Health informatics

Last updated
Electronic patient chart from a health information system Sshot fever.png
Electronic patient chart from a health information system

Health informatics (also called health care informatics, healthcare informatics, medical informatics, nursing informatics, clinical informatics, or biomedical informatics) is information engineering applied to the field of health care, essentially the management and use of patient healthcare information. It is a multidisciplinary field [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 bio-medicine. Health informatics tools include computers, clinical guidelines, formal medical terminologies, and information and communication systems, among 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]

Informatics is a branch of information engineering. It involves the practice of information processing and the engineering of information systems, and as an academic field it is an applied form of information science. The field considers the interaction between humans and information alongside the construction of interfaces, organisations, technologies and systems. As such, the field of informatics has great breadth and encompasses many subspecialties, including disciplines of computer science, information systems, information technology and statistics. Since the advent of computers, individuals and organizations increasingly process information digitally. This has led to the study of informatics with computational, mathematical, biological, cognitive and social aspects, including study of the social impact of information technologies.

Health care Prevention of disease and promotion of wellbeing

Health care or healthcare is the maintenance or improvement of health via the prevention, diagnosis, and treatment of disease, illness, injury, and other physical and mental impairments in people. Health care is delivered by health professionals in allied health fields. Physicians and physician associates are a part of these health professionals. Dentistry, midwifery, nursing, medicine, optometry, audiology, pharmacy, psychology, occupational therapy, physical therapy and other health professions are all part of health care. It includes work done in providing primary care, secondary care, and tertiary care, as well as in public health.

Health information technology is information technology applied to health and health care. It supports health information management across computerized systems and the secure exchange of health information between consumers, providers, payers, and quality monitors. Based on an often-cited 2008 report on a small series of studies conducted at four sites that provide ambulatory care – three U.S. medical centers and one in the Netherlands – the use of electronic health records (EHRs) was viewed as the most promising tool for improving the overall quality, safety and efficiency of the health delivery system. According to a 2006 report by the Agency for Healthcare Research and Quality, broad and consistent utilization of HIT will:

Contents

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]

Subspecialities

Healthcare informatics includes sub-fields of clinical informatics, such as pathology informatics, clinical research informatics (see section below), imaging informatics, public health informatics, community health informatics, home health informatics, nursing informatics, medical informatics, consumer health informatics, clinical bioinformatics, and informatics for education and research in health and medicine, pharmacy informatics. [9] [10] [11] [12] [13] [14] [ excessive citations ]

Imaging informatics, also known as radiology informatics or medical imaging informatics, is a subspecialty of biomedical informatics that aims to improve the efficiency, accuracy, usability and reliability of medical imaging services within the healthcare enterprise. It is devoted to the study of how information about and contained within medical images is retrieved, analyzed, enhanced, and exchanged throughout the medical enterprise.

Public health informatics has been defined as the systematic application of information and computer science and technology to public health practice, research, and learning. It is one of the subdomains of health informatics.

Consumer health informatics (CHI) is a sub-branch of health informatics that helps bridge the gap between patients and health resources. It is defined by the American Medical Informatics Association as "the field devoted to informatics from multiple consumer or patient views". The Consumer Health Informatics Working Group (CHIWG) of the International Medical Informatics Association (IMIA) define it as "the use of modern computers and telecommunications to support consumers in obtaining information, analyzing unique health care needs and helping them make decisions about their own health".

Healthcare informatics

Clinical informatics

Clinical informatics is concerned with the use of information in health care by and for clinicians. [15] [16]

A clinician is a health care professional that works as a primary care giver of a patient in a hospital, skilled nursing facility, clinic, or patient's home. A clinician diagnoses and treats patients. For example, physicians, nurse practitioners, clinical pharmacist and physician assistants are clinicians; a speech-language pathologist (SLP) is a clinician, a speech-language pathology assistant (SLPA) is not. Clinicians take comprehensive exams to be licensed and some complete graduate degrees in their field of expertise. Although a clinician must follow evidence-based best-practices and other professional codes of conduct set by laws and professional governing bodies, a clinician can choose to practice without another's supervision.

Clinical informaticians, also known as clinical informaticists, transform health care by analyzing, designing, implementing, and evaluating information and communication systems that enhance individual and population health outcomes, improve [patient] care, and strengthen the clinician-patient relationship. Clinical informaticians use their knowledge of patient care combined with their understanding of informatics concepts, methods, and health informatics tools to:

Clinical research is a branch of healthcare science that determines the safety and effectiveness (efficacy) of medications, devices, diagnostic products and treatment regimens intended for human use. These may be used for prevention, treatment, diagnosis or for relieving symptoms of a disease. Clinical research is different from clinical practice. In clinical practice established treatments are used, while in clinical research evidence is collected to establish a treatment.

Information that which informs; the answer to a question of some kind; that from which data and knowledge can be derived

Information is the resolution of uncertainty; it is that which answers the question of "what an entity is" and is thus that which specifies the nature of that entity, as well as the essentiality of its properties. Information is associated with data and knowledge, as data is meaningful information and represents the values attributed to parameters, and knowledge signifies understanding of an abstract or concrete concept. The existence of information is uncoupled with an observer, which refers to that which accesses information to discern that which it specifies; information exists beyond an event horizon for example, and in the case of knowledge, the information itself requires a cognitive observer to be accessed.

To provide the safe and effective delivery of medical care, virtually all clinical staff use a number of front-line Health Informatics Tools in their day-to-day operations. The need for standardization and refined development of these tools is underscored by the HITECH Act and other efforts to develop electronic medical records.

Clinicians collaborate with other health care and information technology professionals to develop health informatics tools which promote patient care that is safe, efficient, effective, timely, patient-centered, and equitable. Many clinical informaticists are also computer scientists.

In October 2011 American Board of Medical Specialties (ABMS), the organization overseeing the certification of specialist MDs in the United States, announced the creation of MD-only physician certification in clinical informatics. The first examination for board certification in the subspecialty of clinical informatics was offered in October 2013 by American Board of Preventive Medicine (ABPM) with 432 passing to become the 2014 inaugural class of Diplomates in clinical informatics. [17]

Fellowship programs exist for physicians who wish to become board-certified in clinical informatics. Physicians must have graduated from a medical school in the United States or Canada, or a school located elsewhere that is approved by the ABPM. In addition, they must complete a primary residency program such as Internal Medicine (or any of the 24 subspecialties recognized by the ABMS) and be eligible to become licensed to practice medicine in the state where their fellowship program is located. [18] The fellowship program is 24 months in length, with fellows dividing their time between Informatics rotations, didactic method, research, and clinical work in their primary specialty.

Integrated data repository

Example IDR schema OMOP (IMEDS) Common Data Model (version 4).png
Example IDR schema
Achilles tool for data characterization of a healthcare dataset Achilles tool.png
Achilles tool for data characterization of a healthcare dataset

One of the fundamental elements of biomedical and translation research is the use of integrated data repositories. A survey conducted in 2010 defined "integrated data repository" (IDR) as a data warehouse incorporating various sources of clinical data to support queries for a range of research-like functions. [19] Integrated data repositories are complex systems developed to solve a variety of problems ranging from identity management, protection of confidentiality, semantic and syntactic comparability of data from different sources, and most importantly convenient and flexible query. [20] Development of the field of clinical informatics led to the creation of large data sets with electronic health record data integrated with other data (such as genomic data). Types of data repositories include operational data stores (ODSs), clinical data warehouses (CDWs), clinical data marts, and clinical registries. [21] Operational data stores established for extracting, transferring and loading before creating warehouse or data marts. [21] Clinical registries repositories have long been in existence, but their contents are disease specific and sometimes considered archaic. [21] Clinical data stores and clinical data warehouses are considered fast and reliable. Though these large integrated repositories have impacted clinical research significantly, it still faces challenges and barriers. One big problem is the requirement for ethical approval by the institutional review board (IRB) for each research analysis meant for publication. [22] Some research resources do not require IRB approval. For example, CDWs with data of deceased patients have been de-identified and IRB approval is not required for their usage. [22] [19] [21] [20] Another challenge is data quality. Methods that adjust for bias (such as using propensity score matching methods) assume that a complete health record is captured. Tools that examine data quality (e.g., point to missing data) help in discovering data quality problems. [23]

Clinical research informatics

Clinical research informatics (CRI) is a sub-field of health informatics that tries to improve the efficiency of clinical research by using informatics methods. Some of the problems tackled by CRI are: creation of data warehouses of healthcare data that can be used for research, support of data collection in clinical trials by the use of electronic data capture systems, streamlining ethical approvals and renewals (in US the responsible entity is the local institutional review board), maintenance of repositories of past clinical trial data (de-identified).

CRI is a fairly new branch of informatics and has met growing pains as any up and coming field does. Some issue CRI faces is the ability for the statisticians and the computer system architects to work with the clinical research staff in designing a system and lack of funding to support the development of a new system. Researchers and the informatics team have a difficult time coordinating plans and ideas in order to design a system that is easy to use for the research team yet fits in the system requirements of the computer team. The lack of funding can be a hindrance to the development of the CRI. Many organizations who are performing research are struggling to get financial support to conduct the research, much less invest that money in an informatics system that will not provide them any more income or improve the outcome of the research (Embi, 2009).

