Software designed to store, manipulate, manage, and control data for specific uses.
Extensive collections, reputedly complete, of facts and data garnered from material of a specialized subject area and made available for analysis and application. The collection can be automated by various contemporary methods for retrieval. The concept should be differentiated from DATABASES, BIBLIOGRAPHIC which is restricted to collections of bibliographic references.
The portion of an interactive computer program that issues messages to and receives commands from a user.
Sequential operating programs and data which instruct the functioning of a digital computer.
Organized activities related to the storage, location, search, and retrieval of information.
A loose confederation of computer communication networks around the world. The networks that make up the Internet are connected through several backbone networks. The Internet grew out of the US Government ARPAnet project and was designed to facilitate information exchange.
Systems designed to provide information primarily concerned with the administrative functions associated with the provision and utilization of services; also includes program planning, etc.
The process of pictorial communication, between human and computers, in which the computer input and output have the form of charts, drawings, or other appropriate pictorial representation.
Databases devoted to knowledge about specific genes and gene products.
Specifications and instructions applied to the software.
Integrated set of files, procedures, and equipment for the storage, manipulation, and retrieval of information.
Small computers using LSI (large-scale integration) microprocessor chips as the CPU (central processing unit) and semiconductor memories for compact, inexpensive storage of program instructions and data. They are smaller and less expensive than minicomputers and are usually built into a dedicated system where they are optimized for a particular application. "Microprocessor" may refer to just the CPU or the entire microcomputer.
The procedures involved in combining separately developed modules, components, or subsystems so that they work together as a complete system. (From McGraw-Hill Dictionary of Scientific and Technical Terms, 4th ed)
A system containing any combination of computers, computer terminals, printers, audio or visual display devices, or telephones interconnected by telecommunications equipment or cables: used to transmit or receive information. (Random House Unabridged Dictionary, 2d ed)
A concept, developed in 1983 under the aegis of and supported by the National Library of Medicine under the name of Integrated Academic Information Management Systems, to provide professionals in academic health sciences centers and health sciences institutions with convenient access to an integrated and comprehensive network of knowledge. It addresses a wide cross-section of users from administrators and faculty to students and clinicians and has applications to planning, clinical and managerial decision-making, teaching, and research. It provides access to various types of clinical, management, educational, etc., databases, as well as to research and bibliographic databases. In August 1992 the name was changed from Integrated Academic Information Management Systems to Integrated Advanced Information Management Systems to reflect use beyond the academic milieu.
Management of the acquisition, organization, storage, retrieval, and dissemination of information. (From Thesaurus of ERIC Descriptors, 1994)
A field of biology concerned with the development of techniques for the collection and manipulation of biological data, and the use of such data to make biological discoveries or predictions. This field encompasses all computational methods and theories for solving biological problems including manipulation of models and datasets.
Information systems, usually computer-assisted, designed to store, manipulate, and retrieve information for planning, organizing, directing, and controlling administrative and clinical activities associated with the provision and utilization of clinical laboratory services.
Information systems, usually computer-assisted, designed to store, manipulate, and retrieve information for planning, organizing, directing, and controlling administrative activities associated with the provision and utilization of operating room services and facilities.
Generating, planning, organizing, and administering medical and nursing care and services for patients.
Systems composed of a computer or computers, peripheral equipment, such as disks, printers, and terminals, and telecommunications capabilities.
A broad approach to appropriate coordination of the entire disease treatment process that often involves shifting away from more expensive inpatient and acute care to areas such as preventive medicine, patient counseling and education, and outpatient care. This concept includes implications of appropriate versus inappropriate therapy on the overall cost and clinical outcome of a particular disease. (From Hosp Pharm 1995 Jul;30(7):596)
The science of breeding, feeding and care of domestic animals; includes housing and nutrition.
Management of the acquisition, organization, retrieval, and dissemination of health information.
Specific languages used to prepare computer programs.
Description of pattern of recurrent functions or procedures frequently found in organizational processes, such as notification, decision, and action.
The application of industrial management practice to systematically maintain and improve organization-wide performance. Effectiveness and success are determined and assessed by quantitative quality measures.
Computer-based systems for input, storage, display, retrieval, and printing of information contained in a patient's medical record.
Databases containing information about NUCLEIC ACIDS such as BASE SEQUENCE; SNPS; NUCLEIC ACID CONFORMATION; and other properties. Information about the DNA fragments kept in a GENE LIBRARY or GENOMIC LIBRARY is often maintained in DNA databases.
Management review designed to evaluate efficiency and to identify areas in need of management improvement within the institution in order to ensure effectiveness in meeting organizational goals.
Organized collections of computer records, standardized in format and content, that are stored in any of a variety of computer-readable modes. They are the basic sets of data from which computer-readable files are created. (from ALA Glossary of Library and Information Science, 1983)
Study of the anatomy of the nervous system as a specialty or discipline.
Databases containing information about PROTEINS such as AMINO ACID SEQUENCE; PROTEIN CONFORMATION; and other properties.
Protective measures against unauthorized access to or interference with computer operating systems, telecommunications, or data structures, especially the modification, deletion, destruction, or release of data in computers. It includes methods of forestalling interference by computer viruses or so-called computer hackers aiming to compromise stored data.
The development of systems to prevent accidents, injuries, and other adverse occurrences in an institutional setting. The concept includes prevention or reduction of adverse events or incidents involving employees, patients, or facilities. Examples include plans to reduce injuries from falls or plans for fire safety to promote a safe institutional environment.
Integrated, computer-assisted systems designed to store, manipulate, and retrieve information concerned with the administrative and clinical aspects of providing medical services within the hospital.
Information systems, usually computer-assisted, designed to store, manipulate, and retrieve information for planning, organizing, directing, and controlling administrative activities associated with the provision and utilization of radiology services and facilities.
Procedures, strategies, and theories of planning.
Longitudinal patient-maintained records of individual health history and tools that allow individual control of access.
The process of minimizing risk to an organization by developing systems to identify and analyze potential hazards to prevent accidents, injuries, and other adverse occurrences, and by attempting to handle events and incidents which do occur in such a manner that their effect and cost are minimized. Effective risk management has its greatest benefits in application to insurance in order to avert or minimize financial liability. (From Slee & Slee: Health care terms, 2d ed)
Data processing largely performed by automatic means.
Facilities equipped to carry out investigative procedures.
The field of information science concerned with the analysis and dissemination of medical data through the application of computers to various aspects of health care and medicine.
Systematic organization, storage, retrieval, and dissemination of specialized information, especially of a scientific or technical nature (From ALA Glossary of Library and Information Science, 1983). It often involves authenticating or validating information.
Adjunctive computer programs in providing drug treatment to patients.
Computer-based systems for use in personnel management in a facility, e.g., distribution of caregivers with relation to patient needs.
Management of the internal organization of the hospital.
A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task.

HICLAS: a taxonomic database system for displaying and comparing biological classification and phylogenetic trees. (1/2276)

MOTIVATION: Numerous database management systems have been developed for processing various taxonomic data bases on biological classification or phylogenetic information. In this paper, we present an integrated system to deal with interacting classifications and phylogenies concerning particular taxonomic groups. RESULTS: An information-theoretic view (taxon view) has been applied to capture taxonomic concepts as taxonomic data entities. A data model which is suitable for supporting semantically interacting dynamic views of hierarchic classifications and a query method for interacting classifications have been developed. The concept of taxonomic view and the data model can also be expanded to carry phylogenetic information in phylogenetic trees. We have designed a prototype taxonomic database system called HICLAS (HIerarchical CLAssification System) based on the concept of taxon view, and the data models and query methods have been designed and implemented. This system can be effectively used in the taxonomic revisionary process, especially when databases are being constructed by specialists in particular groups, and the system can be used to compare classifications and phylogenetic trees. AVAILABILITY: Freely available at the WWW URL: CONTACT: [email protected]; [email protected]  (+info)

Identifying diabetes mellitus or heart disease among health maintenance organization members: sensitivity, specificity, predictive value, and cost of survey and database methods. (2/2276)

