'Techonology and Decision Making Paper Hcs 482\r'

'Running channelize: TECHNOLOGY AND DECISION MAKING engine room and determination do University of Phoenix wellness c atomic number 18 Informatics HCS/482 Richard Ong November 15, 2008 engineering science and end Making Technology, termination-making processes, and data accessibility have changed dramatic ally in recent years. This paper contrive discuss transcriptions and culture cognizance theories. The paper ordain confer on the selective discipline, info, and intimacy (DIK) Model. The fictional character of full system in treat cargon and medicine include for be yieldd. examineing back up and closing concentrate systems ar employ every mean solar day providing focus, leading and direction within technology and entrust be examined.\r\nThe implement of technology for persevering and client precaution will be explored. An epitome of the impact of technology on healthcargon and health status will be investigated. Systems and Informatics Theories Systems ar â€Å"a group of interacting, inter cogitate, or interdependent elements forming a complex whole” (Systems, n. d. , Definition). Systems describe health look at, schools, computing devices, and a person. The systems ar either open or closed. Closed systems argon inoperable to make with a nonher(prenominal)s third ships fellowship products and open systems are designed to allow third party products to plug in or interoperate with the system.\r\nneither system interacts with the environment. Open systems consist of terzetto characteristics; purpose, functions, and structure (Englebardt and Nelson, 2002). Systems john have to a greater extent than one purpose ground on the claims of the user. Functions that the system will need to carry out need to be identified for the system to achieve its purpose. The â€Å"systems are structured in ways that allow them to bring to pass their functions” (Englebardt & Nelson, 2002, p. 6). The two types of mo dels utilise to create mentally the structure of a system; graded and web (Englebardt & Nelson, 2002).\r\nSome examples of system applications are; institution wide, specialty support, documentation, administrations, operations, expert, stand only if culture, and close support. The study of health apprehension informatics incorporates theories from development Nursing science, computer science, cognitive science, along with other sciences employ in the health care address (Englebardt & Nelson, 2002). Three models that embody the informatics theories are; Shannon and Weaver’s reading-communication model, Blum’s model and The Nelson data to science continuum.\r\nShannon and Weaver’s model states that a nub starts with the transmiter and is converted to a code by the encoder. The converted meaning wad be letters, words, music, symbols or a computer code (Englebardt & Nelson, 2002). The message is carried by a channel and along with the message noise is transmitted in the length to the decoder where the message is converted to a format that is understood by the receiver. â€Å"Bruce L. Blum certain a definition of information from an analysis of the accomplishments in health check deliberation” (Englebardt & Nelson, 2002, p. 12).\r\n accord to Blum the three types of health care computing applications are; data, information and association (Englebardt & Nelson, 2002). Data is information that is not interpreted. Data that is processed and displayed is categorize as information and when the data and information are combined and formalized knowledge results (Englebardt & Nelson, 2002). â€Å"A knowledge base includes the interrelation between the data and information” (Englebardt & Nelson, 2002, p. 13). The Nelson Data to Wisdom Continuum states the four types of healthcare computing applications are; data, information, knowledge and wisdom.\r\nThe four coincide at all t imes. Data is the naming, assembling and organizing the message. development is further organizing and interpreting the message. fellowship occurs when the message is interpreted, integrated and understood. Wisdom is the talent to understand and hold in the message with compassion. Data, Information and Knowledge Model â€Å"Nursing informatics, as delimit by the American Nurses Association(ANA), is a specialty that integrates breast feeding science, computer science and information science to manage and make known data, information and knowledge in nurse practice” (Newbold, 2008, para. 1).\r\n come uponing making by healthcare professionals is found on the immersion of data, information and knowledge to support persevering care. Organizing data, information and knowledge for the processing by computers is accomplished through the use of information technology and information structures (Newbold, 2008). The first aim is data which â€Å"…are recorded (cap tured and stored) symbols and signalize readings” (Liew, 2007, Definitions). Data is bits of information though to only when have data is not meaning(prenominal) to decisiveness making. The second take aim is information which is organized, interpreted and communicated data between machines or humans. Characteristics of musical note information are: eff and come active in its descriptions, accurate, measurable, preferably by measurable objective means much(prenominal) as numbers, variable by free observers, promptly entered, rapidly and easily usable when needed, objective, rather than subjective, comprehensive, including all necessary information, enchant to each user’s involve, clear and unambiguous, reliable, easy and convenient form to interpret, classify, store, imagine and update” (Theoretical issues, 1998, Concepts).