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Clinical & Medical informatics glossary & taxonomy
 
Evolving Terminology for Emerging Technologies
Comments? Questions? Revisions? 
Mary Chitty MSLS mchitty@healthtech.com
Last revised January 09, 2020

Clinical Research News reports on innovative technologies from clinical trials to medical informatics. Technology continues to permeate all aspects of clinical trials and the patient experience, and the tools to support these efforts are maturing rapidly. .. news, views, and insights on the vast landscape of innovation between clinical trial management   Areas of regular coverage:  include Electronic data capture, Patient recruitment technologies and practices, Clinical trial informatics including ePRO (patient reported outcomes), clinical trial management software, trial master files, and case report forms, Trial design, Adaptive clinical trials, Contract and clinical research organizations, Regulatory issues, Site Selection, Site Monitoring, Genomics in the clinic, IT to support patient care and patient engagement, Telehealth and telemedicine, Population health and data analytics, Personalized medicine and care delivery, Clinical data mining, Point of Care clinical trials, Healthcare informatics, Clinical trial monitoring and compliance   http://www.clinicalinformaticsnews.com/Editorial-Profile/

Related informatics glossaries include Algorithms & data analysis,   Bioinformatics,   Cheminformatics  Drug discovery informatics   Information management & interpretation,  IT infrastructure  Regulatory  Research 
See also Clinical trials  Molecular Medicine  Molecular Diagnostics  Therapeutic areas Cancer  Cardiovascular CNS & Neurology Immunology Infectious Diseases Inflammation   

AI for Healthcare: Transforming the Industry Landscape 2020 April 21-23 Boston MA Artificial intelligence in the healthcare industry is predicted to save $150 billion annually for the US. As such, AI is being rapidly deployed in many areas of the healthcare landscape. The Inaugural AI for Healthcare track will primarily focus on the providers, attracting CIOs, CTOs, VPs of IT and Informatics along with senior physicians and clinicians from the leading US hospitals who will share their experiences of using AI in clinical care and hospital operations. http://www.bio-itworldexpo.com/ai-healthcare

Bayesian network: Wikipedia  http://en.wikipedia.org/wiki/Bayesian_network 
Bayesian networks:  A quick intro, Karen Sachs, Biomedical Computation Review, Summer 2005 http://www.biomedicalcomputationreview.org/1/1/9.pdf A computational analysis approach, machine learning tool. 

Bayesian statistics: Bayesian statistics is an approach for learning from evidence as it accumulates. In clinical trials, traditional (frequentist) statistical methods may use information from previous studies only at the design stage. Then, at the data analysis stage, the information from these studies is considered as a complement to, but not part of, the formal analysis. In contrast, the Bayesian approach uses Bayes’ Theorem to formally combine prior information with current information on a quantity of interest. The Bayesian idea is to consider the prior information and the trial results as part of a continual data stream, in which inferences are being updated each time new data become available.

Throughout this document we will use the terms “prior distribution”, “prior probabilities”, or simply “prior” to refer to the mathematical entity (the probability distribution) that is used in these Bayesian calculations. The term “prior information” refers to the set of all information that may be used to construct the prior distribution. FDA, CBER, CDHR Guidance for the use of Bayesian Statistics in Medical Device Clinical Trials Feb. 2010 http://www.fda.gov/medicaldevices/deviceregulationandguidance/guidancedocuments/ucm071072.htm#1

biomathematics: The application of mathematics to problems in biology and medicine. An essential tool in fields such as population genetics, cellular neurobiology, comparative genetics, biomedical imaging, pharmacokinetics, and epidemiology. It plays an increasingly vital role in the effort to understand diseases and disorders, and to improve therapies.  Collection Development Manual, National Library of Medicine, US 2004  http://www.nlm.nih.gov/tsd/acquisitions/cdm/subjects14.html Related terms: bioinformatics, computational biology

biomedical informatics:  "the field that is concerned with the optimal use of information, often aided by the use of technology and people, to improve individual health, health care, public health, and biomedical research"¹. William Hersh 2010 , Biomedical Informatics, Ohio State University http://medicine.osu.edu/bmi/Pages/index.aspx
http://en.wikipedia.org/wiki/Biomedical_informatics    Related terms: medical informatics