Common data elements (CDEs) in clinical research

Ability to integrate data from multiple clinical trials is an important part of clinical research informatics. Initiatives, such as PhenX and Patient-Reported Outcomes Measurement Information System triggered a general effort to improve secondary use of data collected in past human clinical trials. CDE initiatives, for example, try to allow clinical trial designers to adopt standardized research instruments (electronic case report forms). [24]

Data sharing platforms for clinical study data

A parallel effort to standardizing how data is collected are initiatives that offer de-identified patient level clinical study data to be downloaded by researchers who wish to re-use this data. Examples of such platforms are Project Data Sphere, [25] dbGaP, ImmPort [26] or Clinical Study Data Request. [27] Informatics issues in data formats for sharing results (plain CSV files, FDA endorsed formats, such as CDISC Study Data Tabulation Model) are important challenges within the field of clinical research informatics.

Human bioinformatics

Translational bioinformatics

With the completion of the human genome and the recent advent of high throughput sequencing and genome-wide association studies of single nucleotide polymorphic organisms, the fields of molecular bioinformatics, bio-statistics, statistical genetics and clinical informatics are converging into the emerging field of translational bioinformatics. [28] [29] [30]
The relationship between bioinformatics and health informatics, while conceptually related under the umbrella of biomedical informatics, [31] has not always been very clear. The TBI community is specifically motivated with the development of approaches to identify linkages between fundamental biological and clinical information.
Along with complementary areas of emphasis, such as those focused on developing systems and approaches within clinical research contexts, [32] insights from TBI may enable a new paradigm for the study and treatment of disease.

Translational Bioinformatics (TBI) is a relatively new field that surfaced in the year of 2000 when human genome sequence was released. [33] The commonly used definition of TBI is lengthy and could be found on the AMIA website. [34] In simpler terms, TBI could be defined as a collection of colossal amounts of health related data (biomedical and genomic) and translation of the data into individually tailored clinical entities. [33] Today, TBI field is categorized into four major themes that are briefly described below:

  1. Clinical big data
    Clinical big data is a collection of electronic health records that are used for innovations. The evidence-based approach that is currently practiced in medicine is suggested to be merged with the practice-based medicine to achieve better outcomes for patients. As CEO of California-based cognitive computing firm Apixio, Darren Schutle, explains that the care can be better fitted to the patient if the data could be collected from various medical records, merged, and analyzed. Further, the combination of similar profiles can serve as a basis for personalized medicine pointing to what works and what does not for certain condition (Marr, 2016).
  2. Genomics in clinical care
    Genomic data are used to identify the genes involvement in unknown or rare conditions/syndromes. Currently, the most vigorous area of using genomics is oncology. The identification of genomic sequencing of cancer may define reasons of drug(s) sensitivity and resistance during oncological treatment processes. [33]
  3. Omics for drugs discovery and repurposing
    Repurposing of the drug is an appealing idea that allows the pharmaceutical companies to sell an already approved drug to treat a different condition/disease that the drug was not initially approved for by the FDA. The observation of “molecular signatures in disease and compare those to signatures observed in cells” points to the possibility of a drug ability to cure and/or relieve symptoms of a disease. [33]
  4. Personalized genomic testing
    In the USA, several companies offer direct-to-consumer (DTC) genetic testing. The company that performs the majority of testing is called 23andMe. Utilizing genetic testing in health care raises many ethical, legal and social concerns; one of the main questions is whether the healthcare providers are ready to include patient-supplied genomic information while providing care that is unbiased (despite the intimate genomic knowledge) and a high quality. The documented examples of incorporating such information into a healthcare delivery showed both positive and negative impacts on the overall healthcare related outcomes. [33]

Computational health informatics

Computational health informatics is a branch of computer science that deals specifically with computational techniques that are relevant in healthcare. Computational health informatics is also a branch of health informatics, but is orthogonal to much of the work going on in health informatics because computer scientists' interest is mainly in understanding fundamental properties of computation. Health informatics, on the other hand, is primarily concerned with understanding fundamental properties of medicine that allow for the intervention of computers. The health domain provides an extremely wide variety of problems that can be tackled using computational techniques, and computer scientists are attempting to make a difference in medicine by studying the underlying principles of computer science that will allow for meaningful (to medicine) algorithms and systems to be developed. Thus, computer scientists working in computational health informatics and health scientists working in medical health informatics combine to develop the next generation of healthcare technologies.

Using computers to analyze health data has been around since the 1950s, but it wasn't until the 1990s that the first sturdy models appeared. The development of the Internet has helped develop computational health informatics over the past decade. Computer models are used to examine various topics such as how exercise affects obesity, healthcare costs, and many more. [35]

Examples of projects in computational health informatics include the COACH project. [36] [37]

Informatics for education and research in health and medicine

Clinical research informatics

Clinical research informatics (CRI) is an amalgamation of clinical and research informatics. Featuring both clinical and research informatics, CRI has a vital role in clinical research, patient care, and the building of healthcare system (Katzan & Rudick, 2012). CRI is one of the rapidly growing subdivisions of biomedical informatics which plays an important role in developing new informatics theories, tools, and solutions to accelerate the full transitional continuum (Kahn & Weng, 2012). Evolution of CRI was extremely important in Informatics as there was an extraordinary increase in the scope and pace of clinical and translational science advancements (Katzan & Rudick, 2012). Clinical research informatics takes the core foundations, principles, and technologies related to Health Informatics, and applies these to clinical research contexts. [38] As such, CRI is a sub-discipline of health informatics, and interest and activities in CRI have increased greatly in recent years given the overwhelming problems associated with the explosive growth of clinical research data and information. [39] There are a number of activities within clinical research that CRI supports, including:

History

Worldwide use of computer technology in medicine began in the early 1950s with the rise of the computers. [41] In 1949, Gustav Wagner established the first professional organization for informatics in Germany. [42] The prehistory, history, and future of medical information and health information technology are discussed in reference. [43] Specialized university departments and Informatics training programs began during the 1960s in France, Germany, Belgium and The Netherlands. Medical informatics research units began to appear during the 1970s in Poland and in the U.S. [42] Since then the development of high-quality health informatics research, education and infrastructure has been a goal of the U.S. and the European Union. [42]

Early names for health informatics included medical computing, biomedical computing, medical computer science, computer medicine, medical electronic data processing, medical automatic data processing, medical information processing, medical information science, medical software engineering, and medical computer technology.[ citation needed ]

The health informatics community is still growing, it is by no means a mature profession, but work in the UK by the voluntary registration body, the UK Council of Health Informatics Professions has suggested eight key constituencies within the domain—information management, knowledge management, portfolio/program/project management, ICT, education and research, clinical informatics, health records(service and business-related), health informatics service management. These constituencies accommodate professionals in and for the NHS, in academia and commercial service and solution providers.

Since the 1970s the most prominent international coordinating body has been the International Medical Informatics Association (IMIA). [44]

In the United States

Even though the idea of using computers in medicine emerged as technology advanced in the early 20th century, it was not until the 1950s that informatics began to have an effect in the United States. [41]

The earliest use of electronic digital computers for medicine was for dental projects in the 1950s at the United States National Bureau of Standards by Robert Ledley. [45] During the mid-1950s, the United States Air Force (USAF) carried out several medical projects on its computers while also encouraging civilian agencies such as the National Academy of Sciences – National Research Council (NAS-NRC) and the National Institutes of Health (NIH) to sponsor such work. [46] In 1959, Ledley and Lee B. Lusted published "Reasoning Foundations of Medical Diagnosis," a widely read article in Science , which introduced computing (especially operations research) techniques to medical workers. Ledley and Lusted's article has remained influential for decades, especially within the field of medical decision making. [47]

Guided by Ledley's late 1950s survey of computer use in biology and medicine (carried out for the NAS-NRC), and by his and Lusted's articles, the NIH undertook the first major effort to introduce computers to biology and medicine. This effort, carried out initially by the NIH's Advisory Committee on Computers in Research (ACCR), chaired by Lusted, spent over $40 million between 1960 and 1964 in order to establish dozens of large and small biomedical research centers in the US. [46]

One early (1960, non-ACCR) use of computers was to help quantify normal human movement, as a precursor to scientifically measuring deviations from normal, and design of prostheses. [48] The use of computers (IBM 650, 1620, and 7040) allowed analysis of a large sample size, and of more measurements and subgroups than had been previously practical with mechanical calculators, thus allowing an objective understanding of how human locomotion varies by age and body characteristics. A study co-author was Dean of the Marquette University College of Engineering; this work led to discrete Biomedical Engineering departments there and elsewhere.

The next steps, in the mid-1960s, were the development (sponsored largely by the NIH) of expert systems such as MYCIN and Internist-I. In 1965, the National Library of Medicine started to use MEDLINE and MEDLARS. Around this time, Neil Pappalardo, Curtis Marble, and Robert Greenes developed MUMPS (Massachusetts General Hospital Utility Multi-Programming System) in Octo Barnett's Laboratory of Computer Science [49] at Massachusetts General Hospital in Boston, another center of biomedical computing that received significant support from the NIH. [50] In the 1970s and 1980s it was the most commonly used programming language for clinical applications. The MUMPS operating system was used to support MUMPS language specifications. As of 2004, a descendent of this system is being used in the United States Veterans Affairs hospital system. The VA has the largest enterprise-wide health information system that includes an electronic medical record, known as the Veterans Health Information Systems and Technology Architecture (VistA). A graphical user interface known as the Computerized Patient Record System (CPRS) allows health care providers to review and update a patient's electronic medical record at any of the VA's over 1,000 health care facilities.

