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Clinical & Medical informatics glossary & taxonomy
Evolving Terminology for Emerging Technologies
Comments? Questions? Revisions? 
Mary Chitty 
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

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 HealthcareTransforming 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.

Bayesian network: Wikipedia 
Bayesian networks: 
A quick intro, Karen Sachs, Biomedical Computation Review, Summer 2005 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

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 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
    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.  

clinical data repositories, shared: Agency for Healthcare Research & Quality

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  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 

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

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

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.

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 

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  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

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 

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

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 

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,   

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

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

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 

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

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

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
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 

Electronic Common Technical Document, Wikipedia

EDC electronic data capture: Wikipedia 

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

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,

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?

electronic prescribing: Agency for Healthcare Research & Quality,

electronic records Part 11 electronic signatures  -- FDA:

Electronic standards for the transfer of regulatory information, Glossary of Abbreviations and Terms ICH m2, 2015

evidence based medicine:  Wikipedia
BMJ Evidence Based Medicine

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

"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  
Related terms: biomedical informatics, healthcare informatics, medical 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, 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.

health IT tools: Agency for Healthcare Research & Quality,

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. 

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. 

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.  

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

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.    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.

laboratory informatics: the specialized application of information technology aimed at optimizing laboratory operations. It is a collection of informatics tools utilized within laboratory environments to collect, store, process, analyze, report, and archive data and information from the laboratory and supporting processes. Laboratory informatics includes the integration of systems, the electronic delivery of results to customers, and the supporting systems including training and policies. Examples of laboratory informatics include: Laboratory Information Management Systems (LIMS), Electronic Laboratory Notebooks (ELNs), Chromatography Data Systems (CDS), and Scientific Data Management Systems (SDMS). ASTM E1578 Standard Guide for Laboratory Informatics 2013    Wikipedia   Related term?: Drug discovery & development  LIMS  

LOINC Logical Observation Identifiers Names and Codes: The purpose of the LOINC database is to facilitate the exchange and pooling of results, such as blood hemoglobin, serum potassium, or vital signs, for clinical care, outcomes management, and research. Regenstrief Institute Inc. Germany  

meaningful use:
is using certified electronic health record (EHR) technology to: Improve quality, safety, efficiency, and reduce health disparities, Engage patients and family, Improve care coordination, and population and public health, Maintain privacy and security of patient health information, Ultimately, it is hoped that the meaningful use compliance will result in: Better clinical outcomes, Improved population health outcomes, Increased transparency and efficiency, Empowered individuals, More robust research data on health systems EHR Incentives and Certification

The overall goal of the Meaningful Use program is to promote the widespread adoption of electronic health records systems, ultimately creating an infrastructure that improves the quality, safety and efficiency of patient care in the United States. … To qualify for Meaningful Use incentive payments, eligible providers must not only adopt an EHR, but also show that they are "meaningfully using" their EHR by meeting a number of objectives designed to have a positive impact on patient care. The Centers for Medicare & Medicaid Services (CMS) has established these measures as part of their mission to advance health care IT in the U.S. AthenaHealth
CDC, meaningful use

Medbiquitous Consortium: ANSI-accredited developer of information technology standards for healthcare education and quality improvement.

medical bioinformatics: Linking clinical data to patient gene profiling. Covers haplotyping, genotyping, population genomics, gene expression profiling, particularly for use in diagnosis, prognosis and therapeutic stratification of patients.  Related terms: BiomarkersExpression,   Microarrays and protein chips

medical informatics: The field of information science concerned with the analysis and dissemination of medical data through the application of computers to various aspects of health care and medicine. MeSH, 1987

An emerging discipline that has been defined as the study, invention, and implementation of structures and algorithms to improve communication, understanding and management of medical information. The end objective of biomedical informatics is the coalescing of data, knowledge, and the tools necessary to apply that data and knowledge in the decision- making process, at the time and place that a decision needs to be made. The focus on the structures and algorithms necessary to manipulate the information separates Biomedical Informatics from other medical disciplines where information content is the focus. Medical Informatics FAQ, 1999  