case definition : Optimal case definition is important in epidemiological research, but can be problematic when no satisfactory gold standard is available. In particular, difficulties arise where the pathology underlying a disorder is unknown or cannot be reliably diagnosed. This problem can be overcome if diagnoses are viewed not necessarily as labels for disease processes, but more generally as a useful method for classifying people for the purpose of preventing or managing illness. With this perspective, the value of a case definition lies in its practical utility in distinguishing groups of people whose illnesses share the same causes or determinants of outcome (including response to treatment). A corollary is that the best-case definition for a disorder may vary according to the purpose for which it is being applied.  Assessing case definitions in the absence of a diagnostic gold standard, D Coggon, C Martyn, KT Palmer, B Evanoff, Intl J Epidemiol 34 (4): 949-952 

CDISC Clinical Data Interchange Standards Consortium: An open, multidisciplinary, non- profit organization committed to the development of industry standards to support the electronic acquisition, exchange, submission and archiving of clinical trials data and metadata for medical and biopharmaceutical product development. http://www.cdisc.org/  

clinical data repositories, shared: Agency for Healthcare Research & Quality http://healthit.ahrq.gov/portal/server.pt?open=514&objID=5554&mode=2&holderDisplayURL=http://prodportallb.ahrq.gov:7087/publis

clinical forecasting: It is clear that late-stage clinical failures account for a large proportion of the expenses. This can be as a result of both the large out-of-pocket investments in Phase III clinical trials and because unsuccessful trials tie up capital resources during their conduct, and potentially also for the time spent during any attempted recovery following regulatory rejection. So, there is an interest in strategies that could halt, as early as possible, the development of drugs that eventually fail. Clinical forecasting in drug development, Asher D. Schachter and Marco F. Ramoni, Nature Reviews Drug Discovery 6, 107-108 (February 2007) | doi:10.1038/nrd2246 http://www.nature.com/nrd/journal/v6/n2/full/nrd2246.html  Narrower term: Bayesian clinical forecasting, Bayesian clinical trials  

clinical informatics: Integration of clinical workflow and business strategies of any healthcare organization will spell success for the providers of the future. Efficient exchange of data and information is essential for this merger, and information technology is the tool with which to accomplish the consolidation. Clinical Informatics is the practice evolving from this need in healthcare. HIMSS Clinical informatics http://www.himss.org/ASP/topics_clinicalInformatics.asp 

is the application of informatics and information technology to deliver healthcare services. It is also referred to as applied clinical informatics and operational informatics. AMIA considers informatics when used for healthcare delivery to be essentially the same regardless of the health professional group involved (whether dentist, pharmacist, physician, nurse, or other health professional). Clinical Informatics is concerned with information use in health care by clinicians. Clinical informatics includes a wide range of topics ranging from clinical decision support to visual images (e.g. radiological, pathological, dermatological, ophthalmological, etc); from clinical documentation to provider order entry systems; and from system design to system implementation and adoption issues. AMIA Clinical informatics http://www.amia.org/applications-informatics/clinical-informatics

The application of informatics approaches to the clinical- evaluation phase of drug development. These approaches can include clinical- trial simulations to improve trial design and patient selection, as well as electronic capturing and storing of clinical data and protocols. The goal is to reduce expenses and time to market   

Clinical Research News http://www.clinicalinformaticsnews.com/

Clinical Research & Translational Informatics Transforming Biological Data to Clinical Development 2019 April 17-18 Boston MA Advancing clinical trials and translational research requires transforming biological insights and raw research data into clean, actionable data using innovative techniques for its integration, visualization and analysis. The Clinical Research & Translational Informatics track explores new approaches to the integration, visualization, analysis, and application of biological and clinical trial data, including machine learning, artificial intelligence, big data analytics, and additional technologies with case studies from across pharma and academia.  http://www.bio-itworldexpo.com/clinical-translational-informatics

clinomics: The application of oncogenomic research. Daniel von Hoff, Univ. of Arizona "All hands on deck at dawn" Nature Genetics 27 (4): 347-349, April 2001 