We conducted a study of the sensitivity, specificity, positive predictive value, and cost of two methods of identifying diagnosed diabetes mellitus or heart disease among members of a health maintenance organization (HMO). Among 3186 adult HMO members who were attending one primary care clinic, 2326 were reached for a telephone survey (efficiency = 0.73). Among these members, 1991 answered standardized questions to ascertain whether they had diabetes or heart disease (corrected response rate = 0.85). Linkage was then made to computerized diagnostic databases. By means of both a database method and a survey method, the 1976 members with complete data for analysis were classified as having or not having diabetes or heart disease. When results with the two methods disagreed, charts were reviewed to confirm the presence or absence of diabetes or heart disease. Diabetes was identified among 4.7% of adult members, and heart disease was identified among 3.7%. Identification of diabetes differed between the database method and the survey method (sensitivity 0.91 vs 0.98, specificity 0.99 vs 0.99, positive predictive value 0.94 vs 0.83). Identification of heart attach history was similar for the database method and the survey method (sensitivity 0.89 vs 0.95, specificity 0.99 vs 0.99, positive predictive value 0.79 vs 0.81). The cost of obtaining data was $13.50 per member for the survey method and $0.30 per member for the database method. Database methods or survey methods of identifying selected chronic diseases among HMO members may be acceptable for various purposes, but database identification methods appear to be less expensive and provide information on a higher proportion of HMO members than do survey methods. Accurate identification of chronic diseases among patients supports clinic-level measures for clinical improvement, research, and accountability.  (+info)

Prevalence and cost of hospitalization for gastrointestinal complications related to peptic ulcers with bleeding or perforation: comparison of two national databases. (3/2276)

The purpose of this study was to determine the prevalence and cost of hospitalization for upper gastrointestinal complications, including peptic ulcers with hemorrhage or perforation. Upper gastrointestinal complications and corresponding economic data were obtained from two sources. The first was a 20% sample of all community hospital discharges (about 6 million per year) from 11 states for 1991 and 1992 Hospital Cost Utilization Project; HCUP-3). The second source of data was a claims database for employees of large US corporations and their dependents for 1992, 1993, and 1994 (about 3.5 million covered lives per year; MarketScan). A group of ICD-9 codes for the diagnosis of peptic and gastroduodenal ulcers with bleeding or perforation were used to identify hospital admissions because of upper gastrointestinal complications. Similar patterns were observed across the MarketScan and HCUP-3 databases regarding hospitalization with diagnoses related to gastrointestinal complications identified according to the ICD-9 codes. The average age of patients with upper gastrointestinal complications was 66 years in the HCUP-3 database and 52 years in the MarketScan database. The average annual rates of upper gastrointestinal complications as a primary or secondary diagnosis were 6.4 and 6.7 per 1000 discharges for 1991 and 1992, respectively (HCUP-3), and 4.3, 4.2, and 4.9 per 1000 admissions for 1992, 1993, and 1994, respectively (MarketScan). The average length of stay for upper gastrointestinal complications as a primary diagnosis was 7.8 days in 1991 and 7.5 days in 1992 (HCUP-3) and 6.1, 5.1, and 5.1 days in 1992, 1993, and 1994, respectively (MarketScan). The national average total charge for hospitalization for gastrointestinal problems as a primary diagnosis was $12,970 in 1991 and $14,294 in 1992 (HCUP-3). The average total reimbursement for hospitalizations related to upper gastrointestinal problems was $15,309 in 1992, $12,987 in 1993, and $13,150 in 1994 (MarketScan). Hospital admissions for upper gastrointestinal complications are expensive. The rate and cost per admission are higher for the older population. The results on the elements covered by both databases are consistent. Therefore the databases complement each other on the type of information abstracted.  (+info)

DNA microarray technology: the anticipated impact on the study of human disease. (4/2276)

One can imagine that, one day, there will be a general requirement that relevant array data be deposited, at the time of publication of manuscripts in which they are described, into a single site made available for the storage and analysis of array data (modeled after the GenBank submission requirements for DNA sequence information). With this system in place, one can anticipate a time when data from thousands of gene expression experiments will be available for meta-analysis, which has the potential to balance out artifacts from many individual studies, thus leading to more robust results and subtle conclusions. This will require that data adhere to some type of uniform structure and format that would ideally be independent of the particular expression technology used to generate it. The pros and cons of various publication modalities for these large electronic data sets have been discussed elsewhere [12], but, practical difficulties aside, general depositing must occur for this technology to reach the broadest range of investigators. Finally, as mentioned at the beginning of this review, it is unfortunate that this important research tool remains largely restricted to a few laboratories that have developed expertise in this area and to a growing number of commercial interests. Ultimately the real value of microarray technology will only be realized when this approach is generally available. It is hoped that issues including platforms, instrumentation, clone availability, and patents [20] will be resolved shortly, making this technology accessible to the broadest range of scientists at the earliest possible moment.  (+info)

Motif-based searching in TOPS protein topology databases. (5/2276)

MOTIVATION: TOPS cartoons are a schematic ion of protein three-dimensional structures in two dimensions, and are used for understanding and manual comparison of protein folds. Recently, an algorithm that produces the cartoons automatically from protein structures has been devised and cartoons have been generated to represent all the structures in the structural databank. There is now a need to be able to define target topological patterns and to search the database for matching domains. RESULTS: We have devised a formal language for describing TOPS diagrams and patterns, and have designed an efficient algorithm to match a pattern to a set of diagrams. A pattern-matching system has been implemented, and tested on a database derived from all the current entries in the Protein Data Bank (15,000 domains). Users can search on patterns selected from a library of motifs or, alternatively, they can define their own search patterns. AVAILABILITY: The system is accessible over the Web at  (+info)

Wrapping SRS with CORBA: from textual data to distributed objects. (6/2276)

MOTIVATION: Biological data come in very different shapes. Databanks are maintained and used by distinct organizations. Text is the de facto Standard exchange format. The SRS system can integrate heterogeneous textual databanks but it was lacking a way to structure the extracted data. RESULTS: This paper presents a CORBA interface to the SRS system which manages databanks in a flat file format. SRS Object Servers are CORBA wrappers for SRS. They allow client applications (visualisation tools, data mining tools, etc.) to access and query SRS servers remotely through an Object Request Broker (ORB). They provide loader objects that contain the information extracted from the databanks by SRS. Loader objects are not hard-coded but generated in a flexible way by using loader specifications which allow SRS administrators to package data coming from distinct databanks. AVAILABILITY: The prototype may be available for beta-testing. Please contact the SRS group (  (+info)

The strategic and operational characteristics of a distributed phased archive for a multivendor incremental implementation of picture archiving and communications systems. (7/2276)

The long-term (10 years) multimodality distributed phased archive for the Medical Information, Communication and Archive System (MICAS) is being implemented in three phases. The selection process took approximately 10 months. Based on the mandatory archive attributes and desirable features, Cemax-Icon (Fremont, CA) was selected as the vendor. The archive provides for an open-solution allowing incorporation of leading edge, "best of breed" hardware and software and provides maximum flexibility and automation of workflow both within and outside of radiology. The solution selected is media-independent, provides expandable storage capacity, and will provide redundancy and fault tolerance in phase II at minimum cost. Other attributes of the archive include scalable archive strategy, virtual image database with global query, and an object-oriented database. The archive is seamlessly integrated with the radiology information system (RIS) and provides automated fetching and routing, automated study reconciliation using modality worklist manager, clinical reports available at any Digital Imaging and Communications in Medicine (DICOM) workstation, and studies available for interpretation whether validated or not. Within 24 hours after a new study is acquired, four copies will reside within different components of the archive including a copy that can be stored off-site. Phase II of the archive will be installed during 1999 and will include a second Cemax-Icon archive and database using archive manager (AM) Version 4.0 in a second computer room.  (+info)

Establishing radiologic image transmission via a transmission control protocol/Internet protocol network between two teaching hospitals in Houston. (8/2276)

The technical and management considerations necessary for the establishment of a network link between computed tomography (CT) and magnetic resonance imaging (MRI) networks of two geographically separated teaching hospitals are presented. The University of Texas Medical School at Houston Department of Radiology provides radiology residency training at its primary teaching hospital and at a second county-run hospital located approximately 12 miles away. A direct network link between the two hospitals was desired to permit timely consultative services to residents and professional colleagues. The network link was established by integrating the county hospital free-standing imaging network into the network infrastructure of the Medical School and the main teaching hospital. Technical issues involved in the integration were reassignment of internet protocol (IP) addresses, determination of data transmission protocol compatibilities, proof of connectivity and image transmission, transmission speeds and network loading, and management of the new network. These issues were resolved in a planned stepwise fashion and despite the fact that the system has a rate-limiting T1 segment between the county hospital and the teaching hospital the transmission speed was deemed suitable. The project has proven successful and can provide a guide for planning similar projects elsewhere. It has in fact made possible several new services for the teaching and research activities of the department's faculty and residents, which were not envisaged before the implementation of this connection.  (+info)

A Database Management System (DBMS) is a software application that enables users to define, create, maintain, and manipulate databases. It provides a structured way to organize, store, retrieve, and manage data in a digital format. The DBMS serves as an interface between the database and the applications or users that access it, allowing for standardized interactions and data access methods. Common functions of a DBMS include data definition, data manipulation, data security, data recovery, and concurrent data access control. Examples of DBMS include MySQL, Oracle, Microsoft SQL Server, and MongoDB.