MedDRA Medical Dictionary for Regulatory Activities: In the late 1990s, the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) developed MedDRA, a rich and highly specific standardised medical terminology to facilitate sharing of regulatory information internationally for medical products used by humans.  

meta-analysis: The use of statistical techniques in a systematic review to integrate the results of included studies. Sometimes misused as a synonym for systematic reviews, where the review includes a meta- analysis.  Cochrane Collaboration "Glossary of terms in the Cochrane Collaboration, 2014   

A quantitative method of combining the results of independent studies (usually drawn from the published literature) and synthesizing summaries and conclusions which may be used to evaluate therapeutic effectiveness, plan new studies, etc., with application chiefly in the areas of research and medicine. MeSH, 1989

meta-regression:  Meta-regression is an extension to subgroup analyses that allows the effect of continuous, as well as categorical, characteristics to be investigated, and in principle allows the effects of multiple factors to be investigated simultaneously (although this is rarely possible due to inadequate numbers of studies) (Thompson 2002). Meta-regression should generally not be considered when there are fewer than ten studies in a meta-analysis. General Methods for Cochran Reviews, Cochran Collaborative

mHealth : (also written as m-health) is  an abbreviation for mobile health, a term used for the practice of medicine and public health supported by mobile devices.[1] The term is most commonly used in reference to using mobile communication devices, such as mobile phones, tablet computers and PDAs, and wearable devices such as smart watches, for health services, information, and data collection.[2] 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 satellitepatient monitors, etc., for health services and information.[3] mHealth applications include the use of mobile devices in collecting community and clinical health data, delivery of healthcare information to practitioners, researchers, and patients, real-time monitoring of patient vital signs, and direct provision of care (via mobile telemedicine).[4]  While mHealth certainly has application for industrialized nations, the field has emerged in recent years as largely an application for developing countries, stemming from the rapid rise of mobile phone penetration in low-income nations. Wikipedia accessed 2018 March 15

With the emergence of new technologies such as mobile devices and wearables, the pharma and biotech industry are poised to capitalize on these advancements to innovate existing clinical trial processes and systems. Advancing technological innovation in clinical trials coincides with the move toward greater cross-industry clinical trial data sharing and clinical data transparency.  Coupled together new technological advances and increased clinical trial data sharing leads to more efficient clinical trials.  See also telehealth.

National Center for Integrative Biomedical Informatics:
One of eight 
National Centers for Biomedical Computing (NCBC) within the NIH Roadmap. The NCBC program is focused on building a universal computing infrastructure designed to speed progress in biomedical research.  

National Electronics Clinical Trials and Research (NECTAR): An enriched pipeline of biomedical discoveries, an infrastructure to facilitate the translation of these discoveries from the laboratory to the clinic, and a robust force of clinical investigators will make it possible to test new therapeutic and preventive strategies in larger numbers of patients far sooner than currently possible. These large studies are often best conducted through networks of investigators who are equipped with tools to facilitate collaboration and information sharing. Because of the vast number of therapies, diagnostics, and treatments that must be evaluated through clinical trials, many clinical research networks operate simultaneously, but independently, of each other. As a result, researchers must sometimes duplicate data that already exists because they are unaware of the data or do not have access to the data. Standardizing data reporting would enable seamless data- and sample-sharing across studies. By enhancing the efficiency of clinical research networks through informatics and other technologies, researchers will be better able to broaden the scope of their research. Reduced duplication of studies will leave more time and funds to address additional research questions.  NECTAR, NIH Common Fund

neuroimaging: Neuroimaging informatics tools and resources 

neuroinformatics:  a research field concerned with the organization of neuroscience data by the application of computational models and analytical tools. These areas of research are important for the integration and analysis of increasingly large-volume, high-dimensional, and fine-grain experimental data. Neuroinformaticians provide computational tools, mathematical models, and create interoperable databases for clinicians and research scientists. Neuroscience is a heterogeneous field, consisting of many and various sub-disciplines (e.g., cognitive psychologybehavioral neuroscience, and behavioral genetics). Wikipedia accessed 2018 Oct 23 