During the 1960s, Morris Collen, a physician working for Kaiser Permanente's Division of Research, developed computerized systems to automate many aspects of multi-phased health checkups. These systems became the basis the larger medical databases Kaiser Permanente developed during the 1970s and 1980s. [51] The American College of Medical Informatics (ACMI) has since 1993 annually bestowed the Morris F. Collen, MD Medal for Outstanding Contributions to the Field of Medical Informatics. [52] Kaiser permanente

In the 1970s a growing number of commercial vendors began to market practice management and electronic medical records systems. Although many products exist, only a small number of health practitioners use fully featured electronic health care records systems. In 1970, Warner V. Slack, MD, and Howard L. Bleich, MD, co-founded the academic division of clinical informatics [53] at Beth Israel Deaconess Medical Center and Harvard Medical School. Warner Slack is a pioneer of the development of the electronic patient medical history, [54] and in 1977 Dr. Bleich created the first user-friendly search engine for the worlds biomedical literature. [55] In 2002, Dr. Slack and Dr. Bleich were awarded the Morris F. Collen Award for their pioneering contributions to medical informatics. [56]

Computerized systems involved in patient care have led to a number of changes. Such changes have led to improvements in electronic health records which are now capable of sharing medical information among multiple healthcare stakeholders(Zahabi, Kaber, & Swangnetr, 2015); thereby, supporting the flow of patient information through various modalities of care.

Computer use today involves a broad ability which includes but isn't limited to physician diagnosis and documentation, patient appointment scheduling, and billing. Many researchers in the field have identified an increase in the quality of healthcare systems, decreased errors by healthcare workers, and lastly savings in time and money (Zahabi, Kaber, & Swangnetr, 2015). The system, however, is not perfect and will continue to require improvement. Frequently cited factors of concern involve usability, safety, accessibility, and user-friendliness (Zahabi, Kaber, & Swangnetr, 2015). As leaders in the field of medical informatics improve upon the aforementioned factors of concern, the overall provision of health care will continue to improve. [57] [58]

Homer R. Warner, one of the fathers of medical informatics, [59] founded the Department of Medical Informatics at the University of Utah in 1968. The American Medical Informatics Association (AMIA) has an award named after him on application of informatics to medicine.

Informatics certifications

Like other IT training specialties, there are Informatics certifications available to help informatics professionals stand out and be recognized. The American Nurses Credentialing Center (ANCC) offers a board certification in Nursing Informatics. [60] For Radiology Informatics, the CIIP (Certified Imaging Informatics Professional) certification was created by ABII (The American Board of Imaging Informatics) which was founded by SIIM (the Society for Imaging Informatics in Medicine) and ARRT (the American Registry of Radiologic Technologists) in 2005. The CIIP certification requires documented experience working in Imaging Informatics, formal testing and is a limited time credential requiring renewal every five years. The exam tests for a combination of IT technical knowledge, clinical understanding, and project management experience thought to represent the typical workload of a PACS administrator or other radiology IT clinical support role. [61] Certifications from PARCA (PACS Administrators Registry and Certifications Association) are also recognized. The five PARCA certifications are tiered from entry-level to architect level. The American Health Information Management Association offers credentials in medical coding, analytics, and data administration, such as Registered Health Information Administrator and Certified Coding Associate. [62]

Certifications are widely requested by employers in health informatics, and overall the demand for certified informatics workers in the United States is outstripping supply. [63] The American Health Information Management Association reports that only 68% of applicants pass certification exams on the first try. [64]

In 2017, a consortium of health informatics trainers (composed of MEASURE Evaluation, Public Health Foundation India, University of Pretoria, Kenyatta University, and the University of Ghana) identified the following areas of knowledge as a curriculum for the digital health workforce, especially in low- and middle-income countries: clinical decision support; telehealth; privacy, security, and confidentiality; workflow process improvement; technology, people, and processes; process engineering; quality process improvement and health information technology; computer hardware; software; databases; data warehousing; information networks; information systems; information exchange; data analytics; and usability methods. [65]

In the UK

The broad history of health informatics has been captured in the book UK Health Computing: Recollections and reflections, Hayes G, Barnett D (Eds.), BCS (May 2008) by those active in the field, predominantly members of BCS Health and its constituent groups. The book describes the path taken as 'early development of health informatics was unorganized and idiosyncratic'. In the early 1950s, it was prompted by those involved in NHS finance and only in the early 1960s did solutions including those in pathology (1960), radiotherapy (1962), immunization (1963), and primary care (1968) emerge. Many of these solutions, even in the early 1970s were developed in-house by pioneers in the field to meet their own requirements. In part, this was due to some areas of health services (for example the immunization and vaccination of children) still being provided by Local Authorities. Interesting, this is a situation which the coalition government proposes broadly to return to in the 2010 strategy Equity and Excellence: Liberating the NHS (July 2010); stating:

"We will put patients at the heart of the NHS, through an information revolution and greater choice and control' with shared decision-making becoming the norm: 'no decision about me without me' and patients having access to the information they want, to make choices about their care. They will have increased control over their own care records."

These types of statements present a significant opportunity for health informaticians to come out of the back-office and take up a front-line role in supporting clinical practice, and the business of care delivery. The UK health informatics community has long played a key role in the international activity, joining TC4 of the International Federation of Information Processing (1969) which became IMIA (1979). Under the aegis of BCS Health, Cambridge was the host for the first EFMI Medical Informatics Europe (1974) conference and London was the location for IMIA's tenth global congress (MEDINFO2001).

Current state and policy initiatives

Argentina

Since 1997, the Buenos Aires Biomedical Informatics Group, a nonprofit group, represents the interests of a broad range of clinical and non-clinical professionals working within the Health Informatics sphere. Its purposes are:

The Argentinian health system is heterogeneous in its function, and because of that the informatics developments show a heterogeneous stage. Many private Health Care center have developed systems, such as the Hospital Aleman of Buenos Aires, or the Hospital Italiano de Buenos Aires that also has a residence program for health informatics.

Brazil

The first applications of computers to medicine and healthcare in Brazil started around 1968, with the installation of the first mainframes in public university hospitals, and the use of programmable calculators in scientific research applications. Minicomputers, such as the IBM 1130 were installed in several universities, and the first applications were developed for them, such as the hospital census in the School of Medicine of Ribeirão Preto and patient master files, in the Hospital das Clínicas da Universidade de São Paulo, respectively at the cities of Ribeirão Preto and São Paulo campuses of the University of São Paulo. In the 1970s, several Digital Corporation and Hewlett Packard minicomputers were acquired for public and Armed Forces hospitals, and more intensively used for intensive-care unit, cardiology diagnostics, patient monitoring and other applications. In the early 1980s, with the arrival of cheaper microcomputers, a great upsurge of computer applications in health ensued, and in 1986 the Brazilian Society of Health Informatics was founded, the first Brazilian Congress of Health Informatics was held, and the first Brazilian Journal of Health Informatics was published. In Brazil, two universities are pioneers in teaching and research in Medical Informatics, both the University of Sao Paulo and the Federal University of Sao Paulo offer undergraduate programs highly qualified in the area as well as extensive graduate programs (MSc and PhD). In 2015 the Universidade Federal de Ciências da Saúde de Porto Alegre, Rio Grande do Sul, also started to offer undergraduate program.

Canada

Health Informatics projects in Canada are implemented provincially, with different provinces creating different systems. A national, federally funded, not-for-profit organization called Canada Health Infoway was created in 2001 to foster the development and adoption of electronic health records across Canada. As of December 31, 2008 there were 276 EHR projects under way in Canadian hospitals, other health-care facilities, pharmacies and laboratories, with an investment value of $1.5-billion from Canada Health Infoway. [66]

Provincial and territorial programmes include the following:

United States

In 2004, President George W. Bush signed Executive Order 13335, [68] creating the Office of the National Coordinator for Health Information Technology (ONCHIT) as a division of the U.S. Department of Health and Human Services (HHS). The mission of this office is widespread adoption of interoperable electronic health records (EHRs) in the US within 10 years. See quality improvement organizations for more information on federal initiatives in this area.

In 2014 The Department of Education approved an advanced Health Informatics Undergraduate program that was submitted by The University of South Alabama. The program is designed to provide specific Health Informatics education, and is the only program in the country with a Health Informatics Lab. The program is housed in The School of Computing in Shelby Hall, a recently completed $50 million state of the art teaching facility. The University of South Alabama awarded David L. Loeser on May 10, 2014 with the first Health Informatics degree. The program currently is scheduled to have 100+ students awarded by 2016.

The Certification Commission for Healthcare Information Technology (CCHIT), a private nonprofit group, was funded in 2005 by the U.S. Department of Health and Human Services to develop a set of standards for electronic health records (EHR) and supporting networks, and certify vendors who meet them. In July 2006, CCHIT released its first list of 22 certified ambulatory EHR products, in two different announcements. [69]

Harvard Medical School added a department of biomedical informatics in 2015. [70] The University of Cincinnati in partnership with Cincinnati Children's Hospital Medical Center created a biomedical informatics (BMI) Graduate certificate program and in 2015 began a BMI PhD program. [71] [72] [73] The joint program allows for researchers and students to observe the impact their work has on patient care directly as discoveries are translated from bench to bedside.