A factual database in the medical context is a collection of organized and structured data that contains verified and accurate information related to medicine, healthcare, or health sciences. These databases serve as reliable resources for various stakeholders, including healthcare professionals, researchers, students, and patients, to access evidence-based information for making informed decisions and enhancing knowledge.

Examples of factual medical databases include:

1. PubMed: A comprehensive database of biomedical literature maintained by the US National Library of Medicine (NLM). It contains citations and abstracts from life sciences journals, books, and conference proceedings.
2. MEDLINE: A subset of PubMed, MEDLINE focuses on high-quality, peer-reviewed articles related to biomedicine and health. It is the primary component of the NLM's database and serves as a critical resource for healthcare professionals and researchers worldwide.
3. Cochrane Library: A collection of systematic reviews and meta-analyses focused on evidence-based medicine. The library aims to provide unbiased, high-quality information to support clinical decision-making and improve patient outcomes.
4. OVID: A platform that offers access to various medical and healthcare databases, including MEDLINE, Embase, and PsycINFO. It facilitates the search and retrieval of relevant literature for researchers, clinicians, and students.
5. A registry and results database of publicly and privately supported clinical studies conducted around the world. The platform aims to increase transparency and accessibility of clinical trial data for healthcare professionals, researchers, and patients.
6. UpToDate: An evidence-based, physician-authored clinical decision support resource that provides information on diagnosis, treatment, and prevention of medical conditions. It serves as a point-of-care tool for healthcare professionals to make informed decisions and improve patient care.
7. TRIP Database: A search engine designed to facilitate evidence-based medicine by providing quick access to high-quality resources, including systematic reviews, clinical guidelines, and practice recommendations.
8. National Guideline Clearinghouse (NGC): A database of evidence-based clinical practice guidelines and related documents developed through a rigorous review process. The NGC aims to provide clinicians, healthcare providers, and policymakers with reliable guidance for patient care.
9. DrugBank: A comprehensive, freely accessible online database containing detailed information about drugs, their mechanisms, interactions, and targets. It serves as a valuable resource for researchers, healthcare professionals, and students in the field of pharmacology and drug discovery.
10. Genetic Testing Registry (GTR): A database that provides centralized information about genetic tests, test developers, laboratories offering tests, and clinical validity and utility of genetic tests. It serves as a resource for healthcare professionals, researchers, and patients to make informed decisions regarding genetic testing.

A User-Computer Interface (also known as Human-Computer Interaction) refers to the point at which a person (user) interacts with a computer system. This can include both hardware and software components, such as keyboards, mice, touchscreens, and graphical user interfaces (GUIs). The design of the user-computer interface is crucial in determining the usability and accessibility of a computer system for the user. A well-designed interface should be intuitive, efficient, and easy to use, minimizing the cognitive load on the user and allowing them to effectively accomplish their tasks.

I am not aware of a widely accepted medical definition for the term "software," as it is more commonly used in the context of computer science and technology. Software refers to programs, data, and instructions that are used by computers to perform various tasks. It does not have direct relevance to medical fields such as anatomy, physiology, or clinical practice. If you have any questions related to medicine or healthcare, I would be happy to try to help with those instead!

'Information Storage and Retrieval' in the context of medical informatics refers to the processes and systems used for the recording, storing, organizing, protecting, and retrieving electronic health information (e.g., patient records, clinical data, medical images) for various purposes such as diagnosis, treatment planning, research, and education. This may involve the use of electronic health record (EHR) systems, databases, data warehouses, and other digital technologies that enable healthcare providers to access and share accurate, up-to-date, and relevant information about a patient's health status, medical history, and care plan. The goal is to improve the quality, safety, efficiency, and coordination of healthcare delivery by providing timely and evidence-based information to support clinical decision-making and patient engagement.

I'm sorry for any confusion, but "Internet" is a term that pertains to the global network of interconnected computers and servers that enable the transmission and reception of data via the internet protocol (IP). It is not a medical term and does not have a specific medical definition. If you have any questions related to medicine or health, I'd be happy to try to help answer them for you!

I'm sorry for any confusion, but "Management Information Systems" (MIS) is not a medical term. It is a term commonly used in the field of information systems and technology to describe:

"A computer-based system that provides information to support managerial decision-making at all levels of an organization." (Source: "Management Information Systems" article, *Encyclopedia Britannica*)

In a healthcare setting, MIS can be used to manage various aspects of patient care and administrative tasks. This can include maintaining electronic health records, managing scheduling and billing systems, tracking inventory, analyzing patient data for quality improvement, and more.

Computer graphics is the field of study and practice related to creating images and visual content using computer technology. It involves various techniques, algorithms, and tools for generating, manipulating, and rendering digital images and models. These can include 2D and 3D modeling, animation, rendering, visualization, and image processing. Computer graphics is used in a wide range of applications, including video games, movies, scientific simulations, medical imaging, architectural design, and data visualization.

A genetic database is a type of biomedical or health informatics database that stores and organizes genetic data, such as DNA sequences, gene maps, genotypes, haplotypes, and phenotype information. These databases can be used for various purposes, including research, clinical diagnosis, and personalized medicine.

There are different types of genetic databases, including:

1. Genomic databases: These databases store whole genome sequences, gene expression data, and other genomic information. Examples include the National Center for Biotechnology Information's (NCBI) GenBank, the European Nucleotide Archive (ENA), and the DNA Data Bank of Japan (DDBJ).
2. Gene databases: These databases contain information about specific genes, including their location, function, regulation, and evolution. Examples include the Online Mendelian Inheritance in Man (OMIM) database, the Universal Protein Resource (UniProt), and the Gene Ontology (GO) database.
3. Variant databases: These databases store information about genetic variants, such as single nucleotide polymorphisms (SNPs), insertions/deletions (INDELs), and copy number variations (CNVs). Examples include the Database of Single Nucleotide Polymorphisms (dbSNP), the Catalogue of Somatic Mutations in Cancer (COSMIC), and the International HapMap Project.
4. Clinical databases: These databases contain genetic and clinical information about patients, such as their genotype, phenotype, family history, and response to treatments. Examples include the ClinVar database, the Pharmacogenomics Knowledgebase (PharmGKB), and the Genetic Testing Registry (GTR).
5. Population databases: These databases store genetic information about different populations, including their ancestry, demographics, and genetic diversity. Examples include the 1000 Genomes Project, the Human Genome Diversity Project (HGDP), and the Allele Frequency Net Database (AFND).

Genetic databases can be publicly accessible or restricted to authorized users, depending on their purpose and content. They play a crucial role in advancing our understanding of genetics and genomics, as well as improving healthcare and personalized medicine.

I must clarify that there is no specific medical definition for "Software Design." Software design is a term used in the field of software engineering and development, which includes the creation of detailed plans, schemas, and models that describe how a software system or application should be constructed and implemented. This process involves various activities such as defining the architecture, components, modules, interfaces, data structures, and algorithms required to build the software system.

However, in the context of medical software or healthcare applications, software design would still refer to the planning and structuring of the software system but with a focus on addressing specific needs and challenges within the medical domain. This might include considerations for data privacy and security, regulatory compliance (such as HIPAA or GDPR), integration with existing health IT systems, user experience (UX) design for healthcare professionals and patients, and evidence-based decision support features.

In the context of healthcare, an Information System (IS) is a set of components that work together to collect, process, store, and distribute health information. This can include hardware, software, data, people, and procedures that are used to create, process, and communicate information.

Healthcare IS support various functions within a healthcare organization, such as:

1. Clinical information systems: These systems support clinical workflows and decision-making by providing access to patient records, order entry, results reporting, and medication administration records.
2. Financial information systems: These systems manage financial transactions, including billing, claims processing, and revenue cycle management.
3. Administrative information systems: These systems support administrative functions, such as scheduling appointments, managing patient registration, and tracking patient flow.
4. Public health information systems: These systems collect, analyze, and disseminate public health data to support disease surveillance, outbreak investigation, and population health management.

Healthcare IS must comply with various regulations, including the Health Insurance Portability and Accountability Act (HIPAA), which governs the privacy and security of protected health information (PHI). Effective implementation and use of healthcare IS can improve patient care, reduce errors, and increase efficiency within healthcare organizations.