NIH Blueprint for Neuroscience Research

Office of the National Coordinator for Health Information Technology (ONC): is at the forefront of the administration’s health IT efforts and is a resource to the entire health system to support the adoption of health information technology and the promotion of nationwide health information exchange to improve health care. ONC is the principal federal entity charged with coordination of nationwide efforts to implement and use the most advanced health information technology and the electronic exchange of health information.

outcomes research:  The terms "outcomes research" and "effectiveness research" have been used to refer to a wide range of studies, and there is no single definition for either that has gained widespread acceptance. As these fields evolved, it appears that "outcomes research" emerged from a new emphasis on measuring a greater variety of impacts on patients and patient care (function, quality of life, satisfaction, readmissions, costs, etc). The term "effectiveness research" was used to emphasize the contrast with efficacy studies, and highlighted the goal of learning how medical interventions affected real patients in "typical" practice settings (OTA, 1994). Effectiveness studies sought to understand the impact of health care on patients with diverse characteristics, rather than highly homogeneous study populations. While the terms may have different initial roots, there does not appear to be much value in distinguishing these activities, and the field is generally referred to as OER. .. OER evaluates the impact of health care (including discrete interventions such as particular drugs, medical devices, and procedures as well as broader programmatic or system interventions) on the health outcomes of patients and populations. OER may include evaluation of economic impacts linked to health outcomes, such as cost- effectiveness and cost utility. OER emphasizes health problem- (or disease-) oriented evaluations of care delivered in general, real- world settings; multidisciplinary teams; and a wide range of outcomes, including mortality, morbidity, functional status, mental well- being, and other aspects of health-related quality of life.   Outcome of Outcomes Research at AHCPR: Final Report, Agency for Health Care Policy and Research, AHCPR Publication No. 99-R044
Related term: comparative effectiveness research

pathology informatics: involves collecting, examining, reporting, and storing large complex sets of data derived from tests performed in clinical laboratories, anatomic pathology laboratories, or research laboratories in order to improve patient care and enhance our understanding of disease-related processes. … The data sets used in pathology informatics include clinical tests, anatomic pathology reports, image files, telepathology data, and large-scale experiments including gene, proteomic and tissue array studies. Association for Pathology Informatics

patient engagement: Surgeon General C Everett Koop once said “Drugs don’t work in patients who don’t take them.” I’ll offer a corollary of my own: Patients who aren’t engaged don’t comply with therapies or report complications.  Enabling Patient Engagement and Healthcare Innovation, FDA Testimony Healthcare Innovation DDMAC Public Hearings on Internet & Social Media #FDASM Zen Chu, 2009 

patient reported outcomes: the PROMIS (Patient-Reported Outcomes Measurement Information System) initiative is developing new ways to measure patient-reported outcomes (PROs), such as pain, fatigue, physical functioning, emotional distress, and social role participation that have a major impact on quality-of-life across a variety of chronic diseases. Clinical measures of health outcomes, such as x-rays and lab tests, may have minimal relevance to the day-to-day functioning of patients with chronic diseases. Often, the best way patients can judge the effectiveness of treatments is by changes in symptoms. The goal of PROMIS is to improve the reporting and quantification of changes in PROs. PROMIS Patient Reported Outcomes, NIH Common Fund 