cohort studies large scale: In the past 20 years, birth cohort studies to assess the risks to developing children from harmful chemicals in air, water and food have been undertaken in many countries. These birth cohort studies usually started during pregnancy and followed children through adolescence or beyond. Even the largest of these birth cohort studies, however, were not big enough to study rare outcomes such as childhood cancer or sudden infant death syndrome. To increase the sample size, investigators working with these older cohort studies are now making an effort to pool their data. Their efforts are hampered by the fact that the older studies did not usually agree upon disease outcome definitions, time periods of measurement, or methods for measuring biomarkers and chemical contaminants in air, water and food. This makes pooling data extremely difficult. To avoid such problems in the next generation of large-scale birth cohort studies, it is worthwhile for investigators from various countries to invest time up front to agree on how to assess disease outcomes, measure biomarkers, and measure environmental exposures. Pooling of data, should that be desirable, with then be much more straightforward.  Coordination of new large scale birth cohort studies, Children’s Environmental Health, WHO 2014 http://www.who.int/ceh/cohorts/en/ 

communications standards: It is clear that shared understanding of the basic data elements within pharmacogenomics is a critical building block upon which to build an information infrastructure. Methods for communicating these data are therefore equally as important. The two main areas that require progress are the definition of shared syntax (how information is structured in a data file) and semantics (how the information should be interpreted by others). Russ Altman "Challenges for Biomedical Informatics and Pharmacogenomics, Stanford Medical Informatics, 2002 http://www.annualreviews.org/doi/abs/10.1146/annurev.pharmtox.42.082401.140850  Related terms: Information management & interpretation  controlled vocabularies, syntax, semantics

comparative data mining: Algorithms Useful for clinical trial meta-analyses  

comparative effectiveness research CER: is the conduct and synthesis of systematic research comparing different interventions and strategies to prevent, diagnose, treat and monitor health conditions. The purpose of this research is to inform patients, providers, and decision-makers, responding to their expressed needs, about which interventions are most effective for which patients under specific circumstances. To provide this information, comparative effectiveness research must assess a comprehensive array of health-related outcomes for diverse patient populations… [Internet.] Federal Coordinating Council for Comparative Effectiveness Research [cited 28 July 2010].  Comparative Effectiveness Research, Health Services Research Information Central, National Library of Medicine, NIH http://www.nlm.nih.gov/hsrinfo/cer.html

complex: It has become common to use complicated and complex interchangeably … The essence of ‘complicated’ is hard to figure out. ..Complex, on the other hand is a term reserved for systems that display properties that are not predictable from a complete description of their components, and that are generally considered to be qualitatively different from the sum of their parts. [Editorial, "Complicated is not complex" Nature Biotechnology 17: 511 June 1999] Would it be fair to say that Mendelian genetics is linear, while genomics and polygenic diseases/traits are nonlinear?

According to the Oxford English Dictionary one of the meanings of complicated is complex, though it also means not easy to unravel or separate. Both complex and complicated are contrasted with simple. Whatever the original senses of these two words, the above distinction seems a useful one now.  Related term: complexity; Narrower terms: biocomplexity, complex diseases, complex genomes; complex phenotypes, complex traits  

complex diseases: Diseases characterized by risk to relatives of an affected individual which is greater than the incidence of the disorder in the population. [NHLBI] 

The research activities in the Department of Genetics and Complex Diseases and its pre and postdoctoral training programs concentrate on the molecular, cellular, and organismic adaptations and responses to nutrients, toxins, and radiation stress and explore the genetic basis controlling the heterogeneity of these interactions in experimental systems. The integrated interdisciplinary opportunities also aim to apply this knowledge to human populations to understand, prevent, and treat complex human diseases. Dept of Genetics and Complex Diseases, Harvard School of Public Health  2011 http://www.hsph.harvard.edu/departments/genetics-and-complex-diseases/ 

How are complex diseases related to polygenic diseases?  Related terms: SNPs & genetic variations;   Omes & omics phenome, phenomics

computable phenotypes: A computable phenotype is a clinical condition, characteristic, or set of clinical features that can be determined solely from the data in EHRs and ancillary data sources and does not require chart review or interpretation by a clinician. These can also be referred to as EHR condition definitions, EHR-based phenotype definitions, or simply phenotypes. We use the term EHR broadly to reference data that are generated through healthcare delivery and reimbursement practices; in practice, these functions may be covered in multiple systems and can contain both practice management data and data that are strictly limited to the clinical domain. We use ancillary data sources to refer to sources such as disease registries, claims data, or supplemental data collection that are related to health care delivery but may not be directly integrated into the EHR system.   Electronic Health Records based phenotyping http://rethinkingclinicaltrials.org/resources/ehr-phenotyping/