I'm sorry for any confusion, but "Microcomputers" is not a term commonly used in medical definitions. Microcomputers are small computers with a microprocessor as the central processing unit. They are widely used in various settings, including healthcare, to perform tasks such as data management, analysis, and patient record keeping. However, the term itself does not have a specific medical connotation. If you have any questions related to technology use in healthcare, I'd be happy to try to help with those!

I'm sorry for any confusion, but "Systems Integration" is not a medical term per se. It is a term more commonly used in the fields of engineering, computer science, and information technology. However, I can provide you with a general definition:

Systems Integration refers to the process of combining different sub-systems or components into a single, cohesive system to allow seamless communication and data exchange between them. This integration aims to improve efficiency, performance, and overall functionality by unifying various standalone systems into an interconnected network that behaves as a unified whole.

In the context of healthcare, systems integration can be applied to merge different electronic health record (EHR) systems, medical devices, or other healthcare technologies to create a comprehensive, interoperable healthcare information system. This facilitates better care coordination, data sharing, and decision-making among healthcare providers, ultimately enhancing patient outcomes and satisfaction.

Computer communication networks (CCN) refer to the interconnected systems or groups of computers that are able to communicate and share resources and information with each other. These networks may be composed of multiple interconnected devices, including computers, servers, switches, routers, and other hardware components. The connections between these devices can be established through various types of media, such as wired Ethernet cables or wireless Wi-Fi signals.

CCNs enable the sharing of data, applications, and services among users and devices, and they are essential for supporting modern digital communication and collaboration. Some common examples of CCNs include local area networks (LANs), wide area networks (WANs), and the Internet. These networks can be designed and implemented in various topologies, such as star, ring, bus, mesh, and tree configurations, to meet the specific needs and requirements of different organizations and applications.

I'm sorry for any confusion, but "Integrated Advanced Information Management Systems" is not a recognized medical term or concept in and of itself. However, I can provide some insight into what the individual terms might mean in a healthcare context:

1. **Integrated:** This generally refers to the combination of different systems or components so that they work together as a unified whole. In healthcare, an integrated system might involve the seamless sharing of data and functionality between electronic health records, imaging systems, laboratory information systems, and other technology platforms.

2. **Advanced:** This term is somewhat subjective, but in a technological context, it often refers to systems that employ cutting-edge techniques or technologies. In healthcare, an advanced information management system might use artificial intelligence, machine learning, or natural language processing to improve data analysis, patient care, or operational efficiency.

3. **Information Management Systems:** These are systems designed to acquire, process, store, and disseminate information. In healthcare, these systems can include electronic health records, picture archiving and communication systems (PACS) for medical imaging, laboratory information management systems (LIMS), and many others.

So, an "Integrated Advanced Information Management Systems" in a broad healthcare context could refer to a system or suite of systems that combine cutting-edge technology with seamless integration to manage health data and improve patient care. However, it's important to note that this is not a standard medical term, and its exact meaning could vary depending on the specific context.

I'm happy to help! However, it looks like you are asking for a medical definition of "Information Management." It is important to note that "Information Management" is not a medical term per se, but rather a general term used in many fields, including healthcare. Here's a possible definition of Information Management in the context of healthcare:

Information Management (in healthcare) refers to the systematic processes and practices used to collect, store, distribute, retrieve, and dispose of health information in an accurate, confidential, timely, and efficient manner. It involves the use of technology, policies, procedures, and personnel to ensure that health information is accessible, secure, and used appropriately for patient care, research, quality improvement, and other purposes. Effective Information Management is critical for ensuring high-quality healthcare, improving patient outcomes, and complying with legal and regulatory requirements related to privacy and security of health information.

Computational biology is a branch of biology that uses mathematical and computational methods to study biological data, models, and processes. It involves the development and application of algorithms, statistical models, and computational approaches to analyze and interpret large-scale molecular and phenotypic data from genomics, transcriptomics, proteomics, metabolomics, and other high-throughput technologies. The goal is to gain insights into biological systems and processes, develop predictive models, and inform experimental design and hypothesis testing in the life sciences. Computational biology encompasses a wide range of disciplines, including bioinformatics, systems biology, computational genomics, network biology, and mathematical modeling of biological systems.

A Clinical Laboratory Information System (CLIS) is a type of healthcare information system that is designed to automate and manage the workflow, data management, and reporting capabilities of a clinical laboratory. It serves as a centralized repository for all laboratory data and test results, allowing for efficient communication between healthcare providers, laboratorians, and patients.

The CLIS typically includes modules for specimen tracking, order entry, result reporting, data analysis, and quality control. It interfaces with other hospital information systems such as the electronic health record (EHR), radiology information system (RIS), and pharmacy information system (PIS) to provide a comprehensive view of the patient's medical history and test results.

The CLIS is used to manage a wide range of laboratory tests, including clinical chemistry, hematology, microbiology, immunology, molecular diagnostics, and toxicology. It helps laboratories to streamline their operations, reduce errors, improve turnaround times, and enhance the overall quality of patient care.

In summary, a Clinical Laboratory Information System is an essential tool for modern clinical laboratories that enables them to manage large volumes of data, improve efficiency, and provide accurate and timely test results to healthcare providers and patients.

An Operating Room Information System (ORIS) is a specialized type of healthcare information system that is designed to manage and support the various clinical and operational functions of an operating room (OR) department within a hospital or surgical facility. The primary goal of an ORIS is to optimize the efficiency, safety, and quality of care in the perioperative environment by providing real-time access to critical patient information, streamlining workflows, and facilitating communication among members of the surgical team.

An ORIS typically consists of several interconnected modules that address different aspects of OR management, such as:

1. Surgical scheduling and case management: This module helps manage the scheduling of surgeries, track patient progress through the perioperative process, and maintain an up-to-date record of surgical cases, including details about the patient, procedure, surgeons, anesthesia providers, and other relevant information.
2. Patient data management: This module provides secure access to comprehensive patient information, such as medical history, allergies, medications, lab results, and imaging studies, which is essential for making informed clinical decisions during surgery.
3. Anesthesia information management: This module supports the documentation and tracking of anesthesia-related data, including preoperative assessments, intraoperative monitoring, and postoperative orders, to ensure the safe and effective administration of anesthesia care.
4. Equipment and inventory management: This module helps track and manage the utilization and maintenance of surgical equipment and supplies, ensuring their availability and optimal performance during surgeries while also facilitating the ordering and restocking of consumables.
5. Perioperative documentation and reporting: This module enables the creation, storage, and retrieval of electronic records related to the perioperative process, such as surgical reports, anesthesia records, nursing notes, and charge capture data, which can be used for quality improvement, research, and regulatory compliance purposes.
6. Communication and collaboration: This module facilitates secure communication and information sharing among members of the surgical team, both within and across departments, to enhance coordination and collaboration during the perioperative process.

By integrating these various functions into a single, centralized system, an ORIS can help improve patient safety, streamline workflows, reduce costs, and support data-driven decision-making in the surgical setting.

Patient care management is a coordinated, comprehensive approach to providing healthcare services to individuals with chronic or complex medical conditions. It involves the development and implementation of a plan of care that is tailored to the needs of the patient, with the goal of improving clinical outcomes, enhancing quality of life, and reducing healthcare costs.

Patient care management typically involves a multidisciplinary team of healthcare professionals, including physicians, nurses, social workers, pharmacists, and other specialists as needed. The team works together to assess the patient's medical, psychological, social, and functional needs, and develop a plan of care that addresses those needs in a holistic and coordinated manner.

The plan of care may include a range of services, such as:

* Regular monitoring and management of chronic conditions
* Medication management and education
* Coordination of specialist appointments and other healthcare services
* Education and support for self-management of health conditions
* Behavioral health interventions to address mental health or substance use disorders
* Assistance with accessing community resources, such as transportation or housing

The ultimate goal of patient care management is to help patients achieve their optimal level of health and well-being, while also ensuring that healthcare services are delivered in a cost-effective and efficient manner. By coordinating care across providers and settings, patient care management can help reduce unnecessary hospitalizations, emergency department visits, and other costly interventions, while improving the overall quality of care for patients with complex medical needs.

A computer system is a collection of hardware and software components that work together to perform specific tasks. This includes the physical components such as the central processing unit (CPU), memory, storage devices, and input/output devices, as well as the operating system and application software that run on the hardware. Computer systems can range from small, embedded systems found in appliances and devices, to large, complex networks of interconnected computers used for enterprise-level operations.

