 2000, P.68). Thus, it involves the input of knowledge from various disciplines that form part of public health. Distinguishing feature of public health informatics from other health informatics includes, that it focuses on the health of the community rather than that of the individual patient, it focuses on prevention rather than diagnosis and treatment and it exists in a governmental context (Shortliffe & Cimino, P.538). Studies involving PHI mainly focus on the prevention of disease and injury to populations rather than on the intervention after their incidences. These studies are not bound to clinical setup only, but they are also involved in the monitoring of the environment for health risks.
Based on its distinguishing features, the following are the basic defining and guiding principles of PHI: first, it primarily focuses on the application of information technology that promotes the health of populations in contrast to that of specific individuals. Secondly, the application of technology should be “to prevent disease and injury by altering the conditions or the surroundings that put populations of individuals at risk” (Yasnoff, et al, 2000).
Additionally, it should put into consideration the need for prevention at all vulnerable points in the causal chains leading to disease, injury, or disability. Lastly, it should reflect “the governmental context within which the public health is practiced” (Yasnoff, et al, 2000). Governmental context is because either public health operates directly or indirectly through government agencies that must adhere to public accountability standards, policy, and other public observances.
PHI is a quite broad field involving areas such as computer-based maintenance of patient records (CPR), monitoring, and evaluation of environmental conditions about health risks, epidemiology, and biosurveillance. Among the primary functions of PHI is the function of assessment that largely involves public health surveillance. Surveillance in public health refers to the continuing collection, analysis, interpretation, and dissemination of data on health conditions and health threats (Shortliffe & Cimino, P. 540). In the continuing part of this paper biosurveillance for human health will be explored within the context of PHI, technologies used to enhance biosurveillance will also be explored in depth especially on their role in biosurveillance, and the challenges encountered in implementing PHI and biosurveillance.
Biosurveillance
Biosurveillance is defined as the “process of active data gathering with appropriate analysis and interpretation of biosphere data that might relate to disease activity and threats to human or animal health; including determining whether they are infectious, toxic, metabolic, or otherwise regardless of whether they are intentional or of natural origin, to achieve early warning of health threats, early detection of health events, and overall situational awareness of disease activity” (HSPD-21, 2010). Thus, through the incorporation of PHI tools, biosurveillance is aimed at early prediction of threats and hazards, and detection and evaluation of health threats early enough to prevent or reduce severe health effects. Biosurveillance thus is a new area of public health information that readily utilizes a variety of health data and information sources to facilitate planned and accurate situation sensitization of population health.
Biosurveillance requires integrating and proper management of health-related information using a variety of information systems in monitoring and analysis of health threats. Further, it requires not only the integration of human health information but also the integration of information relating to animals, the environment, and plants when they are vital to human health. Incapacity building for a successful biosurveillance unit, the following factors are very essential: first, availability of quality data and information; secondly, the input of informed human judgment and a competent workforce. In addition, a collaboration between partners and stakeholders in the public health sector and governments units is important. Lastly, the adoption of a wider communication strategy that can enable faster information retrieval and understanding of that information among the partners must be embraced. All these are factors are integrated and achieved through case detection, cluster detection, integration of data and information sources, signal validation, event characterization, notification and communication, and quality control (CDC, 2010).
Biosurveillance focuses mainly on situation awareness to populations’ health will remaining relevant to time, space, and specificity of the health events. Hence biosurveillance is different from traditional public health surveillance in several ways: First, though traditional public health surveillance leads to situation awareness it lacks sufficient information needed for situation awareness across the phases of an event (CDC, 2010). Moreover, biosurveillance can provide preliminary information that is reflective of the health conditions such as syndromes and laboratory test orders, which is a departure from traditional public health surveillance that concentrates on cases once they occur. Finally, biosurveillance also involves ‘collection of related information about animals, environment, and plants that are recorded in quantitative or qualitative form while traditional public health surveillance focuses on case-based surveillance that relies “on individuals diagnosed with or suspected of having a disease, injury, or an exposure of public health importance” (CDC, 2010). Biosurveillance is enabled by various information and science technologies and in the next part of the paper; some of these technologies will be explored about biosurveillance.