computational pharmacology: Pharmacogenomics

computational physiology: The International Union of Physiological Sciences (IUPS) Physiome Project is an internationally collaborative open- source project to provide a public domain framework for computational physiology, including the development of modeling standards, computational tools and web-accessible databases of models of structure and function at all spatial scales [1,2,3]. It aims to develop an infrastructure for linking models of biological structure and function across multiple levels of spatial organization and multiple time scales. The levels of biological organisation, from genes to the whole organism, includes gene regulatory networks, protein- protein and protein- ligand interactions, protein pathways, integrative cell function, tissue and whole heart structure- function relations. The whole heart models include the spatial distribution of protein expression. Keynote: Peter J. Hunter, Univ of Auckland, International Society of Computational Biology, Detroit, MI, 2005 http://www.iscb.org/ismb2005/keynotes.html 

computational therapeutics:  An emerging biomedical field. It is concerned with the development of techniques for using software to collect, manipulate and link biological and medical data from diverse sources.   It is also concerned with the use of such information in simulation models to make predictions or therapeutically relevant discoveries or advances. (Referred to by some as in silico pharmacology) C. Anthony Hunt Lab, Biosystems at Univ. of California, San Francisco, http://biosystems.ucsf.edu/   

consumer health informatics: is the field devoted to informatics from multiple consumer or patient views. These include patient-focused informatics, health literacy and consumer education. The focus is on information structures and processes that empower consumers to manage their own health--for example health information literacy, consumer-friendly language, personal health records, and Internet-based strategies and resources. The shift in this view of informatics analyses consumers' needs for information; studies and implements methods for making information accessible to consumers; and models and integrates consumers' preferences into health information systems. Consumer informatics stands at the crossroads of other disciplines, such as nursing informatics, public health, health promotion, health education, library science, and communication science. AMIA Consumer Health Informatics  http://www.amia.org/applications-informatics/consumer-health-informatics

digiceuticals: Digital Therapeutics is a different class of product than Digiceuticals. Most people confuse the two. The difference is similar to prescription medication versus nutritional supplements. Both play their role, but the standards of efficacy, and thus pricing and reimbursement are very different.  Hundreds of millions of dollars have been invested in digiceuticals: …But, the efficacy has not been evaluated in prospective randomized clinical trials and found to be non-inferior to the control group. Thus, while the app usage data might show correlation with the end goal, it has not proven causation. Digiceuticals are important, but like nutritional supplements, are a consumer-focused business.   Digital Therapeutics vs. Digiceuticals, Defining the software mediated digital healthcare Landscape,  Medium, 2016 https://medium.com/@Healthy.vc/digital-therapeutics-vs-digiceuticals-defining-the-software-mediated-healthcare-landscape-fd0eb9dbedec

digital health: Digital health is not a new concept. Seth Frank, writing 13 years ago, penned “Digital Health Care—The convergence of health care and the Internet” in The Journal of Ambulatory Care Management. Today, technology is rapidly transforming healthcare. Eric Topol’s The Creative Destruction of Medicine enumerates how these digital technologies, social networking, mobile connectivity and bandwidth, increasing computing power and the data universe will converge with wireless sensors, genomics, imaging, and health information systems to creatively destroy medicine as we know it. He refers to this as digital medicine, or the digitization of human beings.  At Rock Health, we support entrepreneurs working in the space Topol describes—at the intersection of healthcare and technology; and not solely in medicine, but across healthcare, including wellness and administration. As part of our research, we track companies and catalog venture funding in the digital health space.  Defining digital health and choosing which companies to include is complex, so here is some transparency as to how we catalog deals: What Digital Health is [and Isn’t) Rock Health http://rockhealth.com/2013/04/what-digital-health-is-and-isnt/ 

The broad scope of digital health includes categories such as mobile health (mHealth), health information technology (IT), wearable devices, telehealth and telemedicine, and personalized medicine.  FDA Digital Health
https://www.fda.gov/medicaldevices/digitalhealth/

