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Public health informatics has been defined as the systematic application of information and computer science and technology to public health practice, research, and learning. It is one of the subdomains of health informatics.
Computer science is the study of processes that interact with data and that can be represented as data in the form of programs. It enables the use of algorithms to manipulate, store, and communicate digital information. A computer scientist studies the theory of computation and the practice of designing software systems.
Public health has been defined as "the science and art of preventing disease, prolonging life and promoting human health through organized efforts and informed choices of society, organizations, public and private, communities and individuals". Analyzing the health of a population and the threats it faces is the basis for public health. The public can be as small as a handful of people or as large as a village or an entire city; in the case of a pandemic it may encompass several continents. The concept of health takes into account physical, psychological and social well-being. As such, according to the World Health Organization, it is not merely the absence of disease or infirmity.
Health informatics is information engineering applied to the field of health care, essentially the management and use of patient healthcare information. It is a multidisciplinary field that uses health information technology (HIT) to improve health care via any combination of higher quality, higher efficiency, and new opportunities. The disciplines involved include information science, computer science, social science, behavioral science, management science, and others. The NLM defines health informatics as "the interdisciplinary study of the design, development, adoption and application of IT-based innovations in healthcare services delivery, management and planning". It deals with the resources, devices, and methods required to optimize the acquisition, storage, retrieval, and use of information in health and bio-medicine. Health informatics tools include computers, clinical guidelines, formal medical terminologies, and information and communication systems, among others. It is applied to the areas of nursing, clinical medicine, dentistry, pharmacy, public health, occupational therapy, physical therapy, biomedical research, and alternative medicine, all of which are designed to improve the overall of effectiveness of patient care delivery by ensuring that the data generated is of a high quality.
Public health informatics is defined as the use of computers, clinical guidelines, communication and information systems, which apply to vast majority of public health, related professions, such as nursing, clinical/ hospital care/ public health and medical research.
In developed countries like the United States, public health informatics is practiced by individuals in public health agencies at the federal and state levels and in the larger local health jurisdictions. Additionally, research and training in public health informatics takes place at a variety of academic institutions.
At the federal Centers for Disease Control and Prevention in US states like Atlanta, Georgia, the Public Health Surveillance and Informatics Program Office (PHSIPO) focuses on advancing the state of information science and applies digital information technologies to aid in the detection and management of diseases and syndromes in individuals and populations.
The Centers for Disease Control and Prevention (CDC) is the leading national public health institute of the United States. The CDC is a United States federal agency under the Department of Health and Human Services and is headquartered in Atlanta, Georgia.
The bulk of the work of public health informatics in the United States, as with public health generally, takes place at the state and local level, in the state departments of health and the county or parish departments of health. At a state health department the activities may include: collection and storage of vital statistics (birth and death records); collection of reports of communicable disease cases from doctors, hospitals, and laboratories, used for infectious disease surveillance; display of infectious disease statistics and trends; collection of child immunization and lead screening information; daily collection and analysis of emergency room data to detect early evidence of biological threats; collection of hospital capacity information to allow for planning of responses in case of emergencies. Each of these activities presents its own information processing challenge.
(TODO: describe CDC-provided DOS/desktop-based systems like TIMSS (TB), STDMIS (Sexually transmitted diseases); Epi-Info for epidemiology investigations; and others )
Since the beginning of the World Wide Web, public health agencies with sufficient information technology resources have been transitioning to web-based collection of public health data, and, more recently, to automated messaging of the same information. In the years roughly 2000 to 2005 the Centers for Disease Control and Prevention, under its National Electronic Disease Surveillance System (NEDSS), built and provided free to states a comprehensive web and message-based reporting system called the NEDSS Base System (NBS). Due to the funding being limited and it not being wise to have fiefdom-based systems, only a few states and larger counties have built their own versions of electronic disease surveillance systems, such as Pennsylvania's PA-NEDSS. These do not provide timely full intestate notification services causing an increase in disease rates versus the NEDSS federal product.