Internet and Biosurveillance
The Internet has completely transformed the face of biosurveillance by providing a network platform through which people and biosurveillance systems all over the world can communicate and share data. Modern biosurveillance systems such as real-time outbreak and disease surveillance (RODS), web-based disease reporting systems, ESSENCE, and BioSense are only possible through the internet (Wagner, Moore & Aryel, 2006, P.375). The Internet has enabled the fast setup of biosurveillance systems that reflect a global perspective.
Within the biosurveillance context, the internet refers to the physical internet and the software programs that operate it. The physical internet is the global interconnection of computers that communicate with each other. Its components include cables, optical fiber, satellites, routers, and protocols. Protocols are computer languages that enable computers on the internet to communicate and the most widely used include IP and TCP. Internet protocol (IP) determines the standard format through which the data is transmitted across the internet. The transmission control protocol (TCP) determines the standards for complex communications between the machines by specifying how data packets are broken at one end and how they are reassembled at the other end to complete the communication.
The software programs that run the internet include applications such as web servers, search engines, email applications, and file transfer applications. The World Wide Web (web) enables sharing of research information globally through hyperlinked information systems. The web contains hypertext-based documents (web pages) that link other documents or information systems through HTML and HTTP. Thus by selecting a link one can access additional information about the highlighted topic. The web also uses URLs (uniform resource locators) as an address system for locating resources on the internet. Thus, the web is ‘’a compilation of interlinked documents and resources that are linked by hyperlinks and URLs’’ (Wagner, Moore & Aryel, 2006, P.377). The Internet Engineering Task Force (IETF) is charged with the responsibility of the architectural design of the internet software systems (IETF, 2011). Web browser software such as Mozilla Firefox, Google, Internet Explorer, and Opera enables internet users to move from one page to another through the hyperlinks embedded in the documents. These technologies enable the internet to lay the grounds for biosurveillance systems.
One of the major roles that the internet plays in biosurveillance systems is enhancing communication among the partners and stakeholders involved in biosurveillance. The Internet enables individuals involved in biosurveillance to exchange data, emails, images, audio-visual information relating to health events. The Internet has evolved much in being able to support both asynchronous and synchronous communication such as conference calls, video conferencing, telemedicine, and remote diagnosis all of which are powerful technological tools for facilitating biosurveillance (Wagner, Moore & Aryel, 2006, P.375). The Internet also provides a platform for network groups to share information, the host informed discussion and conversations enabling individuals to communicate their inputs in biosurveillance systems. Thus, apart from providing communication avenues internet also has the much-aided establishment of biosurveillance systems by providing a backbone through which they are based.
The Internet has become a handy resource center for individuals interested in biosurveillance data and information. Currently, the internet is a real-time online library and dictionary for an epidemiologist, infection control practitioners, outbreak investigators, and researchers, where they can easily retrieve journal articles, technical reports, books, videos, and newswire stories that provide them with very reliable and useful information (Wagner, Moore & Aryel, 2006, P.375). For outbreak investigators, all they need is just to use search engines to find the location of an outbreak or create interest concerning an outbreak incidence. Additionally, the enormous volume of information found on the internet is a very resourceful source of data and information for biosurveillance. For example, a disease outbreak news post on the internet is a vital data input for biosurveillance systems such as Global Public Health Intelligence Network (GPHIN). Therefore, through powerful internet tools, the individuals involved in biosurveillance can analyze the vast amount of data collection on the internet, filter, and come up with reliable biosurveillance inputs. In essence, the internet has become the most powerful way of accessing, conducting, and enhancing public health education.
Studies have further revealed that using the internet for electronic reporting in biosurveillance of reportable diseases, greatly improves the timeliness of reporting, saves the health care practitioners the workload, and reduces underreporting incidences. Traditional disease surveillance strategies are very prone to underreporting since they rely on communications means such as telephone, mail, or fax that mostly delay communication of confirmatory test results and
notification of the appropriate public health organization (Hoffman, et al, 2003). These strategies are so unreliable to the extent that sometimes severe disease incidences go unreported or there is significant variability of information provided for surveillance since the information provided might be lacking some vital information that forces public health surveillance practitioners to make follow-up calls for additional information.