Digital health is the convergence of the digital and genetics revolutions with health and healthcare. As we are seeing and experiencing, digital health is empowering us to better track, manage, and improve our own and our family’s health. It’s also helping to reduce inefficiencies in healthcare delivery, improve access, reduce costs, increase quality, and make medicine more personalized and precise. … The essential elements of the digital health revolution include wireless devices, hardware sensors and software sensing technologies, microprocessors and integrated circuits, the Internet, social networking, mobile and body area networks, health information technology, genomics, and personal genetic information. The lexicon of Digital Health is extensive and includes all or elements of mHealth (aka Mobile Health), Wireless Health, Health 2.0, eHealth, Health IT, Big Data, Health Data, Cloud Computing, e-Patients, Quantified Self and Self-tracking, Wearable Computing, Gamification, Telehealth & Telemedicine, Precision and Personalized Medicine, plus Connected Health. Story of Digital Health, Paul Sonnier, 2014 http://storyofdigitalhealth.com/definition/

digital therapeutics: The term digital therapeutics began to circulate around 2013, in large part due to Sean Duffy, CEO of Omada Health. He began using it at conferences and in the company’s marketing materials to describe its online coaching software to help pre-diabetics avoid getting sick by exercising more and losing weight.  About a dozen startups now call themselves digital therapeutics providers, and say they’re distinct from the rest of the digital health market of activity monitors, smart scales, and sleep trackers.  But defining exactly what a digital therapeutic actually is can be elusive…says Peter Hames …Hames says digital therapies fall into two groups, which he calls “medication augmentation” and “medication replacement.” … Can “Digital Therapeutics” Be as Good as Drugs?, Christina Farr, April 7, 2017 MIT Technology Review https://www.technologyreview.com/s/604053/can-digital-therapeutics-be-as-good-as-drugs/
Related term: digiceuticals.

drug utilization: The utilization of drugs as reported in individual hospital studies, FDA studies, marketing, or consumption, etc. This includes drug stockpiling, and patient drug profiles. MeSH, 1973

drug utilization review:  Formal programs for assessing drug prescription against some standard. Drug utilization review may consider clinical appropriateness, cost effectiveness, and, in some cases, outcomes. Review is usually retrospective, but some analysis may be done before drugs are dispensed (as in computer systems which advise physicians when prescriptions are entered). Drug utilization review is mandated for Medicaid programs beginning in 1993. MeSH, 1994  Related terms: ATC/DDD, EPhMRA, PBIRG

eCommon Technical Document: The Electronic Common Technical Document (eCTD) is CDER/CBER’s standard format for electronic regulatory submissions. The FDA would like to work closely with people who plan to provide a submission using the eCTD specifications  FDA, Common Technical Document http://www.fda.gov/Drugs/DevelopmentApprovalProcess/FormsSubmissionRequirements/ElectronicSubmissions/ucm153574.htm 

Electronic Common Technical Document, Wikipedia http://en.wikipedia.org/wiki/Electronic_Common_Technical_Document

EDC electronic data capture: Wikipedia http://en.wikipedia.org/wiki/Electronic_Data_Capture 

effectiveness research: See comparative effectiveness research, see also under outcomes research

e-health: (also written e-health) is a relatively recent healthcare practice supported by electronic processes and communication, dating back to at least 1999.^[1] Usage of the term varies. A study in 2005 found 51 unique definitions.^[2] Some argue that it is interchangeable with health informatics with a broad definition covering electronic/digital processes in health^[3] while others use it in the narrower sense of healthcare practice using the Internet.^[4][5][6] It can also include health applications and links on mobile phones, referred to as mHealth or m-Health.^[7] … Several authors have noted the variable usage in the term, from being specific to the use of the Internet in healthcare to being generally around any use of computers in healthcare.^[10] Various authors have considered the evolution of the term and its usage and how this maps to changes in health informatics and healthcare generally.^[1][11][12] Oh et al., in a 2005 systematic review of the term's usage, offered the definition of eHealth as a set of technological themes in health today, more specifically based on commerce, activities, stakeholders, outcomes, locations, or perspectives.^[2] One thing that all sources seem to agree on is that e-Health initiatives do not originate with the patient, though the patient may be a member of a patient organization that seeks to do this, as in the e-Patient movement . Wikipedia accessed 2018 march 15 https://en.wikipedia.org/wiki/EHealth

Electronic Health Records EHRs:  Electronic Health Records (EHRs) are safe and confidential records that your doctor, other health care provider, medical office staff, or a hospital keeps on a computer about your health care or treatments. If your providers use electronic health records, they can join a network to securely share your records with each other. EHRs can help lower the chances of medical errors, eliminate duplicate tests, and may improve your overall quality of care.  EHRs can help your providers have the same up-to-date information about your conditions, treatments, tests, and prescriptions. Electronic Health Records, Medicare.gov http://www.medicare.gov/manage-your-health/electronic-health-records/electronic-health-records.html

The healthcare environment will be profoundly changed by the convergence of technology, and ready access to updated patient information. The program will cover the use of combinatorial device technology to integrate healthcare systems, and the novel connectivity of global electronic medical record efforts. Clinical management of disease will be addressed through the use of handheld and point-of-care devices. The value of real time patient information to the clinical management team and the pharmaceutical researcher will be leveraged while addressing the ethical and legal implications. 