Europe

The European Union's Member States are committed to sharing their best practices and experiences to create a European eHealth Area, thereby improving access to and quality health care at the same time as stimulating growth in a promising new industrial sector. The European eHealth Action Plan plays a fundamental role in the European Union's strategy. Work on this initiative involves a collaborative approach among several parts of the Commission services. [74] [75] The European Institute for Health Records is involved in the promotion of high quality electronic health record systems in the European Union. [76]

UK

There are different models of health informatics delivery in each of the home countries (England, Scotland, Northern Ireland and Wales) but some bodies like UKCHIP ref>UKCHIP</ref> (see below) operate for those 'in and for' all the home countries and beyond.

England

NHS informatics in England was contracted out to several vendors for national health informatics solutions under the National Programme for Information Technology (NPfIT) label in the early to mid-2000s, under the auspices of NHS Connecting for Health (part of the Health and Social Care Information Centre as of 1 April 2013). NPfIT originally divided the country into five regions, with strategic 'systems integration' contracts awarded to one of several Local Service Providers (LSP). The various specific technical solutions were required to connect securely with the NHS 'Spine', a system designed to broker data between different systems and care settings. NPfIT fell significantly behind schedule and its scope and design were being revised in real time, exacerbated by media and political lambasting of the Programme's spend (past and projected) against the proposed budget. In 2010 a consultation was launched as part of the new Conservative/Liberal Democrat Coalition Government's White Paper 'Liberating the NHS'. This initiative provided little in the way of innovative thinking, primarily re-stating existing strategies within the proposed new context of the Coalition's vision for the NHS. The degree of computerization in NHS secondary care was quite high before NPfIT, and the programme stagnated further development of the install base – the original NPfIT regional approach provided neither a single, nationwide solution nor local health community agility or autonomy to purchase systems, but instead tried to deal with a hinterland in the middle.

Almost all general practices in England and Wales are computerized under the GP Systems of Choice (GPSoC) [77] programme, and patients have relatively extensive computerized primary care clinical records. System choice is the responsibility of individual general practices and while there is no single, standardized GP system, GPSoC sets relatively rigid minimum standards of performance and functionality for vendors to adhere to. Interoperation between primary and secondary care systems is rather primitive. It is hoped that a focus on interworking (for interfacing and integration) standards will stimulate synergy between primary and secondary care in sharing necessary information to support the care of individuals. Notable successes to date are in the electronic requesting and viewing of test results, and in some areas, GPs have access to digital x-ray images from secondary care systems.

Scotland

Scotland has an approach to the central connection underway which is more advanced than the English one in some ways. Scotland has the GPASS system whose source code is owned by the State, and controlled and developed by NHS Scotland. GPASS was accepted in 1984. It has been provided free to all GPs in Scotland but has developed poorly.[ citation needed ] Discussion of open sourcing it as a remedy is occurring.

Wales

Wales has a dedicated Health Informatics function that supports NHS Wales in leading on the new integrated digital information services and promoting Health Informatics as a career.

Netherlands

In the Netherlands, health informatics is currently a priority for research and implementation. The Netherlands Federation of University medical centers (NFU) [78] has created the Citrienfonds, which includes the programs eHealth and Registration at the Source. [79] The Netherlands also has the national organizations Society for Healthcare Informatics (VMBI) [80] and Nictiz, the national center for standardization and eHealth. [81]

Emerging Directions (European R&D)

The European Commission's preference, as exemplified in the 5th Framework [82] as well as currently pursued pilot projects, [83] is for Free/Libre and Open Source Software (FLOSS) for healthcare. Another stream of research currently focuses on aspects of "big data" in health information systems. For background information on data-related aspects in health informatics see, e.g., the book "Biomedical Informatics" [84] by Andreas Holzinger.

Asia and Oceania

In Asia and Australia-New Zealand, the regional group called the Asia Pacific Association for Medical Informatics (APAMI) [85] was established in 1994 and now consists of more than 15 member regions in the Asia Pacific Region.

Australia

The Australasian College of Health Informatics (ACHI) is the professional association for health informatics in the Asia-Pacific region. It represents the interests of a broad range of clinical and non-clinical professionals working within the health informatics sphere through a commitment to quality, standards and ethical practice. [86] ACHI is an academic institutional member of the International Medical Informatics Association (IMIA) [87] and a full member of the Australian Council of Professions. [88] ACHI is a sponsor of the "e-Journal for Health Informatics", [89] an indexed and peer-reviewed professional journal. ACHI has also supported the "Australian Health Informatics Education Council" (AHIEC) since its founding in 2009. [90]

Although there are a number of health informatics organizations in Australia, the Health Informatics Society of Australia [91] (HISA) is regarded as the major umbrella group and is a member of the International Medical Informatics Association (IMIA). Nursing informaticians were the driving force behind the formation of HISA, which is now a company limited by guarantee of the members. The membership comes from across the informatics spectrum that is from students to corporate affiliates. HISA has a number of branches (Queensland, New South Wales, Victoria and Western Australia) as well as special interest groups such as nursing (NIA), pathology, aged and community care, industry and medical imaging (Conrick, 2006).

China

After 20 years, China performed a successful transition from its planned economy to a socialist market economy. Along this change, China's healthcare system also experienced a significant reform to follow and adapt to this historical revolution. In 2003, the data (released from Ministry of Health of the People's Republic of China (MoH)), indicated that the national healthcare-involved expenditure was up to RMB 662.33 billion totally, which accounted for about 5.56% of nationwide gross domestic products. Before the 1980s, the entire healthcare costs were covered in central government annual budget. Since that, the construct of healthcare-expended supporters started to change gradually. Most of the expenditure was contributed by health insurance schemes and private spending, which corresponded to 40% and 45% of total expenditure, respectively. Meanwhile, the financially governmental contribution was decreased to 10% only. On the other hand, by 2004, up to 296,492 healthcare facilities were recorded in statistic summary of MoH, and an average of 2.4 clinical beds per 1000 people were mentioned as well. [92]

In China
Proportion of nationwide hospitals with HIS in China by 2004 Proportion of nation-wide hospitals with HIS.tif
Proportion of nationwide hospitals with HIS in China by 2004

Along with the development of information technology since the 1990s, healthcare providers realized that the information could generate significant benefits to improve their services by computerized cases and data, for instance of gaining the information for directing patient care and assessing the best patient care for specific clinical conditions. Therefore, substantial resources were collected to build China's own health informatics system. Most of these resources were arranged to construct hospital information system (HIS), which was aimed to minimize unnecessary waste and repetition, subsequently to promote the efficiency and quality-control of healthcare. [93] By 2004, China had successfully spread HIS through approximately 35–40% of nationwide hospitals. [94] However, the dispersion of hospital-owned HIS varies critically. In the east part of China, over 80% of hospitals constructed HIS, in northwest of China the equivalent was no more than 20%. Moreover, all of the Centers for Disease Control and Prevention (CDC) above rural level, approximately 80% of healthcare organisations above the rural level and 27% of hospitals over town level have the ability to perform the transmission of reports about real-time epidemic situation through public health information system and to analysis infectious diseases by dynamic statistics. [95]

China has four tiers in its healthcare system. The first tier is street health and workplace clinics and these are cheaper than hospitals in terms of medical billing and act as prevention centers. The second tier is district and enterprise hospitals along with specialist clinics and these provide the second level of care. The third tier is provisional and municipal general hospitals and teaching hospitals which provided the third level of care. In a tier of its own is the national hospitals which are governed by the Ministry of Health. China has been greatly improving its health informatics since it finally opened its doors to the outside world and joined the World Trade Organization (WTO). In 2001, it was reported that China had 324,380 medical institutions and the majority of those were clinics. The reason for that is that clinics are prevention centers and Chinese people like using traditional Chinese medicine as opposed to Western medicine and it usually works for the minor cases. China has also been improving its higher education in regards to health informatics. At the end of 2002, there were 77 medical universities and medical colleges. There were 48 university medical colleges which offered bachelor, master, and doctorate degrees in medicine. There were 21 higher medical specialty institutions that offered diploma degrees so in total, there were 147 higher medical and educational institutions. Since joining the WTO, China has been working hard to improve its education system and bring it up to international standards. [96] SARS played a large role in China quickly improving its healthcare system. Back in 2003, there was an outbreak of SARS and that made China hurry to spread HIS or Hospital Information System and more than 80% of hospitals had HIS. China had been comparing itself to Korea's healthcare system and figuring out how it can better its own system. There was a study done that surveyed six hospitals in China that had HIS. The results were that doctors didn't use computers as much so it was concluded that it wasn't used as much for clinical practice than it was for administrative purposes. The survey asked if the hospitals created any websites and it was concluded that only four of them had created websites and that three had a third-party company create it for them and one was created by the hospital staff. In conclusion, all of them agreed or strongly agreed that providing health information on the Internet should be utilized. [97]

Standards in China

Collected information at different times, by different participants or systems could frequently lead to issues of misunderstanding, dis-comparing or dis-exchanging. To design an issues-minor system, healthcare providers realized that certain standards were the basis for sharing information and interoperability, however a system lacking standards would be a large impediment to interfere the improvement of corresponding information systems. Given that the standardization for health informatics depends on the authorities, standardization events must be involved with government and the subsequently relevant funding and supports were critical. In 2003, the Ministry of Health released the Development Lay-out of National Health Informatics (2003–2010) [98] indicating the identification of standardization for health informatics which is 'combining adoption of international standards and development of national standards'.