\r\nKnowledge is the third train of the model and is the collection of information that is obtained from some(prenominal) inc eptions to produce a concept used to achieve a basis for arranged decision-making. The information needs to be utilizable and applied to be known as knowledge. The final level is Wisdom which â€Å"…is the highest level of existence able to understand and apply knowledge exploitation compassion” (Theoretical issues, 1998, Concepts). â€Å"Information consists of data, but data is not inevitably information. Also, wisdom is knowledge, which in turn is information, which in turn is data, but, for example, knowledge is not inevitably wisdom.\r\nSo wisdom is a subset of knowledge, which is a subset of information, which is a subset of data” (Steyn, 2001, para. 2). Without an understanding of the source of data and information which is based on activities and situations, the kind between data, information, and knowledge will not be understood (Liew, 2007). technical Systems in Nursing Care and medicament aesculapian artificial science is earlier concerned w ith the structure of Artificial lore (AI) programs that perform diagnosis and make therapy recommendations. contradictory checkup applications based on other programming methods, such as stringently statistical and probabilistic methods, medical AI programs are based on exemplary models, such as statistical and probabilistic methods, medical AI programs are based on symbolic models of disease entities and their relationship to uncomplaining factors and clinical manifestations’ as defined by Clancey and Shortliffe (1984). Expert systems (ES) in nursing care and medicine fill an provide role with intelligent programs offering probative benefits.\r\nThey hold medical knowledge containing specifically defined tasks and are able to reason out with data from individual patients responding with reasoned conclusions. The advantages of an expert system over a pay off are: 1. A mountainous database of knowledge can be added and kept up to date with the ability of a abundan t amount to be stored. 2. The system does not forget or get facts wrong. 3. The move existence of the knowledge is forever not lost with death or retirement. 4. The computer can make contact with specialist knowledge that a remediate whitethorn not have. . The ES whitethorn scale down time to make the correct diagnosis and reduce diagnostic errors. 6. Countries with a braggy number of population and have physicians are limited can receive medical knowledge leading to prompt care. ES’s are not transposition doctors or nurses but are universe used by them stimulating an interrogated large database of knowledge of a human expert. finding Aids and stopping point Support Systems Decision support systems (DSS) are systems that â€Å"model and provide support for human decision-making processes in clinical situations.\r\nThey are travel technologies that support clinical decision making by interfacing evidence-based clinical knowledge at the point of care with real-time c linical data at significant clinical decision points”(Gregory, 2006, p. 21). Decision support systems offer various methods of decision support, including recommendations for diagnostic testing, searing lab order alerts, jockstrap with diagnosis and advice for clinicians on what medications to use. fit to the British Medical journal, â€Å"Clinical decision support systems do not continuously modify clinical practice, however.\r\nIn a recent systematic review of computer based systems, most (66%) significantly modify clinical practice, but 34% did not” (Kawanoto, Houlihan, Balas, & Lobach, 2005, p. 769). Decision support systems can improve patient outcomes however; more(prenominal) studies are needed to develop better systems. Decisions by their very nature are uncertain, medical decisions have the added complexity of involving an individual’s honours and beliefs as related to the risk-benefit profiles or uncertain outcomes of medical treatment. Th e goal of use a decision aid is to stand by the patient make informed decisions based on his or her belief and value system.\r\nLimited and conflicting research on the use of decision aids makes it unsufferable to determine if having patients use a decision aid would benefit him or her. harmonise to an article published in the Medical Decision Making Journal â€Å"Decision aids are a burnished saucily technological innovation in health care, however, like any bare-ass innovation, their widespread adoption needs to be preceded by a careful evaluation of their effectiveness harms, rather than an uncritical onward motion of their potential benefits” (Nelson, Han, Fagerlin, Stefanek, & Ubel, 2007, p. 617).\r\nDecision aids can be an important addition to promoting divided decision making between the physicians and patient however, decision aids â€Å" may send the wrong message to patients about the goals of decision making, or lead patients to believe that they can reduce or eliminate incertitude when confronting decisions” (Nelson, Han, Fagerlin, Stefanek, & Ubel, 2007, p. 618) Technology for Patient and Client forethought Technology can be used in umpteen areas of patient and client management. Technology is said to have the potential to bring the patient and healthcare providers unitedly creating patient-centered care.\r\nThe goal of patient-centered care is to empower the patients, give patients choices and tailor treatment decisions based on the patient’s beliefs, values, cultural traditions, their family situations and their lifestyles. Technology impacts this concept when healthcare providers use clinical information systems such as compound patient registration systems which uses the internet or onsite wireless devices, using decision aids and decision support systems, Tele observe Devices, and the electronic health record.\r\nNew technology will divine service healthcare providers with patient management by increasing the ability of healthcare providers to mobilise and apply accurate information about their patients quickly and allow patients to acquire information to improve control of their diagnosis and or treatments and to talk with their healthcare providers. Technology on Healthcare and Health Status analytic thinking The future holds many another(prenominal) technological changes that will affect healthcare directly and help shape our already powerful profession.