Infodemiology was defined by Gunther Eysenbach in the early 2000s as information epidemiology. [1] It is an area of science research focused on scanning the internet for user-contributed health-related content, with the ultimate goal of improving public health. [1] [2] [3] Later, it is also defined as the science of mitigating public health problems resulting from an infodemic. [4]
Eysenbach first used the term in the context of measuring and predicting the quality of health information on the Web (i.e., measuring the "supply" side of information). [1] He later included in his definition methods and techniques which are designed to automatically measure and track health information "demand" (e.g., by analyzing search queries) as well as "supply" (e.g., by analyzing postings on webpages, in blogs, and news articles, for example through GPHIN) on the Internet with the overarching goal of informing public health policy and practice. In 2013, the Infovigil Project was launched in an effort to bring the research community together to help realize this goal. It is funded by the Canadian Institutes of Health Research. [5]
Eysenbach demonstrated his point by showing a correlation between flu-related searches on Google (demand data) and flu-incidence data. [2] The method is shown to be better and more timely (i.e., can predict public health events earlier) than traditional syndromic surveillance methods such as reports by sentinel physicians.[ citation needed ]
Researchers have applied an infodemiological approach to studying the spread of HIV/AIDS, [6] SARS, [7] especially SARS-CoV-2 [ citation needed ] during the COVID-19 pandemic, and influenza, [8] [9] [10] vaccination uptake, [11] [12] antibiotics consumption, [13] the incidence of multiple sclerosis, [14] [15] patterns of alcohol consumption, [16] the efficacy of using the social web for personalization of health treatment, [17] [18] the contexts of status epilepticus patients, [19] [20] factors of Abdominal pain and its impact on quality of life [21] and the effectiveness of the Great American Smokeout anti-smoking awareness event. [22] Applications outside the field of health care include urban planning [23] and the study of economic trends and voter preferences. [24] Infodemiology plays a role in understanding how people seek out health-related information online and how this impacts public health outcomes. As technologies that people use continues to advance, it will becomes relevant for researchers to utilize infodemiological approaches in order to stay informed about emerging health trends in the digital world. One of the main goals of infodemiology is to provide real-time information about public health trends and behaviors. By analyzing user-generated content on the internet, researchers can gain insights into people's attitudes towards health issues and track the spread of diseases or outbreaks. This information can then be used to inform public health policies and interventions. There are also challenges associated with infodemiology. One major concern is the reliability and accuracy of online information. With the rise of fake news and misinformation on the internet, it is important for researchers to carefully evaluate the data sources. [25] [26] [27]
Infodemiology utilizes a variety of methods and techniques, including data mining, natural language processing, machine learning, and social network analysis. It also involves collaboration between different disciplines such as public health, computer science, sociology, and psychology. [25] [26] [27]
Health On the Net Foundation (HON) was a Swiss not-for-profit organization based in Geneva which promoted a code of conduct for websites providing health information and offered certificates to those in compliance.
eHealth describes healthcare services which are supported by digital processes, communication or technology such as electronic prescribing, Telehealth, or Electronic Health Records (EHRs). The use of electronic processes in healthcare dated back to at least the 1990s. Usage of the term varies as it covers not just "Internet medicine" as it was conceived during that time, but also "virtually everything related to computers and medicine". A study in 2005 found 51 unique definitions. Some argue that it is interchangeable with health informatics with a broad definition covering electronic/digital processes in health while others use it in the narrower sense of healthcare practice using the Internet. It can also include health applications and links on mobile phones, referred to as mHealth or m-Health. Key components of eHealth include electronic health records (EHRs), telemedicine, health information exchange, mobile health applications, wearable devices, and online health information. These technologies enable healthcare providers, patients, and other stakeholders to access, manage, and exchange health information more effectively, leading to improved communication, decision-making, and overall healthcare outcomes.
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 track emerging health-related issues at an early stage and find active solutions in a timely manner. Surveillance systems are generally called upon to provide information regarding when and where health problems are occurring and who is affected.
WebCite is an intermittently available archive site, originally designed to digitally preserve scientific and educationally important material on the web by taking snapshots of Internet contents as they existed at the time when a blogger or a scholar cited or quoted from it. The preservation service enabled verifiability of claims supported by the cited sources even when the original web pages are being revised, removed, or disappear for other reasons, an effect known as link rot.
An e-patient is a health consumer who participates fully in their own medical care, primarily by gathering information about medical conditions that impact them and their families, using the Internet and other digital tools. The term encompasses those who seek guidance for their own ailments, and the friends and family members who research on their behalf. E-patients report two effects of their health research: "better health information and services, and different, but not always better, relationships with their doctors."