In China, the establishment of standardization was initially facilitated with the development of vocabulary, classification and coding, which is conducive to reserve and transmit information for premium management at national level. By 2006, 55 international/ domestic standards of vocabulary, classification and coding have served in hospital information system. In 2003, the 10th revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10) and the ICD-10 Clinical Modification (ICD-10-CM) were adopted as standards for diagnostic classification and acute care procedure classification. Simultaneously, the International Classification of Primary Care (ICPC) were translated and tested in China 's local applied environment. [99] Another coding standard, named Logical Observation Identifiers Names and Codes (LOINC), was applied to serve as general identifiers for clinical observation in hospitals. Personal identifier codes were widely employed in different information systems, involving name, sex, nationality, family relationship, educational level and job occupation. However, these codes within different systems are inconsistent, when sharing between different regions. Considering this large quantity of vocabulary, classification and coding standards between different jurisdictions, the healthcare provider realized that using multiple systems could generate issues of resource wasting and a non-conflicting national level standard was beneficial and necessary. Therefore, in late 2003, the health informatics group in Ministry of Health released three projects to deal with issues of lacking national health information standards, which were the Chinese National Health Information Framework and Standardization, the Basic Data Set Standards of Hospital Information System and the Basic Data Set Standards of Public Health Information System.

Objectives of Chinese National Health Information Framework and Standardisation
1. Establish national health information framework and identify in what areas standards and guidelines are required
2. Identify the classes, relationships and attributes of national health information framework. Produce a conceptual health data model to cover the scope of the health information framework
3. Create logical data model for specific domains, depicting the logical data entities, the data attributes, and the relationships between the entities according to the conceptual health data model
4. Establish uniform represent standard for data elements according to the data entities and their attributes in conceptual data model and logical data model
5. Circulate the completed health information framework and health data model to the partnership members for review and acceptance
6. Develop a process to maintain and refine the China model and to align with and influence international health data models

[92]

Comparison between China's EHR Standard and Segments of the ASTM E 1384 Standard

Recently, researchers from local universities evaluated the performance of China's Electronic Health Record (EHR) Standard compared with the American Society for Testing and Materials Standard Practice for Content and Structure of Electronic Health Records in the United States (ASTM E 1384 Standard). [100]

China'sEHR standardASTM E 1384 standard
●  H.01 Document identifier, H.02 Service object identifier, H.03 Demographics, H.04 Contact person, H.05 Address, H.06 Contacts●  Seg1 Demographic/Administrative, Seg14A Administrative/Diagnostic

Summary

●  H.07 Medical insurance
●  H.08 Healthcare institution, H.09 Healthcare practitioner●  Seg4 Provider/Practitioners
●  H.10 Event summary●  Seg5 Problem List, Seg14A Administrative/Diagnostic Summary
●  S.01 Chief complaints●  Seg14B Chief Complaint Present Illness/Trauma Care
●  S.02 Physical exam●  Seg9 Assessments/Exams
●  S.03 Present illness history●  Seg14B Chief Complaint Present Illness/Trauma Care
●  S.04 Past medical history●  Seg5 Problem List, Seg6 Immunizations, Seg7 Exposure to Hazardous Substances, Seg8 Family/Prenatal/Cumulative Health/Medical/Dental Nursing History
●  S.05 Specific Exam, S.06 Lab data●  Seg11 Diagnostic Tests
●  S.07 Diagnoses●  Seg5 Problem List, Seg14A Administrative/Diagnostic Summary
●  S.08 Procedures●  Seg14E Procedures
●  S.09 Medications●  Seg12 Medications
●  S.10 Care/treatment plans●  Seg2 Legal Agreements, Seg10 Care/Treatment Plans and Orders, Seg13 Scheduled Appointments/Events
●  S.11 Assessments●  Seg9 Assessments/Exams
●  S.12 Encounters/episodes notes●  Seg14C Progress Notes/Clinical Course, Seg14D Therapies, Seg14F Disposition
●  S.13 Financial information●  Seg3 Financial
●  S.14 Nursing service●  Seg8 Family/Prenatal/Cumulative Health/Medical/Dental Nursing History, Seg14D Therapies
●  S.15 Health guidance●  Seg10 Care/Treatment Plans and Orders
●  S.16 Four diagnostic methods in Traditional Chinese medicine●  Seg11 Diagnostic Tests

The table above demonstrates details of this comparison which indicates certain domains of improvement for future revisions of EHR Standard in China. Meticulously, these deficiencies are listed in the following.

  1. The lack of supporting on privacy and security. The ISO/TS 18308 specifies "The EHR must support the ethical and legal use of personal information, in accordance with established privacy principles and frameworks, which may be culturally or jurisdictionally specific" (ISO 18308: Health Informatics-Requirements for an Electronic Health Record Architecture, 2004). However this China's EHR Standard did not achieve any of the fifteen requirements in the subclass of privacy and security.
  2. The shortage of supporting on different types of data and reference. Considering only ICD-9 is referenced as China's external international coding systems, other similar systems, such as SNOMED CT in clinical terminology presentation, cannot be considered as familiar for Chinese specialists, which could lead to internationally information-sharing deficiency.
  3. The lack of more generic and extensible lower level data structures. China's large and complex EHR Standard was constructed for all medical domains. However, the specific and time-frequent attributes of clinical data elements, value sets and templates identified that this once-for-all purpose cannot lead to practical consequence. [101]

Hong Kong

In Hong Kong a computerized patient record system called the Clinical Management System (CMS) has been developed by the Hospital Authority since 1994. This system has been deployed at all the sites of the authority (40 hospitals and 120 clinics). It is used for up to 2 million transactions daily by 30,000 clinical staff. The comprehensive records of 7 million patients are available on-line in the electronic patient record (ePR), with data integrated from all sites. Since 2004 radiology image viewing has been added to the ePR, with radiography images from any HA site being available as part of the ePR.

The Hong Kong Hospital Authority placed particular attention to the governance of clinical systems development, with input from hundreds of clinicians being incorporated through a structured process. The health informatics section in the Hospital Authority [102] has a close relationship with the information technology department and clinicians to develop healthcare systems for the organization to support the service to all public hospitals and clinics in the region.

The Hong Kong Society of Medical Informatics (HKSMI) was established in 1987 to promote the use of information technology in healthcare. The eHealth Consortium has been formed to bring together clinicians from both the private and public sectors, medical informatics professionals and the IT industry to further promote IT in healthcare in Hong Kong. [103]

India

  • eHCF School of Medical Informatics [104]
  • eHealth-Care Foundation [105]

Malaysia

Since 2010, the Ministry of Health (MoH) has been working on the Malaysian Health Data Warehouse (MyHDW) project. MyHDW aims to meet the diverse needs of timely health information provision and management, and acts as a platform for the standardization and integration of health data from a variety of sources (Health Informatics Centre, 2013). The Ministry has embarked on introducing the electronic Hospital Information Systems (HIS) in several public hospitals including Serdang Hospital, Selayang Hospital and University Kebangsaan Malaysia Medical Centre (UKMMC) under the Ministry of Higher Education (MOHE).

A hospital information system (HIS) is a comprehensive, integrated information system designed to manage the administrative, financial and clinical aspects of a hospital. As an area of medical informatics, the aim of hospital information system is to achieve the best possible support of patient care and administration by electronic data processing. HIS plays a vital role in planning, initiating, organizing and controlling the operations of the subsystems of the hospital and thus provides a synergistic organization in the process.

New Zealand

Health informatics is taught at five New Zealand universities. The most mature and established programme has been offered for over a decade at Otago. [106] Health Informatics New Zealand (HINZ), is the national organisation that advocates for health informatics. HINZ organises a conference every year and also publishes a journal- Healthcare Informatics Review Online.

Saudi Arabia

The Saudi Association for Health Information (SAHI) was established in 2006 [107] to work under direct supervision of King Saud bin Abdulaziz University for Health Sciences to practice public activities, develop theoretical and applicable knowledge, and provide scientific and applicable studies. [108]

Post-Soviet countries

The Russian Federation

The Russian healthcare system is based on the principles of the Soviet healthcare system, which was oriented on mass prophylaxis, prevention of infection and epidemic diseases, vaccination and immunization of the population on a socially protected basis. The current government healthcare system consists of several directions:

  • Preventive health care
  • Primary health care
  • Specialized medical care
  • Obstetrical and gynecologic medical care
  • Pediatric medical care
  • Surgery
  • Rehabilitation/ Health resort treatment

One of the main issues of the post-Soviet medical health care system was the absence of the united system providing optimization of work for medical institutes with one, single database and structured appointment schedule and hence hours-long lines. Efficiency of medical workers might have been also doubtful because of the paperwork administrating or lost book records.

Along with the development of the information systems IT and healthcare departments in Moscow agreed on design of a system that would improve public services of health care institutes. Tackling the issues appearing in the existing system, the Moscow Government ordered that the design of a system would provide simplified electronic booking to public clinics and automate the work of medical workers on the first level.

The system designed for that purposes was called EMIAS (United Medical Information and Analysis System) and presents an electronic health record (EHR) with the majority of other services set in the system that manages the flow of patients, contains outpatient card integrated in the system, and provides an opportunity to manage consolidated managerial accounting and personalized list of medical help. Besides that, the system contains information about availability of the medical institutions and various doctors.

The implementation of the system started in 2013 with the organization of one computerized database for all patients in the city, including a front-end for the users. EMIAS was implemented in Moscow and the region and it is planned that the project should extend to most parts of the country.

Law

Health informatics law deals with evolving and sometimes complex legal principles as they apply to information technology in health-related fields. It addresses the privacy, ethical and operational issues that invariably arise when electronic tools, information and media are used in health care delivery. Health Informatics Law also applies to all matters that involve information technology, health care and the interaction of information. It deals with the circumstances under which data and records are shared with other fields or areas that support and enhance patient care.