Personal Health Record PHR: The PHR is a tool that you can use to collect, track and share past and current information about your health or the health of someone in your care. Sometimes this information can save you the money and inconvenience of repeating routine medical tests. Even when routine procedures do need to be repeated, your PHR can give medical care providers more insight into your personal health story. AHIMA, MyPHR -

 the science that applies epidemiologic approaches to studying the use, effectiveness, value and safety of pharmaceuticals.  The International Society for Pharmacoepidemiology (ISPE) is an international organization dedicated to advancing the health of the public by providing a global forum for the open exchange of scientific information and for the development of policy, education, and advocacy for the field of pharmacoepidemiology, including such area as pharmacovigilance, drug utilization research, comparative effectiveness review, and therapeutic risk management.  International Society of Pharmacoepidemiology

population health: has been defined as "the health outcomes of a group of individuals, including the distribution of such outcomes within the group".[1] It is an approach to health that aims to improve the health of an entire human population. This concept does not refer to animal or plant populations. It has been described as consisting of three components. These are "health outcomes, patterns of health determinants, and policies and interventions".[1] A priority considered important in achieving the aim of Population Health is to reduce health inequities or disparities among different population groups due to, among other factors, the social determinants of health, SDOH. ... From a population health perspective, health has been defined not simply as a state free from disease but as "the capacity of people to adapt to, respond to, or control life's challenges and changes".[5] The World Health Organization (WHO) defined health in its broader sense in 1946 as "a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity."[6][7] Wikipedia accessed 2018 Feb 20

predictive genomics: Wayne D. Hall1,+, Katherine I. Morley1,2 and Jayne C. Lucke1, The prediction of disease risk in genomic medicine: Scientific prospects and implications for public policy and ethics EMBO reports vol. 5 | Suppl 1 | pp S22-S26 | 2004 DOI: 10.1038/sj.embor.7400224  See also Pharmacogenomics  predictive pharmacogenomics 

The probable outcome or course of a disease; the chance of  recovery. [ORD]

Not a major emphasis in clinical medicine today. Nicholas Christakis' Death Foretold is an eloquent book about the delicate balance between medical reality and optimism, and how seldom this is discussed in either classrooms or hospital rooms today.

public health informatics: The systematic application of information and computer sciences to public health practice, research, and learning. It is the discipline that integrates public health with information technology. The development of this field and dissemination of informatics knowledge and expertise to public health professionals is the key to unlocking the potential of information systems to improve the health of the nation.  MeSH 2003

is the application of informatics in areas of public health, including surveillance, prevention, preparedness, and health promotion. Public health informatics and the related population informatics, work on information and technology issues from the perspective of groups of individuals. Public health is extremely broad and can even touch on the environment, work and living places and more. Generally, AMIA focuses on those aspects of public health that enable the development and use of interoperable information systems for public health functions such as biosurveillance, outbreak management, electronic laboratory reporting and prevention. AMIA Public Health Informatics

Real World Data RWD:  anything OTHER than RCT [randomized controlled trails] generated data…data derived from: Prospective observational studies, Non-interventional observations, Database studies, Prospective registries create a database, Retrospective databases created for other reasons, Medical records, Data abstraction. In general, “real world data” are observations of effects based on what happens after a prescriptive (treatment) decision is made where the researcher does not or cannot control who gets what treatment and does not or cannot control the medical management of the patient beyond observing outcomes. Using Real World Data in Pharmacoeconomic Evaluations: Challenges, Opportunities, and Approaches. Andreas M. Pleil, Pfizer

the data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources. RWD can come from a number of sources, for example: Electronic health records (EHRs), Claims and billing activities, Product and disease registries, Patient-generated data including in home-use settings, Data gathered from other sources that can inform on health status, such as mobile devices. US FDA Real World Evidence Science and Research

Makady A, van Veelen A, Jonsson P, et al. Using Real-World Data in Health Technology Assessment (HTA) Practice: A Comparative Study of Five HTA Agencies. Pharmacoeconomics. 2018;36(3):359-368.

Real world data can be gathered from retrospective or prospective studies in which the investigator observes natural events without intervention (e.g. audits, cohort or case–control studies).

GetReal Project No 115546 WP1 Deliverable D1.3 Glossary of Definitions of Common Terms  2009  [PDF]
WP1: Deliverable D1.3 Glossary of Definitions of Common Terms ...