A clear indicator of these notions is the study undertaken by Hoffman et al (2003) in Kansas City, Missouri on an electronic reporting system for a network of 22 laboratories, with an independent organization acting as a data-clearing house between the reporting laboratories and public health departments. The reports were channeled via a secure internet connection to the Kansas City Health Department and were in tandem with the conventional reporting methods. This study revealed that: first, data is received faster using an electronic reporting system than when using the traditional reporting means; secondly, electronic reporting improved the timeliness of reporting disease incidences; thirdly, electronic reporting achieves greater completeness of data thus saving the follow up for extra information. More so, the data clearinghouse system saves the health practitioners from managing multiple jurisdictional relationships. Lastly, this system greatly reduces underreporting especially for STDs and enteric pathogens (Hoffman, et al, 2003).
Event-based Biosurveillance
The Internet has enabled advancements in the field of biosurveillance leading to a more recent field of event-based biosurveillance. Event-based biosurveillance incorporates various data sources mainly from the internet to come up with reliable information on infectious disease incidences. This approach complements the traditional public health surveillance in situational awareness and early warning of reportable disease incidences. Event-based biosurveillance is defined as ‘’a new scientific discipline that uses information from the internet whereby diverse streams of data are characterized prospectively to provide information on events affecting human health’’ (Walters, et al, 2009).
A departure from earlier surveillance systems, the event-based surveillance systems normally uses unstructured data from media and other sources to check warnings that may infer emerging threats, enabling biosurveillance to contribute to global early warnings of infectious disease and related threats such as chemical, radiological, biological and nuclear (CBRN) agents (Walters, et al, 2009). To enhance event-based surveillance, researchers have created prototype internet-based systems that monitor and trail the outbreaks of infectious diseases and related threats, and analysis the level to which biosurveillance is capable of providing early warning of outbreaks (Hartley et al, 2009). These prototype internet-based biosurveillance systems have been made possible through strategic global partnerships aimed at improving health alertness and response to related threats. Some of the major partnership includes the Global Health Security Initiative (GHSI) and Global Health Security Action Group (GHSAG). The prototype internet-based biosurveillance systems enabled by the global partnerships include systems such as Argus, BioCaster, Global Public Health Intelligence Network (GPHIN), HealthMap, Health Emergency Disease Information System (HEDIS), Medical Information System (MedISys), Program for Monitoring Emerging Diseases (ProMED) and Pattern-based Understanding and Learning System (PULS), all of which are event-based (Hartley et al, 2009). These systems share similarities and variations and are created for varied agendas and approaches. Thus, the future of event-based biosurveillance is more oriented towards integrating these systems to produce an enriched biosurveillance resource.
The challenges encountered in implementing PHI and biosurveillance
First, the major challenge lies in the fact that biosurveillance is accomplished through distributed responsibility; timely sharing of multi-sector and all-hazards information by the stakeholders from the local level through to national and then to global level (CDC, 2010). The responsibility for public health is distributed among all levels of government, practitioner avenues, and study fields, thus pulling all these levels together to come up with concise and reliable information is quite difficult to achieve. Secondly, the establishment of new surveillance systems is mainly based on striking a balance between the new developments and the existing applications. Thus, things like funding and approval for the development of new biosurveillance systems may not be easily available since the new initiative has to be compared with systems that have proven their worth.
Thirdly, ‘’public health threats are mainly multifaceted, hence in their evaluation, they require integration of different types and forms of information in crafting the situation awareness capacity’’ (CDC, 2011). The various data required are gathered by different means and therefore they will require a dynamic approach in adopting them to a given biosurveillance system. Fourthly, interruptions in communication networks may lead to delays and variability that may hinder the surveillance system from detecting or responding to infectious disease incidence or related threats. Additionally, standards for evaluating public health surveillance systems may not be completely suitable for evaluating biosurveillance systems thus uniform standards need to be developed (Hartley et al, 2009). Lastly, other challenges include interoperability, interface customizability, scalability, event traceability, and integration geospatial visualization, event mapping, modeling, and trending tools that are necessary for establishing guidelines for data interpretation and analysis (Hartley et al, 2009). By overcoming and reducing some of these challenges, the capacity for PHI and biosurveillance will improve tremendously and their complementarities will be greatly transformed positively.
References
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