Health data is any data "related to health conditions, reproductive outcomes, causes of death, and quality of life" for an individual or population. Health data includes clinical metrics along with environmental, socioeconomic, and behavioral information pertinent to health and wellness. A plurality of health data are collected and used when individuals interact with health care systems. This data, collected by health care providers, typically includes a record of services received, conditions of those services, and clinical outcomes or information concerning those services. Historically, most health data have been sourced from this framework. The advent of eHealth and advances in health information technology, however, have expanded the collection and use of health data—but have also engendered new security, privacy, and ethical concerns. The increasing collection and use of health data by patients is a major component of digital health.
To promote interoperability, the CDC has encouraged the adoption in public health data exchange of several standard vocabularies and messaging formats from the health care world. The most prominent of these are: the Health Level 7 (HL7) standards for health care messaging; the LOINC system for encoding laboratory test and result information; and the Systematized Nomenclature of Medicine (SNOMED) vocabulary of health care concepts.
Since about 2005, the CDC has promoted the idea of the Public Health Information Network to facilitate the transmission of data from various partners in the health care industry and elsewhere (hospitals, clinical and environmental laboratories, doctors' practices, pharmacies) to local health agencies, then to state health agencies, and then to the CDC. At each stage the entity must be capable of receiving the data, storing it, aggregating it appropriately, and transmitting it to the next level. A typical example would be infectious disease data, which hospitals, labs, and doctors are legally required to report to local health agencies; local health agencies must report to their state public health department; and which the states must report in aggregate form to the CDC. Among other uses, the CDC publishes the Morbidity and Mortality Weekly Report (MMWR) based on these data acquired systematically from across the United States.
Major issues in the collection of public health data are: awareness of the need to report data; lack of resources of either the reporter or collector; lack of interoperability of data interchange formats, which can be at the purely syntactic or at the semantic level; variation in reporting requirements across the states, territories, and localities.
Public health informatics can be thought or divided into three categories.
The first category is to discover and study models of complex systems, such as disease transmission. This can be done through different types of data collections, such as hospital surveys, or electronic surveys submitted to the organization (such as the CDC). Transmission rates or disease incidence rates/surveillance can be obtained through government organizations, such as the CDC, or global organizations, such as WHO. Not only disease transmission/rates can be looked at. Public health informatics can also delve into people with/without health insurance and the rates at which they go to the doctor. Before the advent of the internet, public health data in the United States, like other healthcare and business data, were collected on paper forms and stored centrally at the relevant public health agency. If the data were to be computerized they required a distinct data entry process, were stored in the various file formats of the day and analyzed by mainframe computers using standard batch processing.
The second category is to find ways to improve the efficiency of different public health systems. This is done through various collections methods, storage of data and how the data is used to improve current health problems. In order to keep everything standardized, vocabulary and word usage needs to be consistent throughout all systems. Finding new ways to link together and share new data with current systems is important to keep everything up to date.
Storage of public health data shares the same data management issues as other industries. And like other industries, the details of how these issues play out are affected by the nature of the data being managed.
Due to the complexity and variability of public health data, like health care data generally, the issue of data modeling presents a particular challenge. While a generation ago flat data sets for statistical analysis were the norm, today's requirements of interoperability and integrated sets of data across the public health enterprise require more sophistication. The relational database is increasingly the norm in public health informatics. Designers and implementers of the many sets of data required for various public health purposes must find a workable balance between very complex and abstract data models such as HL7's Reference Information Model (RIM) or CDC's Public Health Logical Data Model, and simplistic, ad hoc models that untrained public health practitioners come up with and feel capable of working with.
Due to the variability of the incoming data to public health jurisdictions, data quality assurance is also a major issue.
Finally, the last category can be thought as maintaining and enriching current systems and models to adapt to overflow of data and storing/sorting of this new data. This can be as simple as connecting directly to an electronic data collection source, such as health records from the hospital, or can go public information (CDC) about disease rates/transmission. Finding new algorithms that will sort through large quantities of data quickly and effectively is necessary as well.