Gunther Eysenbach is a German-Canadian researcher on healthcare, especially health policy, eHealth, and consumer health informatics.
The Journal of Medical Internet Research is a peer-reviewed open-access medical journal established in 1999 covering eHealth and "healthcare in the Internet age". The editors-in-chief are Gunther Eysenbach and Rita Kukafka. The publisher is JMIR Publications.
Online health communities are online social networks related to health. They primarily provide a means for patients and their families to learn about illnesses, to seek and offer social support, and to connect with others in similar circumstances. These online groups can be composed of individuals with illnesses, groups of medical professionals with shared interests, non-professional caregivers and family of patients, or a combination. The term "online health community" is primarily academic jargon.
"Health 2.0" is a term introduced in the mid-2000s, as the subset of health care technologies mirroring the wider Web 2.0 movement. It has been defined variously as including social media, user-generated content, and cloud-based and mobile technologies. Some Health 2.0 proponents see these technologies as empowering patients to have greater control over their own health care and diminishing medical paternalism. Critics of the technologies have expressed concerns about possible misinformation and violations of patient privacy.
mHealth is an abbreviation for mobile health, a term used for the practice of medicine and public health supported by mobile devices. The term is most commonly used in reference to using mobile communication devices, such as mobile phones, tablet computers and personal digital assistants (PDAs), and wearable devices such as smart watches, for health services, information, and data collection. The mHealth field has emerged as a sub-segment of eHealth, the use of information and communication technology (ICT), such as computers, mobile phones, communications satellite, patient monitors, etc., for health services and information. mHealth applications include the use of mobile devices in collecting community and clinical health data, delivery/sharing of healthcare information for practitioners, researchers and patients, real-time monitoring of patient vital signs, the direct provision of care as well as training and collaboration of health workers.
Health 3.0 is a health-related extension of the concept of Web 3.0 whereby the users' interface with the data and information available on the web is personalized to optimize their experience. This is based on the concept of the Semantic Web, wherein websites' data is accessible for sorting in order to tailor the presentation of information based on user preferences. Health 3.0 will use such data access to enable individuals to better retrieve and contribute to personalized health-related information within networked electronic health records, and social networking resources.
Infoveillance is a type of syndromic surveillance that specifically utilizes information found online. The term, along with the term infodemiology, was coined by Gunther Eysenbach to describe research that uses online information to gather information about human behavior.
The Wikipedia online encyclopedia has, since the late 2000s, served as a popular source for health information for both laypersons and, in many cases, health care practitioners. Health-related articles on Wikipedia are popularly accessed as results from search engines, which frequently deliver links to Wikipedia articles. Independent assessments have been made of the number and demographics of people who seek health information on Wikipedia, the scope of health information on Wikipedia, and the quality and reliability of the information on Wikipedia.
Health information on the Internet refers to all health-related information communicated through or available on the Internet.
Health Web Science (HWS) is a sub-discipline of Web Science that examines the interplay between health sciences, health and well-being, and the World Wide Web. It assumes that each domain influences the others. HWS thus complements and overlaps with Medicine 2.0. Research has uncovered emergent properties that arise as individuals interact with each other, with healthcare providers and with the Web itself.
Digital medicine refers to the application of advanced digital technologies, such as artificial intelligence, machine learning, and big data analytics, to improve patient outcomes and healthcare delivery. It involves the integration of technology and medicine to facilitate the creation, storage, analysis, and dissemination of health information, with the aim of enhancing clinical decision-making, improving patient care, and reducing costs.
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 has 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.
Participatory surveillance is community-based monitoring of other individuals. This term can be applied to both digital media studies and ecological field studies. In the realm of media studies, it refers to how users surveil each other using the internet. Either through the use of social media, search engines, and other web-based methods of tracking, an individual has the power to find information both freely or non freely given about the individual being searched. Issues of privacy emerge within this sphere of participatory surveillance, predominantly focused on how much information is available on the web that an individual does not consent to. More so, disease outbreak researchers can study social-media based patterns to decrease the time it takes to detect an outbreak, an emerging field of study called infodemiology. Within the realm of ecological fieldwork, participatory surveillance is used as an overarching term for the method in which indigenous and rural communities are used to gain greater accessibility to causes of disease outbreak. By using these communities, disease outbreak can be spotted earlier than through traditional means or healthcare institutions.
An infodemic is a rapid and far-reaching spread of both accurate and inaccurate information about certain issues. The word is a portmanteau of information and epidemic and is used as a metaphor to describe how misinformation and disinformation can spread like a virus from person to person and affect people like a disease. This term, originally coined in 2003 by David Rothkopf, rose to prominence in 2020 during the COVID-19 pandemic.