Electronic Medical Records EMR: The EMR or electronic medical record refers to everything you’d find in a paper chart, such as medical history, diagnoses, medications, immunization dates, allergies. EHR vs, EMR: What’s the difference? https://www.practicefusion.com/blog/ehr-vs-emr/#EHRvsEMR

electronic prescribing: Agency for Healthcare Research & Quality, 
http://healthit.ahrq.gov/portal/server.pt?open=514&objID=5554&mode=2&holderDisplayURL=http://prodportal

electronic records Part 11 electronic signatures  -- FDA:  https://www.fda.gov/regulatory-information/search-fda-guidance-documents/part-11-electronic-records-electronic-signatures-scope-and-application

Electronic standards for the transfer of regulatory information, Glossary of Abbreviations and Terms ICH m2, 2015  http://estri.ich.org/recommendations/M2_Glossary_v2%200%20_11%20June%202015.pdf

evidence based medicine:  Wikipedia https://en.wikipedia.org/wiki/Evidence-based_medicine
BMJ Evidence Based Medicine http://ebm.bmj.com/

genomic epidemiology: An emerging discipline involving population studies and microarray/ expression studies.  Related terms: environmental factors, public health; molecular epidemiology, human genome epidemiology, phenotypic prevention

health informatics: (also called health care informatics, healthcare informatics, medical informatics, nursing informatics, clinical informatics, or biomedical informatics) is informatics in health care, essentially the management and use of patient healthcare information. It is a multidisciplinary field^[1] that uses health information technology (HIT) to improve health care via any combination of higher quality, higher efficiency (spurring lower cost and thus greater availability), 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".^[2] It deals with the resources, devices, and methods required to optimize the acquisition, storage, retrieval, and use of information in health and biomedicine. Health informatics tools include computers, clinical guidelines, formal medical terminologies, and information and communication systems, amongst others.^[3][4] It is applied to the areas of nursing, clinical medicine, dentistry, pharmacy, public health, occupational therapy, physical therapy, biomedical research, and alternative medicine,^{[5][unreliable medical source?]}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.^[6]  The international standards on the subject are covered by ICS 35.240.80^[7] in which ISO 27799:2008 is one of the core components.^[8]  Wikipedia accessed 2018 March https://en.wikipedia.org/wiki/Health_informatics

"the interdisciplinary study of the design, development, adoption and application of IT-based innovations in healthcare services delivery, management and planning." Procter, R. Dr. (Editor, Health Informatics Journal, Edinburgh, United Kingdom). Definition of health informatics [Internet]. Message to: Virginia Van Horne (Content Manager, HSR Information Central, Bethesda, MD). 2009 Aug 16 [cited 2009 Sept 21]. National Library of Medicine http://www.nlm.nih.gov/hsrinfo/informatics.html  
Related terms: biomedical informatics, healthcare informatics, medical informatics     Wikipedia http://en.wikipedia.org/wiki/Health_informatics  

In the fall of 2015, the TIGER Committee began compiling interprofessional informatics definitions.  The purpose of creating this document was to collaboratively define and document core health informatics terminology in an effort to provide context to the global TIGER interprofessional, interdisciplinary community for consideration when terms are referred to on the TIGER’s main landing page on HIMSS.org, in official documents, and within the TIGER Virtual Learning Environment (VLE).  Our intention is for this resource to serve as a helpful tool for those learning about informatics and informatics competencies. The 3.0 version of this document was published in June 2018. https://www.himss.org/library/tiger-informatics-definitions?utm_source=commnews&utm_medium=email&utm_campaign=tiger

health IT tools: Agency for Healthcare Research & Quality, http://healthit.ahrq.gov/portal/server.pt?open=512&objID=919&parentname=CommunityPage&parentid=9&mode=2&in_h