The need to extract usable public health information from the mass of data available requires the public health informaticist to become familiar with a range of analysis tools, ranging from business intelligence tools to produce routine or ad hoc reports, to sophisticated statistical analysis tools such as DAP/SAS and PSPP/SPSS, to Geographical Information Systems (GIS) to expose the geographical dimension of public health trends.Such analyses usually require methods that appropriately secure the privacy of the health data. One approach is to separate the individually identifiable variables of the data from the rest
There are a few organizations out there that provide useful information for those professionals that want to be more involved in public health informatics. Such as the American Medical Informatics Association (AMIA). AMIA is for professions that are involved in health care, informatics research, biomedical research, including physicians, scientists, researchers, and students. The main goals of AMIA are to move from ‘bench to bedside’, help improve the impact of health innovations and advance the public health informatics field. They hold annual conferences, online classes and webinars, which are free to their members. There is also a career center specific for the biomedical and health informatics community.
Many jobs or fellowships in public health informatics are offered. The CDC (Center for Disease Control) has various fellowship programs, while multiple colleges/companies offer degree programs or training in this field.
For more information on these topics, follow the links below:
Since the late 2000s, data from social media websites such as Twitter and Facebook, as well as search engines such as Google and Bing, have been used extensively in detecting trends in public health.
The National Center for Health Statistics (NCHS) is a principal agency of the U.S. Federal Statistical System which provides statistical information to guide actions and policies to improve the health of the American people.
A cancer registry is a systematic collection of data about cancer and tumor diseases. The data are collected by Cancer Registrars. Cancer Registrars capture a complete summary of patient history, diagnosis, treatment, and status for every cancer patient in the United States, and other countries.
An electronic health record (EHR), or electronic medical record (EMR), is the systematized collection of patient and population electronically-stored health information in a digital format. These records can be shared across different health care settings. Records are shared through network-connected, enterprise-wide information systems or other information networks and exchanges. EHRs may include a range of data, including demographics, medical history, medication and allergies, immunization status, laboratory test results, radiology images, vital signs, personal statistics like age and weight, and billing information.
A personal health record (PHR) is a health record where health data and other information related to the care of a patient is maintained by the patient. This stands in contrast to the more widely used electronic medical record, which is operated by institutions and contains data entered by clinicians to support insurance claims. The intention of a PHR is to provide a complete and accurate summary of an individual's medical history which is accessible online. The health data on a PHR might include patient-reported outcome data, lab results, and data from devices such as wireless electronic weighing scales or from a smartphone.
Public health surveillance is, according to the World Health Organization (WHO), "the continuous, systematic collection, analysis and interpretation of health-related data needed for the planning, implementation, and evaluation of public health practice." Public health surveillance may be used to "serve as an early warning system for impending public health emergencies; document the impact of an intervention, or track progress towards specified goals; and monitor and clarify the epidemiology of health problems, to allow priorities to be set and to inform public health policy and strategies."
Waterborne diseases are conditions caused by pathogenic micro-organisms that are transmitted in water. Disease can be spread while bathing, washing or drinking water, or by eating food exposed to contaminated water. While diarrhea and vomiting are the most commonly reported symptoms of waterborne illness, other symptoms can include skin, ear, respiratory, or eye problems.
Health information management (HIM) is information management applied to health and health care. It is the practice of acquiring, analyzing and protecting digital and traditional medical information vital to providing quality patient care. With the widespread computerization of health records, traditional (paper-based) records are being replaced with electronic health records (EHRs). The tools of health informatics and health information technology are continually improving to bring greater efficiency to information management in the health care sector. Both hospital information systems and Human Resource for Health Information System (HRHIS) are common implementations of HIM.