As many healthcare systems are making an effort to have patient records more readily available to them via the internet, it is important that providers implement security standards in order to ensure that the patients' information is safe. They have to be able to assure confidentiality, integrity, and security of the people, process, and technology. Since there is also the possibility of payments being made through this system, it is vital that this aspect of their private information will also be protected through cryptography.

The use of technology in health care settings has become popular and this trend is expected to continue. Various healthcare facilities had instigated different kinds of health information technology systems in the provision of patient care, such as electronic health records (EHRs), computerized charting, etc. [109] The growing popularity of health information technology systems and the escalation in the amount of health information that can be exchanged and transferred electronically increased the risk of potential infringement in patients' privacy and confidentiality. [110] This concern triggered the establishment of strict measures by both policymakers and individual facility to ensure patient privacy and confidentiality.

One of the federal laws enacted to safeguard patient's health information (medical record, billing information, treatment plan, etc.) and to guarantee patient's privacy is the Health Insurance Portability and Accountability Act of 1996 or HIPAA. [111] HIPAA gives patients the autonomy and control over their own health records. [111] Furthermore, according to the U.S. Department of Health & Human Services (n.d.), this law enables patients to do the following: [111]

Health and medical informatics journals

Impact factors of scholarly journals publishing digital health (ehealth, mhealth) work Impact Factors of scholarly journals publishing digital health (ehealth, mhealth) work.png
Impact factors of scholarly journals publishing digital health (ehealth, mhealth) work

Computers in Biomedical and Research, published in 1967, was one of the first dedicated journals to health informatics. Other early journals included Computers and Medicine, published by the American Medical Association; Journal of Clinical Computing, published by Gallagher Printing, Journal of Medical Systems, published by Plenum Press, and MD Computing, published by Springer-Veriag. In 1984, Lippincott published the first nursing-specific journal, titled Journal Computers in Nursing, which is now known as Computers Informatics Nursing (CIN) Journal. [112]

Today, there are many health and medical informatics journals. As of September 7, 2016, there are roughly 235 informatics journals listed in the National Library of Medicine (NLM) catalog of journals. [113] Here is a list of some of the top health and medical informatics journals: [114]

See also

Standards/frameworks and governance

Algorithms

Related Research Articles

A hospital information system (HIS) is an element of health informatics that focuses mainly on the administrational needs of hospitals. In many implementations, an HIS is a comprehensive, integrated information system designed to manage all the aspects of a hospital's operation, such as medical, administrative, financial, and legal issues and the corresponding processing of services. Hospital information system is also known as hospital management software (HMS) or hospital management system.

Electronic health record a program used to document a patients medical history on a computer

An electronic health record (EHR), or electronic medical record (EMR), is the systematized collection of patient and population electronically-stored health information in a digital format. These records can be shared across different health care settings. Records are shared through network-connected, enterprise-wide information systems or other information networks and exchanges. EHRs may include a range of data, including demographics, medical history, medication and allergies, immunization status, laboratory test results, radiology images, vital signs, personal statistics like age and weight, and billing information.

A clinical decision support system (CDSS) is a health information technology system that is designed to provide physicians and other health professionals with clinical decision support (CDS), that is, assistance with clinical decision-making tasks. A working definition has been proposed by Robert Hayward of the Centre for Health Evidence: "Clinical decision support systems link health observations with health knowledge to influence health choices by clinicians for improved health care". CDSSs constitute a major topic in artificial intelligence in medicine.

A personal health record (PHR) is a health record where health data and other information related to the care of a patient is maintained by the patient. This stands in contrast to the more widely used electronic medical record, which is operated by institutions and contains data entered by clinicians to support insurance claims. The intention of a PHR is to provide a complete and accurate summary of an individual's medical history which is accessible online. The health data on a PHR might include patient-reported outcome data, lab results, and data from devices such as wireless electronic weighing scales or from a smartphone.

Health information management (HIM) is information management applied to health and health care. It is the practice of acquiring, analyzing and protecting digital and traditional medical information vital to providing quality patient care. With the widespread computerization of health records, traditional (paper-based) records are being replaced with electronic health records (EHRs). The tools of health informatics and health information technology are continually improving to bring greater efficiency to information management in the health care sector. Both hospital information systems and Human Resource for Health Information System (HRHIS) are common implementations of HIM.

The ISO/TC 215 is the International Organization for Standardization's (ISO) Technical Committee (TC) on health informatics. TC 215 works on the standardization of Health Information and Communications Technology (ICT), to allow for compatibility and interoperability between independent systems.

MEDCIN, a system of standardized medical terminology, is a proprietary medical vocabulary and was developed by Medicomp Systems, Inc. MEDCIN is a point-of-care terminology, intended for use in Electronic Health Record (EHR) systems, and it includes over 280,000 clinical data elements encompassing symptoms, history, physical examination, tests, diagnoses and therapy. This clinical vocabulary contains over 38 years of research and development as well as the capability to cross map to leading codification systems such as SNOMED CT, CPT, ICD-9-CM/ICD-10-CM, DSM, LOINC, CDT, CVX, and the Clinical Care Classification (CCC) System for nursing and allied health.

Health informatics in China is about the Health informatics or Medical informatics or Healthcare information system/technology in China.

VistA electronic medical record system developed and used within the U.S. Veterans Health Administration

The Veterans Information Systems and Technology Architecture (VISTA) is the nationwide veterans clinical and business information system of the U.S. Department of Veterans Affairs. VISTA consists of 180 applications for clinical, financial, and administrative functions all integrated within a single database, providing single, authoritative source of data for all veteran-related care and services. The U.S. Congress mandates the VA keep the veterans health record in a single, authoritative, lifelong database, which is VISTA.

The Clinical Care Classification (CCC) System is a standardized, coded nursing terminology that identifies the discrete elements of nursing practice. The CCC provides a unique framework and coding structure. Used for documenting the plan of care; following the nursing process in all health care settings.

Clinical point of care is the point in time when clinicians deliver healthcare products and services to patients at the time of care.

Fast Healthcare Interoperability Resources is a draft standard describing data formats and elements and an application programming interface (API) for exchanging electronic health records. The standard was created by the Health Level Seven International (HL7) health-care standards organization.

Medical device connectivity is the establishment and maintenance of a connection through which data is transferred between a medical device, such as a patient monitor, and an information system. The term is used interchangeably with biomedical device connectivity or biomedical device integration. By eliminating the need for manual data entry, potential benefits include faster and more frequent data updates, diminished human error, and improved workflow efficiency.

Health care analytics is a term used to describe the healthcare analysis activities that can be undertaken as a result of data collected from four areas within healthcare; claims and cost data, pharmaceutical and research and development (R&D) data, clinical data, and patient behavior and sentiment data (patient behaviors and preferences,. Health care analytics is a growing industry in the United States, expected to grow to more than $31 billion by 2022. The industry focuses on the areas of clinical analysis, financial analysis, supply chain analysis, as well as, fraud and HR analysis.

The Master of Healthcare Informatics is a master's-level professional degree granted to students who complete a course of study in the knowledge and competencies needed for careers in health informatics, involving the management of patient and public health data for the purposes of collection, retrieval and utilization for the purpose of improving patient care and reducing healthcare costs. Programs can differ according to setting; although practitioner-teacher model programs are typically found in colleges of medicine. Non-health science faculties have also started to offer programmes that specialize in health informatics; for instance, Master of Business Administration (MBA) in Health Informatics and Master of Commerce in Health Informatics.

Dipak Kalra

Professor Dipak Kalra is President of the European Institute for Health Records and of the European Institute for Innovation through Health Data. He undertakes international research and standards development, and advises on adoption strategies, relating to Electronic Health Records.

Health data is any data "related to health conditions, reproductive outcomes, causes of death, and quality of life" for an individual or population. Health data includes clinical metrics along with environmental, socioeconomic, and behavioral information pertinent to health and wellness. A plurality of health data are collected and used when individuals interact with health care systems. This data, collected by health care providers, typically includes a record of services received, conditions of those services, and clinical outcomes or information concerning those services. Historically, most health data have been sourced from this framework. The advent of eHealth and advances in health information technology, however, have expanded the collection and use of health data—but have also engendered new security, privacy, and ethical concerns. The increasing collection and use of health data by patients is a major component of digital health.

Federal and state governments, insurance companies and other large medical institutions are heavily promoting the adoption of electronic health records. The US Congress included a formula of both incentives and penalties for EMR/EHR adoption versus continued use of paper records as part of the Health Information Technology for Economic and Clinical Health (HITECH) Act, enacted as part of the, American Recovery and Reinvestment Act of 2009.