In a medical context, computer systems are often used for tasks such as storing and retrieving electronic health records (EHRs), managing patient scheduling and billing, performing diagnostic imaging and analysis, and delivering telemedicine services. These systems must adhere to strict regulatory standards, such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States, to ensure the privacy and security of sensitive medical information.

Disease management is a proactive, planned approach to identify and manage patients with chronic medical conditions. It involves a systematic and coordinated method of delivering care to patients with the goal of improving clinical outcomes, enhancing quality of life, and reducing healthcare costs. This approach typically includes elements such as evidence-based care guidelines, patient education, self-management support, regular monitoring and follow-up, and collaboration between healthcare providers and specialists.

The objective of disease management is to improve the overall health and well-being of patients with chronic conditions by providing them with the necessary tools, resources, and support to effectively manage their condition and prevent complications. By implementing a comprehensive and coordinated approach to care, disease management can help reduce hospitalizations, emergency department visits, and other costly healthcare services while improving patient satisfaction and overall health outcomes.

Animal husbandry is the practice of breeding and raising animals for agricultural purposes, such as for the production of meat, milk, eggs, or fiber. It involves providing proper care for the animals, including feeding, housing, health care, and breeding management. The goal of animal husbandry is to maintain healthy and productive animals while also being mindful of environmental sustainability and animal welfare.

Health Information Management (HIM) is the practice of acquiring, analyzing, and protecting digital and traditional medical data for the purpose of ensuring accurate and timely health care services, conducting research, and making informed decisions. It involves the use of various technologies, standards, and policies to manage health information and communicate it effectively among healthcare professionals, patients, and other stakeholders. HIM professionals include health information technicians, coders, managers, and analysts who work in hospitals, clinics, physician practices, government agencies, and other healthcare settings.

I'm afraid there seems to be a misunderstanding. Programming languages are a field of study in computer science and are not related to medicine. They are used to create computer programs, through the composition of symbols and words. Some popular programming languages include Python, Java, C++, and JavaScript. If you have any questions about programming or computer science, I'd be happy to try and help answer them!

I'm happy to help, but I need to clarify that "workflow" is not a medical term per se. It is a term used in many fields, including healthcare, to describe a series of steps or tasks that are necessary to complete a process or task. In the context of healthcare, workflows often refer to the processes and procedures involved in delivering care to patients.

A medical definition of "workflow" might be:

The sequence of tasks or activities involved in providing clinical care to patients, including assessment, diagnosis, treatment planning, intervention, monitoring, and follow-up. Workflows may involve multiple healthcare providers, such as physicians, nurses, therapists, and other staff members, and may be supported by technology, such as electronic health records (EHRs) or other clinical information systems. Effective workflow design is critical to ensuring safe, timely, and efficient care delivery.

Total Quality Management (TQM) is not a medical term per se, but rather a management approach that has been adopted in various industries, including healthcare. Here's a general definition:

Total Quality Management (TQM) is a customer-focused management framework that involves all employees in an organization in continuous improvement efforts to meet or exceed customer expectations. It is based on the principles of quality control, continuous process improvement, and customer satisfaction. TQM aims to create a culture where all members of the organization are responsible for quality, with the goal of providing defect-free products or services to customers consistently.

In healthcare, TQM can be used to improve patient care, reduce medical errors, increase efficiency, and enhance patient satisfaction. It involves the use of data-driven decision-making, process improvement techniques such as Lean and Six Sigma, and a focus on evidence-based practices. The ultimate goal of TQM in healthcare is to provide high-quality, safe, and cost-effective care to patients.

A Computerized Medical Record System (CMRS) is a digital version of a patient's paper chart. It contains all of the patient's medical history from multiple providers and can be shared securely between healthcare professionals. A CMRS includes a range of data such as demographics, progress notes, problems, medications, vital signs, past medical history, immunizations, laboratory data, and radiology reports. The system facilitates the storage, retrieval, and exchange of this information in an efficient manner, and can also provide decision support, alerts, reminders, and tools for performing data analysis and creating reports. It is designed to improve the quality, safety, and efficiency of healthcare delivery by providing accurate, up-to-date, and comprehensive information about patients at the point of care.

A nucleic acid database is a type of biological database that contains sequence, structure, and functional information about nucleic acids, such as DNA and RNA. These databases are used in various fields of biology, including genomics, molecular biology, and bioinformatics, to store, search, and analyze nucleic acid data.

Some common types of nucleic acid databases include:

1. Nucleotide sequence databases: These databases contain the primary nucleotide sequences of DNA and RNA molecules from various organisms. Examples include GenBank, EMBL-Bank, and DDBJ.
2. Structure databases: These databases contain three-dimensional structures of nucleic acids determined by experimental methods such as X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy. Examples include the Protein Data Bank (PDB) and the Nucleic Acid Database (NDB).
3. Functional databases: These databases contain information about the functions of nucleic acids, such as their roles in gene regulation, transcription, and translation. Examples include the Gene Ontology (GO) database and the RegulonDB.
4. Genome databases: These databases contain genomic data for various organisms, including whole-genome sequences, gene annotations, and genetic variations. Examples include the Human Genome Database (HGD) and the Ensembl Genome Browser.
5. Comparative databases: These databases allow for the comparison of nucleic acid sequences or structures across different species or conditions. Examples include the Comparative RNA Web (CRW) Site and the Sequence Alignment and Modeling (SAM) system.

Nucleic acid databases are essential resources for researchers to study the structure, function, and evolution of nucleic acids, as well as to develop new tools and methods for analyzing and interpreting nucleic acid data.

I'm sorry for any confusion, but "Management Audit" is not a term that has a specific medical definition. It is a concept that is more commonly used in business and management contexts. A Management Audit refers to an examination and evaluation of an organization's or a company's management systems, processes, and practices. Its aim is to assess their effectiveness, efficiency, and compliance with established policies, procedures, and laws.

If you have any questions related to medical terminology or healthcare concepts, I would be happy to help!

A database, in the context of medical informatics, is a structured set of data organized in a way that allows for efficient storage, retrieval, and analysis. Databases are used extensively in healthcare to store and manage various types of information, including patient records, clinical trials data, research findings, and genetic data.

As a topic, "Databases" in medicine can refer to the design, implementation, management, and use of these databases. It may also encompass issues related to data security, privacy, and interoperability between different healthcare systems and databases. Additionally, it can involve the development and application of database technologies for specific medical purposes, such as clinical decision support, outcomes research, and personalized medicine.

Overall, databases play a critical role in modern healthcare by enabling evidence-based practice, improving patient care, advancing medical research, and informing health policy decisions.

Neuroanatomy is the branch of anatomy that deals with the study of the structure, organization, and relationships of the nervous system, including the brain, spinal cord, and peripheral nerves. It involves understanding the complex arrangement of neurons, neural pathways, and support structures that make up the nervous system, as well as how these components work together to enable various functions such as sensation, movement, cognition, and emotion. Neuroanatomy is a fundamental area of study in neuroscience, medicine, and psychology, providing critical knowledge for understanding brain function and dysfunction, developing treatments for neurological disorders, and advancing our overall understanding of the human body.

A protein database is a type of biological database that contains information about proteins and their structures, functions, sequences, and interactions with other molecules. These databases can include experimentally determined data, such as protein sequences derived from DNA sequencing or mass spectrometry, as well as predicted data based on computational methods.

Some examples of protein databases include:

1. UniProtKB: a comprehensive protein database that provides information about protein sequences, functions, and structures, as well as literature references and links to other resources.
2. PDB (Protein Data Bank): a database of three-dimensional protein structures determined by experimental methods such as X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy.
3. BLAST (Basic Local Alignment Search Tool): a web-based tool that allows users to compare a query protein sequence against a protein database to identify similar sequences and potential functional relationships.
4. InterPro: a database of protein families, domains, and functional sites that provides information about protein function based on sequence analysis and other data.
5. STRING (Search Tool for the Retrieval of Interacting Genes/Proteins): a database of known and predicted protein-protein interactions, including physical and functional associations.

Protein databases are essential tools in proteomics research, enabling researchers to study protein function, evolution, and interaction networks on a large scale.

Computer security, also known as cybersecurity, is the protection of computer systems and networks from theft, damage, or unauthorized access to their hardware, software, or electronic data. This can include a wide range of measures, such as:

* Using firewalls, intrusion detection systems, and other technical safeguards to prevent unauthorized access to a network
* Encrypting sensitive data to protect it from being intercepted or accessed by unauthorized parties
* Implementing strong password policies and using multi-factor authentication to verify the identity of users
* Regularly updating and patching software to fix known vulnerabilities
* Providing security awareness training to employees to help them understand the risks and best practices for protecting sensitive information
* Having a incident response plan in place to quickly and effectively respond to any potential security incidents.