The Association of Public Health Laboratories (APHL) is a membership organization in the United States representing the laboratories that protect the health and safety of the public. In collaboration with members, APHL advances laboratory systems and practices, and promotes policies that support healthy communities. APHL serves as a liaison between laboratories and federal and international agencies, and ensures that the network of laboratories has current and consistent scientific information in order to be ready for outbreaks and other public health emergencies. Membership consists of local, territorial, county and state public health laboratories; environmental, agricultural and veterinary laboratories; and corporations and individuals with an interest in public health and laboratory science. APHL is a non-profit, 501(c)(3) organization with a history of over fifty years.
The Public Health Information Network (PHIN) is a national initiative, developed by the Centers for Disease Control and Prevention (CDC), for advancing fully capable and interoperable information systems in public health organizations. The initiative involves establishing and implementing a framework for public health information systems.
The ISO/TC 215 is the International Organization for Standardization's (ISO) Technical Committee (TC) on health informatics. TC 215 works on the standardization of Health Information and Communications Technology (ICT), to allow for compatibility and interoperability between independent systems.
Tele-epidemiology is the application of telecommunications to epidemiological research and application, including space-based and internet-based systems.
Workplace health surveillance or occupational health surveillance (U.S.) is the ongoing systematic collection, analysis, and dissemination of exposure and health data on groups of workers. The Joint ILO/WHO Committee on Occupational Health at its 12th Session in 1995 defined an occupational health surveillance system as “a system which includes a functional capacity for data collection, analysis and dissemination linked to occupational health programmes”.
Surveillance for communicable diseases is the main public health surveillance activity in China. Currently, the disease surveillance system in China has three major components:
Health information technology is information technology applied to health and health care. It supports health information management across computerized systems and the secure exchange of health information between consumers, providers, payers, and quality monitors. Based on an often-cited 2008 report on a small series of studies conducted at four sites that provide ambulatory care – three U.S. medical centers and one in the Netherlands – the use of electronic health records (EHRs) was viewed as the most promising tool for improving the overall quality, safety and efficiency of the health delivery system. According to a 2006 report by the Agency for Healthcare Research and Quality, broad and consistent utilization of HIT will:
Health informatics in China is about the Health informatics or Medical informatics or Healthcare information system/technology in China.
The Task Force for Global Health is an international, nonprofit organization that works to improve health of people most in need, primarily in developing countries. Founded in 1984 by global health pioneer Dr. William Foege, The Task Force consists of eight programs focused on neglected tropical diseases, vaccines, field epidemiology, public health informatics, and health workforce development. Those programs include the African Health Workforce Project, the Center for Vaccine Equity, Children Without Worms, International Trachoma Initiative, Mectizan Donation Program, Neglected Tropical Diseases Support Center, Public Health Informatics Institute, and TEPHINET. The Task Force works in partnership with ministries of health and hundreds of organizations, including major pharmaceutical companies that donate billions of dollars annually in essential medicines. Major funders include the Bill & Melinda Gates Foundation, CDC, WHO, Robert Wood Johnson Foundation, de Beaumont Foundation, United States Agency for International Development, Sightsavers, Pfizer, Merck & Co., Johnson & Johnson, and GlaxoSmithKline. The Task Force is affiliated with Emory University, headquartered in Decatur, Georgia, a town in metro Atlanta, and has regional offices in Guatemala and Ethiopia. The Task Force currently supports work in 154 countries.
Fast Healthcare Interoperability Resources is a draft standard describing data formats and elements and an application programming interface (API) for exchanging electronic health records. The standard was created by the Health Level Seven International (HL7) health-care standards organization.
Medical device connectivity is the establishment and maintenance of a connection through which data is transferred between a medical device, such as a patient monitor, and an information system. The term is used interchangeably with biomedical device connectivity or biomedical device integration. By eliminating the need for manual data entry, potential benefits include faster and more frequent data updates, diminished human error, and improved workflow efficiency.
Professor Dipak Kalra is President of the European Institute for Health Records and of the European Institute for Innovation through Health Data. He undertakes international research and standards development, and advises on adoption strategies, relating to Electronic Health Records.
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