References

  1. Nadri H, Rahimi B, Timpka T, Sedghi S (August 2017). "The Top 100 Articles in the Medical Informatics: a Bibliometric Analysis". Journal of Medical Systems. 41 (10): 150. doi:10.1007/s10916-017-0794-4. PMID   28825158.
  2. "NLM Definition". NLM.
  3. O'donoghue J, Herbert J (2012). "Data management within mHealth environments: Patient sensors, mobile devices, and databases". Journal of Data and Information Quality. 4 (1): 5.
  4. Mettler T, Raptis DA (June 2012). "What constitutes the field of health information systems? Fostering a systematic framework and research agenda". Health Informatics Journal. 18 (2): 147–56. doi:10.1177/1460458212452496. PMID   22733682.
  5. Popularity of usage of software in homeopathy is shown in example video of homeopathic repertorisation: Shilpa Bhouraskar, Working quick acute cases on Homeopathic Software (YouTube)
  6. O'Donoghue, John; et al. (2011). "Modified early warning scorecard: the role of data/information quality within the decision making process". Electronic Journal Information Systems Evaluation. 14 (1).
  7. "35.240.80: IT applications in health care technology". ISO . Retrieved 2008-06-15.
  8. Fraser, Ross. "ISO 27799: Security management in health using ISO/IEC 17799" (PDF). Archived from the original (PDF) on 2008-12-17. Retrieved 2008-06-15.
  9. American Society of Health-System Pharmacists (2007). "ASHP statement on the pharmacist's role in informatics". American Journal of Health-System Pharmacy. 64 (2): 200–03. doi:10.2146/ajhp060364.
  10. "ASHP statement on the pharmacy technician's role in pharmacy informatics". American Journal of Health-System Pharmacy. 71 (3): 247–50. February 2014. doi:10.1093/ajhp/71.3.247. PMID   24429021.
  11. Troiano D (1999). "A primer on pharmacy information systems". Journal of Healthcare Information Management. 13 (3): 41–52. PMID   10787600.
  12. Bates DW (2000). "Using information technology to reduce rates of medication errors in hospitals". British Medical Journal. 320 (7237): 788–91. doi:10.1136/bmj.320.7237.788. PMC   1117776 . PMID   10720369.
  13. Frye, Julie (2012). "Computers in pharmaceutical management". MDS – 3: Managing Access to Medicines and Health Technologies (3rd ed.). Arlington, Virginia: Management Sciences for Health. pp. 973–96.
  14. Holler J (January 14, 2013). "The role of information technology in advancing pharmacy practice models to improve patient safety". Pharmacy Times: 1–6.
  15. Gardner RM, Overhage JM, Steen EB, Munger BS, Holmes JH, Williamson JJ, Detmer DE (2009). "Core content for the subspecialty of clinical informatics". Journal of the American Medical Informatics Association. 16 (2): 153–7. doi:10.1197/jamia.M3045. PMC   2649328 . PMID   19074296.
  16. Safran C, Shabot MM, Munger BS, Holmes JH, Steen EB, Lumpkin JR, Detmer DE (2009). "Program requirements for fellowship education in the subspecialty of clinical informatics". Journal of the American Medical Informatics Association. 16 (2): 158–66. doi:10.1197/jamia.M3046. PMC   2649323 . PMID   19074295.
  17. "Clinical Informatics 2014 Diplomats". American Board of Preventive Medicine. December 2013. Archived from the original on 8 January 2014. Retrieved 7 January 2014.
  18. "Clinical Informatics Board Certification" (PDF). American Board of Preventive Medicine. 1 January 2013. Archived from the original (PDF) on 29 December 2013. Retrieved 7 January 2014.
  19. 1 2 MacKenzie SL, Wyatt MC, Schuff R, Tenenbaum JD, Anderson N (June 2012). "Practices and perspectives on building integrated data repositories: results from a 2010 CTSA survey". Journal of the American Medical Informatics Association. 19 (e1): e119–24. doi:10.1136/amiajnl-2011-000508. PMC   3392848 . PMID   22437072.
  20. 1 2 Wade TD, Zelarney PT, Hum RC, McGee S, Batson DH (December 2014). "Using patient lists to add value to integrated data repositories". Journal of Biomedical Informatics. 52: 72–7. doi:10.1016/j.jbi.2014.02.010. PMC   4134416 . PMID   24534444.
  21. 1 2 3 4 Nadkarni, Prakash (2016). "Clinical Data Repositories: Warehouses, Registries, and the Use of Standards". Clinical Research Computing: A Practitioner's Handbook. Academic Press. pp. 173–85. doi:10.1016/B978-0-12-803130-8.00009-9. ISBN   978-0128031452.
  22. 1 2 Huser V, Cimino JJ (2014). "Don't take your EHR to heaven, donate it to science: legal and research policies for EHR post mortem". Journal of the American Medical Informatics Association. 21 (1): 8–12. doi:10.1136/amiajnl-2013-002061. PMC   3912713 . PMID   23966483.
  23. Huser V, DeFalco FJ, Schuemie M, Ryan PB, Shang N, Velez M, Park RW, Boyce RD, Duke J, Khare R, Utidjian L, Bailey C (2016). "Multisite Evaluation of a Data Quality Tool for Patient-Level Clinical Data Sets". EGEMs. 4 (1): 1239. doi:10.13063/2327-9214.1239. PMC   5226382 . PMID   28154833.
  24. Huser, V; Shmueli-Blumberg, D (2018). "Data sharing platforms for de-identified data from human clinical trials". Clinical Trials. 15 (4): 413–423. doi:10.1177/1740774518769655. PMID   29676586.
  25. https://www.projectdatasphere.org
  26. https://immport.niaid.nih.gov
  27. https://ClinicalStudyDataRequest.com
  28. Butte AJ (June 2009). "Translational bioinformatics applications in genome medicine". Genome Medicine. 1 (6): 64. doi:10.1186/gm64. PMC   2703873 . PMID   19566916.
  29. Kann MG (January 2010). "Advances in translational bioinformatics: computational approaches for the hunting of disease genes". Briefings in Bioinformatics. 11 (1): 96–110. doi:10.1093/bib/bbp048. PMC   2810112 . PMID   20007728.
  30. Lussier YA, Butte AJ, Hunter L (June 2010). "Current methodologies for translational bioinformatics". Journal of Biomedical Informatics. 43 (3): 355–7. doi:10.1016/j.jbi.2010.05.002. PMC   2894568 . PMID   20470899.
  31. Sarkar IN (February 2010). "Biomedical informatics and translational medicine". Journal of Translational Medicine. 8: 22. doi:10.1186/1479-5876-8-22. PMC   2837642 . PMID   20187952.
  32. Embi PJ, Payne PR (2009). "Clinical research informatics: challenges, opportunities and definition for an emerging domain". Journal of the American Medical Informatics Association. 16 (3): 316–27. doi:10.1197/jamia.m3005. PMC   2732242 . PMID   19261934.
  33. 1 2 3 4 5 Tenenbaum JD (February 2016). "Translational Bioinformatics: Past, Present, and Future". Genomics, Proteomics & Bioinformatics. 14 (1): 31–41. doi:10.1016/j.gpb.2016.01.003. PMC   4792852 . PMID   26876718.
  34. AMIA website
  35. Greengard, Samuel (1 February 2013). "A New Model for Healthcare" (PDF). Communications of the ACM. 56 (2): 1719. doi:10.1145/2408776.2408783 . Retrieved 12 February 2013.[ permanent dead link ]
  36. Hoey J, Poupart P, von Bertoldi A, Craig T, Boutilier C, Mihailidis A (2010). "Automated Handwashing Assistance For Persons With Dementia Using Video and a Partially Observable Markov Decision Process". Computer Vision and Image Understanding (CVIU). 114 (5): 503–19. CiteSeerX   10.1.1.160.8351 . doi:10.1016/j.cviu.2009.06.008.
  37. Mihailidis A, Boger JN, Craig T, Hoey J (November 2008). "The COACH prompting system to assist older adults with dementia through handwashing: an efficacy study". BMC Geriatrics. 8: 28. doi:10.1186/1471-2318-8-28. PMC   2588599 . PMID   18992135.
  38. Peter J. Embi., and Philip R. O. Payne. 2009.Clinical research informatics: challenges, opportunities and definition for an emerging domain. Journal of the American Medical Informatics Association (JAMIA). 2009 May–Jun 16(3):316–17. doi : 10.1197.
  39. Richesson, Rachel L., and James E. Andrews. 2012.Clinical research informatics. London: Springer.
  40. Huser V, Sastry C, Breymaier M, Idriss A, Cimino JJ (October 2015). "Standardizing data exchange for clinical research protocols and case report forms: An assessment of the suitability of the Clinical Data Interchange Standards Consortium (CDISC) Operational Data Model (ODM)". Journal of Biomedical Informatics. 57: 88–99. doi:10.1016/j.jbi.2015.06.023. PMC   4714951 . PMID   26188274.
  41. 1 2 "The History of Health Informatics". Health Informatics, Nursing Informatics and Health Information Management Degrees. University of Illinois at Chicago.
  42. 1 2 3 "NYU Graduate Training Program in Biomedical Informatics (BMI): A Brief History of Biomedical Informatics as a Discipline". www.nyuinformatics.org. NYU Langone Medical Center. Archived from the original on 2010-12-12. Retrieved 11 November 2010.
  43. Robson S, Baek OK (2009). The engines of Hippocrates: From the Dawn of Medicine to Medical and Pharmaceutical Informatics. Hoboken, NJ: John Wiley & Sons. ISBN   978-0470289532.
  44. Haux R (September 2010). "Medical informatics: past, present, future". International Journal of Medical Informatics. 79 (9): 599–610. doi:10.1016/j.ijmedinf.2010.06.003. PMID   20615752.