Real World Evidence RWE:  While the definition of Real World Evidence is still evolving, most proponents associate such as insurance claims data and clinical data from electronic health records. Real World Evidence - The Network For Excellence In Health Innovation 

the clinical evidence regarding the usage and potential benefits or risks of a medical product derived from analysis of RWD. US FDA Real World Evidence Science and Research

FDA, Framework for Real World Evidence Program 2018 Dec

SNOMED Systematized Nomenclature of Medicine: SNOMED International determines global standards for health terms.

systems medicine: an interdisciplinary field of study that looks at the systems of the human body as part of an integrated whole, incorporating biochemical, physiological, and environment interactions. Systems medicine draws on systems science and systems biology, and considers complex interactions within the human body in light of a patient's genomics, behavior and environment.[1] The earliest uses of the term systems medicine appeared in 1992, in an article on systems medicine and pharmacology by B.J. Zeng [2] and in a paper on systems biomedicine by T. Kamada.[3]   Wikipedia accessed 2018 Sept 2

syndromics, syndromic systems: Systems of information for the detected of occurrences of syndromes. Edilson Damasio, Systems of information and surveillance of occurrences in bioterrorism, 9th World Congress on Health Information and Libraries, Brazil, Sept. 20-23, 2005  

telehealth:  Wikipedia 


translational bioinformatics: is the development of storage, analytic, and interpretive methods to optimize the transformation of increasingly voluminous biomedical data, and genomic data, into proactive, predictive, preventive, and participatory health. Translational bioinformatics includes research on the development of novel techniques for the integration of biological and clinical data and the evolution of clinical informatics methodology to encompass biological observations. The end product of translational bioinformatics is newly found knowledge from these integrative efforts that can be disseminated to a variety of stakeholders, including biomedical scientists, clinicians, and patients. AMIA Translational bioinformatics
PLOS Computational Biology Translational Bioinformatics

UMLS Unified Medical Language System:  an interdisciplinary field of study that looks at the systems of the human body as part of an integrated whole, incorporating biochemical, physiological, and environment interactions. Systems medicine draws on systems science and systems biology, and considers complex interactions within the human body in light of a patient's genomics, behavior and environment.[1] The earliest uses of the term systems medicine appeared in 1992, in an article on systems medicine and pharmacology by B.J. Zeng [2] and in a paper on systems biomedicine by T. Kamada.[3]   Wikipedia accessed 2018 Sept 2

uncertainty factor: Mathematical adjustments for reasons of safety when knowledge is incomplete. For example, factors used in the calculation of doses that are not harmful (adverse) to people. These factors are applied to the lowest-observed-adverse-effect-level (LOAEL) or the no-observed-adverse-effect-level (NOAEL) to derive a minimal risk level (MRL). Uncertainty factors are used to account for variations in people's sensitivity, for differences between animals and humans, and for differences between a LOAEL and a NOAEL. Scientists use uncertainty factors when they have some, but not all, the information from animal or human studies to decide whether an exposure will cause harm to people [also sometimes called a safety factor].

Universal Trial Number UTN: The aim of the Universal Trial Number (UTN) is to facilitate the unambiguous identification of clinical trials. The UTN is not a registration number.  The UTN is a number that should be obtained early in the history of the trial.  WHO International Clinical Trials Registry Platform (ICTRP)  The Universal Trial Number (UTN)   

wearable technologies, wearables: Biomaterials & Medical devices

Clinical informatics resources
AMIA American Medical Informatics Association, Glossary of Acronyms and Terms commonly used in informatics, 2013
ASHP, SOPIT Glossary of Informatics Terms
CAP College of American Pathologists, Glossary of clinical Informatics terms
Coiera, Enrico, Health Informatics Glossary
MedDRA Medical Dictionary for Regulatory Activities, Maintenance and Support Services Organization. An international medical terminology designed to support the classification, retrieval, presentation, and communication of medical information throughout the medical product regulatory cycle. 

Informatics Conferences
BioIT World Expo
Molecular Medicine Tri Conference BioIT World West

Molecular Medicine Conference Digital Health

BioIT World magazine   
   BioIT World archives
Clinical Research News

How to look for other unfamiliar  terms

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