The goal of computer security is to maintain the confidentiality, integrity, and availability of computer systems and data, in order to protect the privacy and safety of individuals and organizations.

Safety management is a systematic and organized approach to managing health and safety in the workplace. It involves the development, implementation, and monitoring of policies, procedures, and practices with the aim of preventing accidents, injuries, and occupational illnesses. Safety management includes identifying hazards, assessing risks, setting objectives and targets for improving safety performance, implementing controls, and evaluating the effectiveness of those controls. The goal of safety management is to create a safe and healthy work environment that protects workers, visitors, and others who may be affected by workplace activities. It is an integral part of an organization's overall management system and requires the active involvement and commitment of managers, supervisors, and employees at all levels.

A Hospital Information System (HIS) is a comprehensive, integrated set of software solutions that support the management and operation of a hospital or healthcare facility. It typically includes various modules such as:

1. Electronic Health Record (EHR): A digital version of a patient's paper chart that contains all of their medical history from one or multiple providers.
2. Computerized Physician Order Entry (CPOE): A system that allows physicians to enter, modify, review, and communicate orders for tests, medications, and other treatments electronically.
3. Pharmacy Information System: A system that manages the medication use process, including ordering, dispensing, administering, and monitoring of medications.
4. Laboratory Information System (LIS): A system that automates and manages the laboratory testing process, from order entry to result reporting.
5. Radiology Information System (RIS): A system that manages medical imaging data, including scheduling, image acquisition, storage, and retrieval.
6. Picture Archiving and Communication System (PACS): A system that stores, distributes, and displays medical images from various modalities such as X-ray, CT, MRI, etc.
7. Admission, Discharge, and Transfer (ADT) system: A system that manages patient registration, scheduling, and tracking of their progress through the hospital.
8. Financial Management System: A system that handles billing, coding, and reimbursement processes.
9. Materials Management System: A system that tracks inventory, supply chain, and logistics operations within a healthcare facility.
10. Nursing Documentation System: A system that supports the documentation of nursing care, including assessments, interventions, and outcomes.

These systems are designed to improve the efficiency, quality, and safety of patient care by facilitating communication, coordination, and data sharing among healthcare providers and departments.

A Radiology Information System (RIS) is a type of healthcare software specifically designed to manage medical imaging data and related patient information. It serves as a centralized database and communication platform for radiology departments, allowing the integration, storage, retrieval, and sharing of patient records, orders, reports, images, and other relevant documents.

The primary functions of a RIS typically include:

1. Scheduling and tracking: Managing appointments, scheduling resources, and monitoring workflow within the radiology department.
2. Order management: Tracking and processing requests for imaging exams from referring physicians or other healthcare providers.
3. Image tracking: Monitoring the movement of images throughout the entire imaging process, from acquisition to reporting and storage.
4. Report generation: Assisting radiologists in creating structured, standardized reports based on the interpreted imaging studies.
5. Results communication: Sending finalized reports back to the referring physicians or other healthcare providers, often through integration with electronic health records (EHRs) or hospital information systems (HIS).
6. Data analytics: Providing tools for analyzing and reporting departmental performance metrics, such as turnaround times, equipment utilization, and patient satisfaction.
7. Compliance and security: Ensuring adherence to regulatory requirements related to data privacy, protection, and storage, while maintaining secure access controls for authorized users.

By streamlining these processes, a RIS helps improve efficiency, reduce errors, enhance communication, and support better patient care within radiology departments.

I'm happy to help, but I must clarify that "planning techniques" is not a medical term per se. However, in the context of healthcare and medicine, planning techniques can refer to various methods and approaches used to organize, coordinate, and implement care plans for patients. These techniques are often utilized by healthcare professionals, such as doctors, nurses, and social workers, to ensure that patients receive high-quality, evidence-based care that meets their individual needs and goals.

Here are some examples of planning techniques commonly used in healthcare:

1. Advance Care Planning (ACP): A process that helps individuals plan for future medical care in the event they become unable to make decisions for themselves. This can include creating an advance directive, such as a living will or healthcare power of attorney.
2. Goal-Setting: A collaborative process between patients and healthcare providers to establish specific, measurable, achievable, relevant, and time-bound (SMART) goals for treatment and care.
3. Care Mapping: A visual tool used to map out a patient's care plan, including their medical history, diagnoses, treatments, and support needs. This can help healthcare providers coordinate care and ensure that all team members are on the same page.
4. Root Cause Analysis (RCA): A problem-solving technique used to identify the underlying causes of medical errors or adverse events, with the goal of preventing similar incidents from occurring in the future.
5. Failure Modes and Effects Analysis (FMEA): A proactive risk assessment tool used to identify potential failures in a system or process, and to develop strategies to mitigate those risks.
6. Plan-Do-Study-Act (PDSA) Cycle: A continuous quality improvement technique that involves planning a change, implementing the change, studying its effects, and then acting on the results to make further improvements.

These are just a few examples of the many planning techniques used in healthcare. The specific methods and approaches used will depend on the individual patient's needs, as well as the context and resources available within the healthcare system.

Personal Health Records (PHRs) are defined as:

"An electronic application through which individuals can access, manage and share their health information, and that of others for whom they are authorized, in a private, secure, and confidential environment." (Institute of Medicine, 2011)

PHRs typically contain personal health information such as medical history, medication lists, allergies, test results, and other relevant health data. They can be managed and controlled by the individual and may be connected to or separate from electronic health records maintained by healthcare providers. PHRs allow individuals to have more active roles in managing their own health and communicating with their healthcare team.

Risk management in the medical context refers to the systematic process of identifying, assessing, and prioritizing risks to patients, staff, or healthcare organizations, followed by the development, implementation, and monitoring of strategies to manage those risks. The goal is to minimize potential harm and optimize patient safety, quality of care, and operational efficiency.

This process typically involves:

1. Identifying potential hazards and risks in the healthcare environment, procedures, or systems.
2. Assessing the likelihood and potential impact of each identified risk.
3. Prioritizing risks based on their severity and probability.
4. Developing strategies to mitigate, eliminate, transfer, or accept the prioritized risks.
5. Implementing the risk management strategies and monitoring their effectiveness.
6. Continuously reviewing and updating the risk management process to adapt to changing circumstances or new information.

Effective risk management in healthcare helps organizations provide safer care, reduce adverse events, and promote a culture of safety and continuous improvement.

Automatic Data Processing (ADP) is not a medical term, but a general business term that refers to the use of computers and software to automate and streamline administrative tasks and processes. In a medical context, ADP may be used in healthcare settings to manage electronic health records (EHRs), billing and coding, insurance claims processing, and other data-intensive tasks.

The goal of using ADP in healthcare is to improve efficiency, accuracy, and timeliness of administrative processes, while reducing costs and errors associated with manual data entry and management. By automating these tasks, healthcare providers can focus more on patient care and less on paperwork, ultimately improving the quality of care delivered to patients.

A laboratory (often abbreviated as lab) is a facility that provides controlled conditions in which scientific or technological research, experiments, and measurements may be performed. In the medical field, laboratories are specialized spaces for conducting diagnostic tests and analyzing samples of bodily fluids, tissues, or other substances to gain insights into patients' health status.

There are various types of medical laboratories, including:

1. Clinical Laboratories: These labs perform tests on patient specimens to assist in the diagnosis, treatment, and prevention of diseases. They analyze blood, urine, stool, CSF (cerebrospinal fluid), and other samples for chemical components, cell counts, microorganisms, and genetic material.
2. Pathology Laboratories: These labs focus on the study of disease processes, causes, and effects. Histopathology involves examining tissue samples under a microscope to identify abnormalities or signs of diseases, while cytopathology deals with individual cells.
3. Microbiology Laboratories: In these labs, microorganisms like bacteria, viruses, fungi, and parasites are cultured, identified, and studied to help diagnose infections and determine appropriate treatments.
4. Molecular Biology Laboratories: These labs deal with the study of biological molecules, such as DNA, RNA, and proteins, to understand their structure, function, and interactions. They often use techniques like PCR (polymerase chain reaction) and gene sequencing for diagnostic purposes.
5. Immunology Laboratories: These labs specialize in the study of the immune system and its responses to various stimuli, including infectious agents and allergens. They perform tests to diagnose immunological disorders, monitor immune function, and assess vaccine effectiveness.
6. Toxicology Laboratories: These labs analyze biological samples for the presence and concentration of chemicals, drugs, or toxins that may be harmful to human health. They help identify potential causes of poisoning, drug interactions, and substance abuse.
7. Blood Banks: Although not traditionally considered laboratories, blood banks are specialized facilities that collect, test, store, and distribute blood and its components for transfusion purposes.