  45. Sittig DF, Ash JS, Ledley RS (2006). "The story behind the development of the first whole-body computerized tomography scanner as told by Robert S. Ledley". Journal of the American Medical Informatics Association. 13 (5): 465–9. doi:10.1197/jamia.M2127. PMC   1561796 . PMID   16799115.
  46. 1 2 November, Joseph (2012). Biomedical Computing: Digitizing Life in the United States. Baltimore: Johns Hopkins University Press. ISBN   978-1421404684.
  47. Pyle KI, Lobel RW, Beck JR (1988). "Citation analysis of the field of medical decision making: update, 1959-1985". Medical Decision Making. 8 (3): 155–64. doi:10.1177/0272989X8800800302. PMID   3294550.
  48. "Walking Patterns of Normal Men, JBS, 1964". Archived from the original on 2012-01-18. Retrieved 2012-06-18.
  49. "MGH – Laboratory of Computer Science". Archived from the original on 2014-08-02. Retrieved 2009-04-16.
  50. Edwin D. Reilly (2003). Milestones in Computer Science and Information Technology. Greenwood Press. p. 161. ISBN   978-1573565219.
  51. Collen, Morris F. (1995). A History of Medical Informatics in the United States, 1950 to 1990. Bethesda, MD: American Medical Informatics Association. ISBN   978-0964774308.
  52. "Dr. Morris Collen Tribute". Kaiser Permanente. 2008. Archived from the original on February 2, 2014. Retrieved May 21, 2012.
  53. Historical Videos of the founding of the Division of Clinical Informatics at Beth Israel Deaconess Medical Center
  54. "Patient power through records". Boston Globe. 2017. Retrieved February 2, 2017.
  55. "PaperChase A Computer Program to Search the Medical Literature". Proc Annu Symp Comput Appl Med Care Proc Annu Symp Comput Appl Med Care. November 1982. pp. 1045–1051. PMC   2580387 .
  56. Safran, C (July–August 2002). "Presentation of Morris F. Collen Award to Professors Howard Bleich and Warner Slack". J Am Med Inform Assoc. 9 (4): 406–408. doi:10.1197/jamia.M1080. PMC   403635 . PMID   12087123.
  57. Zahabi M, Kaber DB, Swangnetr M (August 2015). "Usability and Safety in Electronic Medical Records Interface Design: A Review of Recent Literature and Guideline Formulation". Human Factors. 57 (5): 805–34. doi:10.1177/0018720815576827. PMID   25850118.CS1 maint: Uses authors parameter (link)
  58. Zahabi M, Kaber DB, Swangnetr M (August 2015). "Usability and Safety in Electronic Medical Records Interface Design: A Review of Recent Literature and Guideline Formulation". Human Factors. 57 (5): 805–34. doi:10.1177/0018720815576827. PMID   25850118.
  59. Patton GA, Gardner RM (1999). "Medical informatics education: the University of Utah experience". Journal of the American Medical Informatics Association. 6 (6): 457–65. doi:10.1136/jamia.1999.0060457. PMC   61389 . PMID   10579604.
  60. Informatics Nursing Certification Eligibility Criteria, American Nurses Credentialing Center, accessed June 18, 2016
  61. Certification Guide, American Board of Imaging Informatics, accessed June 18, 2016,
  62. Knowledge Domains, American Health Information Management Association, accessed June 18, 2016,
  63. Missed Opportunities? The Labor Market in Health Informatics, 2014, Burning Glass Technologies, December 2014; accessed June 18, 2016
  64. AHIMA Certification Activities 2015, American Health Information Management Association, accessed June 18, 2016
  65. "Health Informatics for Low- and Middle-Income Countries: Short Course for Health Information System Professions — MEASURE Evaluation". www.measureevaluation.org. Retrieved 2018-10-04.
  66. Priest, Lisa (2008-02-18). "Your medical chart, just a mouse click away". The Globe and Mail. Toronto.
  67. "Head of eHealth Ontario is fired amid contracts scandal, gets big package". CBC News. 2009-06-07. Retrieved 2009-08-26.
  68. Executive Order 13335
  69. Certification Commission for Healthcare Information Technology (July 18, 2006): CCHIT Announces First Certified Electronic Health Record Products. Retrieved July 26, 2006.
  70. https://cbmi.med.harvard.edu/
  71. https://www.cincinnatichildrens.org/research/divisions/b/bmi/
  72. http://med.uc.edu/bmi/
  73. http://med.uc.edu/bmigrad/
  74. European eHealth Action Plan
  75. European eHealth Action Plan i2010
  76. "Electronic Health Records for Europe". European Space Agency. 2005. Retrieved 2009-01-13.
  77. GP Systems of Choice (GPSoC)
  78. http://www.nfu.nl/english/about-the-nfu/
  79. http://www.nfu.nl/patientenzorg/citrien
  80. https://www.efmi.org/about/efmi-countries/netherlands
  81. https://www.nictiz.nl/over-nictiz/english
  82. Cordis FP5web
  83. European Patient Smart Open Services
  84. Holzinger, A. (2012). Biomedical Informatics, Lecture Notes to LV 444.152. Books on Demand, ISBN   978-3848222193.
  85. "Asia Pacific Association of Medical Informatics".
  86. "Australasian College of Health Informatics" . Retrieved 3 May 2010.Australasian College of Health Informatics
  87. "International Medical Informatics Association – Academic Institutional Members". Australian College of Health Informatics. 12 August 2009. Archived from the original on 6 July 2010. Retrieved 22 February 2010.
  88. ACHI Memberships ACHI memberships: Professions Australia
  89. eJHI Journal of Health Informatics Archived 2011-07-23 at the Wayback Machine (open access journal)
  90. Australian Health Informatics Education Council (AHIEC) AHIEC Auspicing Organisations
  91. "Health Informatics Society of Australia Ltd" . Retrieved 3 April 2010.
  92. 1 2 Zhang Y, Xu Y, Shang L, Rao K (August 2007). "An investigation into health informatics and related standards in China". International Journal of Medical Informatics. 76 (8): 614–20. doi:10.1016/j.ijmedinf.2006.05.003. PMID   16793329.
  93. Guo J, Takada A, Niu T, He M, Tanaka K, Sato J, Suzuki M, Takahashi K, Daimon H, Suzuki T, Nakashima Y, Araki K, Yoshihara H (October 2005). "Enhancement of CLAIM (clinical accounting information) for a localized Chinese version". Journal of Medical Systems. 29 (5): 463–71. doi:10.1007/s10916-005-6103-7. PMID   16180482.
  94. Wang XJ, Hu J, Wang K, Yu H, Luo M, Lei WY (November 2004). "Setting-up and preliminary performance of the interactive teleradiological conference system based on virtual private network". Chinese Medical Journal. 117 (11): 1735–8. PMID   15569497.
  95. Rao KQ, Wang CY, Hu JP (2005). "Introduction of the National Public Health Emergency Response Information Systems Project". Chinese Journal of Integrative Medicine . 1: 2–5.
  96. "Health Informatics Journal" (PDF).
  97. "The Current Status of Hospital Information Systems in Yanbian, China" (PDF).
  98. "Development Layout of National Health Information" . Retrieved 2017-11-03.
  99. Kalra D, Beale T, Heard S (2005). "The openEHR Foundation". Studies in Health Technology and Informatics. 115: 153–73. PMID   16160223.
  100. Xu W, Guan Z, Cao H, Zhang H, Lu M, Li T (August 2011). "Analysis and evaluation of the Electronic Health Record standard in China: a comparison with the American national standard ASTM E 1384". International Journal of Medical Informatics. 80 (8): 555–61. doi:10.1016/j.ijmedinf.2011.05.003. PMID   21680236.
  101. Lévy PP, Duché L, Darago L, Dorléans Y, Toubiana L, Vibert JF, Flahault A (2005). "ICPCview: visualizing the International Classification of Primary Care". Studies in Health Technology and Informatics. 116: 623–8. PMID   16160327.
  102. Health informatics section in Hong Kong Hospital Authority
  103. eHealth Consortium Archived 2006-06-28 at the Wayback Machine
  104. eHCF School of Medical Informatics
  105. eHealth-Care Foundation
  106. Kerr K, Cullen R, Duke J, Holt A (2006). "Health Informatics Capability Development In New Zealand - A Report to the Tertiary Education Commission" (PDF). Archived from the original (PDF) on 2008-09-20. Retrieved 2009-01-08.
  107. "Medical Pharmaceutical Information Association (MedPharmInfo)". Imia.org. 2008-05-18. Retrieved 2010-07-29.[ permanent dead link ]
  108. "Saudi Association for Health Informatics (SAHI)". www.sahi.org.sa/. Archived from the original on 2010-08-24.
  109. Ericksen, A. (2009). "Informatics: the future of nursing". RN, 72(7), 34–37.
  110. Menachemi N, Collum TH (2011). "Benefits and drawbacks of electronic health record systems". Risk Management and Healthcare Policy. 4: 47–55. doi:10.2147/RMHP.S12985. PMC   3270933 . PMID   22312227.
  111. 1 2 3 Your Rights Under HIPAA. (n.d.). [Text]. Retrieved September 5, 2016, from https://www.hhs.gov/hipaa/for-individuals/guidance-materials-for-consumers/index.html
  112. Nelson, R., & Staggers, N. (2014). Health Informatics: An Interprofessional Approach. St. Louis: Mosby.
  113. NLM Catalog. (2016). Retrieved from National Center for Biotechnology Information, U.S. National Library of Medicine: https://www.ncbi.nlm.nih.gov/nlmcatalog?cmd=historysearch&querykey=3
  114. SCImago. (2007). SJR — SCImago Journal & Country Rank. Retrieved July 21, 2015, from http://www.scimagojr.com

Further reading