\r\n technological advances will dramatically change healthcare provider’s roles and the healthcare delivery systems. Computers are not unusual for a patient to use to surf the lucre to find information related to the diagnosis. Patients may alike browse the Internet and find conditions here the symptoms are closely related to what he or she is experiencing. He reads all he can find, and when he goes to the doctor he may be informed, misinformed, or over-informed, regarding the possible diagnosis of his prob lem. Technology presents to the healthcare consumer a tremendous resource of information regarding his healthcare.\r\nComputers, biosensors, implants, transmitted therapies, and im develop devices are examples of the uphill technologies of the 21st century. Medical artificial intelligence in contexts such as computer-assisted surgery, cardiography and fetal monitoring interpretation, clinical diagnosis, and genetic counseling will have a major impact on our future. Telemedicine shortly ranges from radiographic consultations across cities to telebiotic surgeries across hemispheres (Cohen, Furst, Keil & Keil, 2006). interactive disks already assist patients to make more independent medical decisions regarding their care.\r\nDevices for home use can help monitor short letter pressure and blood glucose or perform a pregnancy test. Technology also helps assist patients with finding information regarding a diagnosis. Although technology is very beneficial to healthcare other concer ns continue to exist. Every day healthcare providers use complex machinery, including many types of monitors, ventilators, intravenous pumps, feeding pumps, suction devices, electronic beds and scales, lift equipment, and assistive devices. The directions for use of many of these machines are not self-evident and may be highly complicated.\r\nAs a result, some patients may endure smirch secondary to misuse of the product (Cohen, Furst, Keil & Keil, 2006). The company may also incur unexpected expenses if the equipment becomes damaged and need to be replaced. Similarly, pertly computer systems present many reading difficulties for healthcare providers. Many computer systems are not user friendly. Computer systems designers are notorious for supplying computers with numerous advanced but obscure functions, but these systems often lack the ability to make nonchalant tasks easier t accomplish. Millions of dollars have een wasted on computer systems that are not used or are und erused because the user needs were not assessed before the systems were designed (Thielst, 2007). in that respect remain three basic reasons for the proceed increase in healthcare cost: inflation, increased demand for services as a result of federal programs such as Medicare and Medicaid, and expensive technological advances in medicine. Conclusion In conclusion, significant economic and social trends are dramatically fixture the forms of healthcare delivery in the unite States and the roles played by healthcare providers.\r\nAdvances in technology, globalization of culture and communication, ever-widening computer applications, aging of the population, and dynamic changes in the healthcare exertion are among major developments (Thielst, 2007). To cope with and to convey to the future of healthcare, the healthcare team must(prenominal) understand how computers are now being used in healthcare, and they must be able to work with computers in a cost-effective manner in their h ealthcare practice.\r\nNo matter what delivery system is in place in a particular institution, healthcare providers will find that each is vitally involved with ensuring quality and in discovering measurable ways of monitoring quality. References W. J. Clancey and E. H. Shortliffe, eds. (1984). Readings in Medical Artificial learning: First Decade. Reading, Massachusetts: Addison-Wesley. Cohen, T. , First, E. , Keil, O. & Wang, B. (2006). Medical equipment management strategies. Biomedical Instrumentation & Technology, 40(3), 233-238.\r\nEnglebardt, S. P. , & Nelson, R. (2002). Health care informatics: An interdisciplinary approach. St. Louis, MO: Mosby Elsevier. Gregory, A. (2006, January/March). Issues of desire and Ethics in Computerized Clinical Decision Support Systems. Nursing Administration Quarterly, 30(1), Pp. 21-29. Kawanoto, K. , Houlihan, C. , Balas, A. , & Lobach, D. (2005, April 2). better clinical practice by using clinical decision support syst ems: A systematic review of trials to identify features critical to success. BMJ, 330, P. 765-700. Liew, A. (2007, June).\r\nUnderstanding data, information, knowledge and their relationship. Retrieved November 10, 2008, from Journal of Knowledge Management Practice: http://www. tlainc. com/article 134. htm Nelson, W. , Han, P. , Fagerlin, A. , Stefanek, M. , & Ubel, P. (2007, October 1, 2007). Rethinking the Objectives of Decision Aids: A Call for conceptual Clarity. Medical Decision Making, 27(5), Pp. 609-618. Newbold, S. (2008). A new definition for nursing informatics. Retrieved November 10, 2008, from Advance for Nurses: http://nursing. advanceweb. com/ article/A-New-Definition-for-Nursing-Informatics. spx Steyn, J. (2001). Data, information, knowledge and wisdom. Retrieved November 12, 2008, from Knowsystem: http://knowsystems. com/km/definition. html System. (n. d. ). Retrieved November 11, 2008, from Answers. com: http://www. answers. com/ question/system Theoretical Is sues. (1998). Retrieved November 10, 2008, from University of Texas at Tyler: http://www. uttyler. edu/nursing/ckilmon/ni/theory. htm Thielst, C. (2007). The future of healthcare technology. Journal of Healthcare Management, 52(1), 7-10. Retrieved from ProQuest database on November 11, 2008.\r\n'