Medical laboratories play a crucial role in diagnosing diseases, monitoring disease progression, guiding treatment decisions, and assessing patient outcomes. They must adhere to strict quality control measures and regulatory guidelines to ensure accurate and reliable results.

Medical Informatics, also known as Healthcare Informatics, is the scientific discipline that deals with the systematic processing and analysis of data, information, and knowledge in healthcare and biomedicine. It involves the development and application of theories, methods, and tools to create, acquire, store, retrieve, share, use, and reuse health-related data and knowledge for clinical, educational, research, and administrative purposes. Medical Informatics encompasses various areas such as bioinformatics, clinical informatics, consumer health informatics, public health informatics, and translational bioinformatics. It aims to improve healthcare delivery, patient outcomes, and biomedical research through the effective use of information technology and data management strategies.

In a medical context, documentation refers to the process of recording and maintaining written or electronic records of a patient's health status, medical history, treatment plans, medications, and other relevant information. The purpose of medical documentation is to provide clear and accurate communication among healthcare providers, to support clinical decision-making, to ensure continuity of care, to meet legal and regulatory requirements, and to facilitate research and quality improvement initiatives.

Medical documentation typically includes various types of records such as:

1. Patient's demographic information, including name, date of birth, gender, and contact details.
2. Medical history, including past illnesses, surgeries, allergies, and family medical history.
3. Physical examination findings, laboratory and diagnostic test results, and diagnoses.
4. Treatment plans, including medications, therapies, procedures, and follow-up care.
5. Progress notes, which document the patient's response to treatment and any changes in their condition over time.
6. Consultation notes, which record communication between healthcare providers regarding a patient's care.
7. Discharge summaries, which provide an overview of the patient's hospital stay, including diagnoses, treatments, and follow-up plans.

Medical documentation must be clear, concise, accurate, and timely, and it should adhere to legal and ethical standards. Healthcare providers are responsible for maintaining the confidentiality of patients' medical records and ensuring that they are accessible only to authorized personnel.

Computer-assisted drug therapy refers to the use of computer systems and technology to support and enhance medication management and administration. This can include a variety of applications such as:

1. Medication ordering and prescribing systems that help reduce errors by providing alerts for potential drug interactions, dosage issues, and allergies.
2. Computerized physician order entry (CPOE) systems that allow healthcare providers to enter, review, and modify medication orders electronically.
3. Electronic medication administration records (eMARs) that track the administration of medications to patients in real-time, reducing errors and improving patient safety.
4. Clinical decision support systems (CDSS) that provide evidence-based recommendations for medication therapy based on patient-specific data.
5. Medication reconciliation systems that help ensure accurate and up-to-date medication lists for patients during transitions of care.

Overall, computer-assisted drug therapy aims to improve the safety, efficacy, and efficiency of medication management by reducing errors, enhancing communication, and providing timely access to relevant patient information.

I could not find a specific medical definition for "Personnel Staffing and Scheduling Information Systems" as it is more related to healthcare management and human resources. However, I can provide you with a general definition and explain its relevance to the medical field:

Personnel Staffing and Scheduling Information Systems refer to automated or computerized systems designed to manage and optimize staffing and scheduling processes within an organization. These systems help streamline workforce management by tracking employee availability, qualifications, and schedules while ensuring adequate coverage for various shifts, departments, or positions.

In the medical field, these systems are particularly important for managing healthcare personnel, such as nurses, doctors, and allied health professionals. Proper staffing and scheduling are crucial for maintaining high-quality patient care, ensuring compliance with regulatory requirements, and optimizing resource allocation. Personnel Staffing and Scheduling Information Systems in healthcare can help:

1. Match staff skills and qualifications to patient needs and unit requirements.
2. Ensure adequate coverage during peak demand periods or emergencies.
3. Minimize overstaffing and reduce labor costs.
4. Prevent scheduling conflicts, fatigue, and burnout by tracking employee work hours and mandatory rest periods.
5. Facilitate communication between staff members, managers, and human resources departments.
6. Monitor compliance with labor laws, union rules, and organizational policies related to staffing and scheduling.
7. Provide data for workforce planning, performance evaluation, and continuous improvement initiatives.

Hospital administration is a field of study and profession that deals with the management and leadership of hospitals and other healthcare facilities. It involves overseeing various aspects such as finance, human resources, operations, strategic planning, policy development, patient care services, and quality improvement. The main goal of hospital administration is to ensure that the organization runs smoothly, efficiently, and effectively while meeting its mission, vision, and values. Hospital administrators work closely with medical staff, board members, patients, and other stakeholders to make informed decisions that promote high-quality care, patient safety, and organizational growth. They may hold various titles such as CEO, COO, CFO, Director of Nursing, or Department Manager, depending on the size and structure of the healthcare facility.

An algorithm is not a medical term, but rather a concept from computer science and mathematics. In the context of medicine, algorithms are often used to describe step-by-step procedures for diagnosing or managing medical conditions. These procedures typically involve a series of rules or decision points that help healthcare professionals make informed decisions about patient care.

For example, an algorithm for diagnosing a particular type of heart disease might involve taking a patient's medical history, performing a physical exam, ordering certain diagnostic tests, and interpreting the results in a specific way. By following this algorithm, healthcare professionals can ensure that they are using a consistent and evidence-based approach to making a diagnosis.

Algorithms can also be used to guide treatment decisions. For instance, an algorithm for managing diabetes might involve setting target blood sugar levels, recommending certain medications or lifestyle changes based on the patient's individual needs, and monitoring the patient's response to treatment over time.

Overall, algorithms are valuable tools in medicine because they help standardize clinical decision-making and ensure that patients receive high-quality care based on the latest scientific evidence.