health record: Historically, the definition of a legal medical or health record seemed straightforward. The contents of the paper chart formed the provider of care’s legal business record. Patients had limited interest in or access to the information contained in their record. With the advent of various electronic media, the Internet, and the consumer’s enhanced role in compiling health records, the definition of the legal health record became more complex. The need remains to ensure information is accessible for its ultimate purposes regardless of the technologies employed or users involved. The definition of the legal health record (LHR) must therefore be reassessed in light of such new technologies, users, and uses.  Amatayakul, Margret et al. "Definition of the Health Record for Legal Purposes (AHIMA Practice Brief)." Journal of AHIMA 72, no.9 (2001): 88A-H. http://library.ahima.org/xpedio/groups/public/documents/ahima/bok1_009223.hcsp?dDocName=bok1_009223 

Healthcare Informatics: Despite the rapid advances in medical science, the healthcare delivery system remains plagued with inefficiencies that hinder basic access to quality care at a reasonable price. Soaring costs are placing severe strains on an already overburdened system, and administrators are scrambling to organize an ever-increasing stream of information from a variety of data sources. There is a growing consensus that Information Technology (IT) provides the key to cost-effective quality care for all. Our research applies core computer science and mathematics to complex healthcare domain problems. We look to solve some of healthcare’s greatest IT challenges with new technology and methods that often translate to other industries. Our technologies and inventions focus on the advancement of multi-modal analysis, complex information integration technology, disease and event modeling and genomics.  http://www.almaden.ibm.com/cs/disciplines/hc/ 

HL7: Health Level Seven is one of several American National Standards Institute (ANSI) -accredited Standards Developing Organizations (SDOs) operating in the healthcare arena. … Health Level Seven’s domain is clinical and administrative data. "Level Seven" refers to the highest level of the International Organization for Standardization (ISO) communications model for Open Systems Interconnection (OSI) - the application level. http://www.hl7.org/  

human factors: Human factors/usability engineering focuses on the interactions between people and devices. The critical element in these interactions is the device user interface ... Human factors/usability engineering is used to design the machine-human (device-user) interface. The user interface includes all components with which users interact while preparing the device for use (e.g., unpacking, set up, calibration), using the device, or performing maintenance (e.g., cleaning, replacing a battery, making repairs). FDA, CDHR Medical Devices General Human Factors Information and Resources http://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/HumanFactors/ucm124829.htm

immunoinformatics: or computational immunology, is an emerging area that provides fundamental methodologies in the study of immunomics, that is, immune-related genomics and proteomics. The integration of immunoinformatics with systems biology approaches may lead to a better understanding of immune-related diseases at various systems levels. Such methods can contribute to translational studies that bring scientific discoveries of the immune system into better clinical practice. One of the most intensely studied areas of the immune system is immune epitopes. Epitopes are important for disease understanding, host-pathogen interaction analyses, antimicrobial target discovery, and vaccine design. The information about genetic diversity of the immune system may help define patient subgroups for individualized vaccine or drug development. Cellular pathways and host immune-pathogen interactions have a crucial impact on disease pathogenesis and immunogen design. Epigenetic studies may help understand how environmental changes influence complex immune diseases such as allergy. High-throughput technologies enable the measurements and catalogs of genes, proteins, interactions, and behavior. Such perception may contribute to the understanding of the interaction network among humans, vaccines, and drugs, to enable new insights of diseases and therapeutic responses. The integration of immunomics information may ultimately lead to the development of optimized vaccines and drugs tailored to personalized prevention and treatment. Methods Mol Biol. 2010;662:203-20. doi: 10.1007/978-1-60761-800-3_10. Immunoinformatics and systems biology methods for personalized medicine. Yan Q. http://www.ncbi.nlm.nih.gov/pubmed/20824473    See also Therapeutic areas: immunogenomics

in silico clinical trials: See Clinical trials computer trials simulations  

in silico pharmacology (also known as computational therapeutics, computational pharmacology) is a rapidly growing area that globally covers the development of techniques for using software to capture, analyse and integrate biological and medical data from many diverse sources. More specifically, it defines the use of this information in the creation of computational models or simulations that can be used to make predictions, suggest hypotheses, and ultimately provide discoveries or advances in medicine and therapeutics. add citation.  https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1978274/