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  • They include: List of relational database management systems, for database management systems based on the relational model. (
  • Advanced Database Systems provides you with a deep and thorough understanding of both conceptual and technical topics connected to Relational Databases, Relational Database Management Systems (RDBMS), and Structured Query Language (SQL). (
  • Strong understanding of data structures and algorithms, as well as database management systems. (
  • The purpose of a bioinformatics platform within SWEGENE is to provide computational facilities and logistical support [databases, algorithms & infrastructure] for problem oriented scientists in an optimal way. (
  • For example, Amazon RDS, Microsoft Azure SQL Database and Google Cloud SQL are some of the leading cloud-based DBMS. (
  • View an educator-verified, detailed solution for Chapter 7, Problem 45 in Coronel/Morris's Database Systems: Design, Implementation, & Management (13th Edition). (
  • Implementation of relations in a Relational Database Management System (RDBMS). (
  • Database views and implementation of integrity constraints. (
  • Implementation of centralized, decentralized, and distributed databases. (
  • Evidence of existence and proper operation of the elements listed in Article 56 of the Financial Regulation, within the entity to be entrusted by the Commission with the implementation of EU funds in indirect centralised management, has been obtained. (
  • Routine health management information system database was reviewed from Addis Ababa Health Bureau for the period from July 2019 to March 2021 across all quarters. (
  • The course provides an overview of data management architectures and analytics procedures aimed at organising, describing and modeling Big Data (structured and unstructured). (
  • The contents of the course covers both technical aspects of data management / analytics and topics related to analysis managerial evaluation (how to translate the outputs into meaningful business insights). (
  • Introduction to data management and analytics. (
  • The course is offered on the fifth term of the Bachelor's programme in Design of Information Systems , to exchange students and as a freestanding course. (
  • Laboratory Services has continued, in management system (SAMI) database. (
  • and geographical information systems and spatial databases. (
  • To provide easier access to these data, the U.S. Bureau of Mines (USBM) is developing the Mine Accident Decision Support System (MADSS). (
  • The MCIS consists of a searchable database system made up of Bureau of Land Management and state of Alaska computerized mining claim records. (
  • sponsoring of algorithm knowledge, database building for specific applications, some computer related acquisitions such as software and databases. (
  • SmartGrid), to healthcare management and urban life (e.g. (
  • These solutions provide efficient ways to define, query, update, and administer databases for applications supporting daily operations and longer-term strategic initiatives. (
  • He is the co-author of three books (Principles of Database Query Processing for Advanced Applications, Advanced Metasearch Engine Technology and Deep Web Query Interface Understanding and Integration). (
  • WEB 107 Back-end Development Fundamentals takes students on a deep dive into the back-end systems that drive modern web applications so that they can gain a more holistic understanding of web development practices and tailor website content for individual users. (
  • Given the continued expansion of the database applications, Infortrend fulfils the demand for more storage requirement. (
  • WEB 108 Data Persistence builds upon fundamental back-end development knowledge and skills by familiarizing students with database management systems, frameworks, and methods for data storage and retrieval. (
  • Basic knowledge in databases and information systems. (
  • publications.html Geneva, World Health Organization 2008. (
  • This has accelerated the global migration of database systems to public, private and hybrid cloud environments. (
  • Lists of database management systems provide indexes and/or comparisons of different types of database management system. (
  • The standards provided by the Institute have been adopted for use throughout the United Nations system and provide independent, authoritative guidance designed to ensure an effective oversight function. (
  • The main purpose of a bioinformatics platform within SWEGENE should be to provide com- putational facilities and logistical support [databases & infrastructure] for scientists whose primary research in biology and medicine benefit from computational approaches. (
  • Bargaining power of buyers: Large organizations can negotiate better deals and pricing with database management providers due to high volume purchases. (
  • Atego is a world leading software tools and professional services company, focused on helping organizations engineer complex, mission- and safety-critical systems and software. (
  • Databases (DB) are used by organizations to collect information in one consolidated place for easy access, management, and update. (
  • She delivered a keynote address at the 35th International Conference on ICT Systems Security and Privacy Protection - IFIP SEC 2020 on September 21, 2020. (
  • The course utilizes the cloud platform Microsoft Azure for development and deployment of databases. (
  • One key trend gaining momentum in the database management system market is the increasing adoption of cloud technologies. (
  • cloudimg presents this Firebird SQL on Ubuntu Server 22.04 image preinstalled with system components such as AWS CLI, AWS CloudWatch Agent, AWS Systems Manager Agent, Python 3 & Cloud-Init. (
  • It helps the Organization to accomplish its objectives by bringing a systematic, disciplined approach to evaluating and improving the effectiveness of processes for risk management, control, and governance. (
  • The Office has full and prompt access to all records and personnel of the Organization, and can review all systems, processes, operations and activities within the Organization. (
  • The course uses AI-based tools and modern Integrated Development Environments (IDE) for development of database backends and clients. (
  • The global database management system market comprises software that helps organize, store, and analyze big volumes of disparate data sets. (
  • Bargaining power of suppliers: Providers of database management software have differentiation in offerings, switching costs for buyers are high. (
  • Firebird is an open-source, SQL relational database management system based on the open source edition of InterBase released by Borland Software Corp, formerly known as Inprise Corp. Developed in C and C++, Firebird supports major hardware and software platforms including Windows, Linux, and Mac OS X. Firebird offers many ANSI SQL standard features, allows simultaneous OLTP and OLAP operations through its multi-generational architecture, and supports stored procedures and triggers. (
  • The Firebird Project is a commercially independent project of C and C++ programmers, technical advisors and supporters developing and enhancing a multi-platform relational database management system based on the source code released by Inprise Corp (now known as Borland Software Corp) on 25 July, 2000. (
  • Exercises (exercises, database, software etc. (
  • A number of data ingestion procedures and machine learning data analysis case histories are shown, on Big and Small Data, using specific data management anf machine learning software. (
  • Infuse any system (ERP, fleet management software, own databases, etc.) with taxonomy standardized equipment data. (
  • Various software resources are also required to enable users to conveniently connect their experimental results with publicly, and application specific, bioinformatics databases and tools. (
  • Taking this course, you will develop your skills in designing and implementing database solutions that support business operations and business objectives. (
  • WEB 101 Agile Project Management introduces students to the principles and methodology of an agile approach to project management. (
  • In some patients, rectocele is thought to develop as a result of congenital or inherited weaknesses within the pelvic support system. (
  • As new features are developed for an application it is very likely that the database will need schema changes to support these features. (
  • There are, in conjunction with the genomics platforms built with SWEGENE support, in general systems for the immediate management of the large amounts of experimental data generated. (
  • You will gain a deeper understanding of relational database theory, models, methods, and an ability to use these in different scenarios. (
  • In this seminar we will research recent topics in data stream management and analysis, such as data compression, online learning, or operator distribution. (
  • AHO is seen as the core of a reinforced regional health information system, interacting with national health observatories in the Member States to contribute to monitoring and evaluation, data collection and analysis at national level. (
  • IARC's A report of the situational analysis, data management assistant position was facilities also serve as a custodian for conducted in 2013, was published created. (
  • Comparison of object database management systems, showing what fundamental object database features are implemented natively Document-oriented database, for storing, retrieving and managing document-oriented information List of column-oriented DBMSes that store data tables by column rather than by row List of in-memory databases, which primarily rely on main memory for computer data storage See Category:Database management systems for a complete lists of articles about database management systems. (
  • Receive a category system, technical specifications, images, datasheets, list prices, market prices / fair market values via an easy-to-integrate GraphQL standard API-interface. (
  • So having a single system-wide cache of the layout won't be correct. (
  • 3 Regional Committee documents: Resolution AFR/RC54/R3, Priority interventions for strengthening national health information systems. (
  • Patch 1 adds an "unknown" bank type so that sysfs initialization issues can be avoided on systems with new bank types. (
  • Patch 2 adds new bank types and error descriptions used in future AMD systems. (
  • Most of the platforms are expected to be connected to resources for handling various types of user interactions, conceivably with a back-end database management system and a front-end web based technique to handle user interactions. (
  • Threat of new entrants: Database management providers require high investments in technical know-how and infrastructure establishment. (
  • She received the IEEE Computer Society Technical Achievement award in 2002 for outstanding contributions to database systems and database security and advanced data management systems, and received the 2005 Tsutomu Kanai Award by the IEEE Computer Society for pioneering and innovative research contributions to secure distributed systems. (
  • Firebird is an open-source SQL relational database management system that runs on Linux, Microsoft Windows, macOS and several Unix platforms. (
  • Database design methodology is explicitly divided into three phases based on the widely accepted Entity-Relationship model: conceptual, logical, and physical.Each phase is described in a separate chapter with an example of the methodology working in practice. (
  • It could possibly automate aspects worth considering of the revenue process, consequently users can spend more time upon nurturing consumer relationships. (
  • Design Building Blocks to be easily portable across STLTs' systems with minimal lift. (
  • A CRM database contains a variety of details about a customer, which include demographics, acquisitions, and more. (
  • She discussed how IoT will usher automation in a large number of application domains, ranging from manufacturing and energy management (e.g. (
  • Les technologies sont mises en place à a) E-mail (electronic mail): The most grande échelle dans les pays développés et aussi dans certaines petites régions des pays en widely used application on the internet, développement. (
  • Information Management Systems), which allow for collection and processing of large data sets. (
  • Performance management systems are quickly becoming more popular. (
  • It scales impressively from a single-user model to enterprise-wide deployments with multiple databases running with hundreds of simultaneous clients. (
  • The most common type of DB storage structures are Relational Databases where the data is stored in relations, taking the form of tables made of columns (fields) and rows (records/items). (
  • Her keynote, titled, "Data Security and Privacy in the IoT," highlighted the way IoT makes it possible to sense and control objects creating opportunities for more direct integration between the physical world and computer-based systems. (
  • Her research interests cover many areas in the fields of information security and database systems. (
  • Professor Bertino serves or has served on the editorial boards of several journals - many of which are related to security, such as the ACM Transactions on Information and System Security, the IEEE Security & Privacy Magazine, and IEEE Transactions on Dependable and Secure Computing. (
  • Almost every company is facing poor quality in historically grown (equipment) databases. (
  • Group required a stronger process radioisotopes was renewed, and per- quality control measures, the Biobank management role and data management mis sion to use genetical y modified participated in international proficiency capacity. (
  • Data stream management systems are special systems which address the specific requirements handling data streams. (
  • Competitive rivalry: The database management industry has dominant global and regional players. (
  • The Global Database Management System Market Size is estimated to be valued at US$ 64.7 Bn in 2024 and is expected to exhibit a CAGR of 9.8% over the forecast period 2024 to 2030. (
  • North America currently holds the largest share in the database management systems market, both in terms of value and volume. (
  • The final exam covers mainly the data ingestion and management topics. (
  • These technologies are paper is to give an overview of technolo- being implemented en masse in developed countries, but also in some pockets of gies that are having or will likely have the developing nations as well. (
  • Simple Client Database is a client management system written in PHP and JavaScript. (