Information Technology In Healthcare

Sources Sayles, B. N., (2013), Health Information Management Technology: An Applied Approach. Chicago: American Health information management Association.

Since many health information infrastructure systems are relatively new, there is still variability in the implementation stages that different organizations have achieved. Additionally, most systems will have more than one capability that provides value, so the relationship between the system’s functionality and the resulting impact to patient care must be analyzed in order to determine the value it provides (Einstein, Juzwishin, Kushniruk, & Nahm, 2011). Value of health information infrastructures can be assessed in many different ways, including whether the technology allows the availability of useful information, how that information is utilized by staff and patients, and its impact on health outcomes. For information to be of value and influence medical decision making, it must be comprehensive, accessible, useful, and valid (Fitterer, Mettler, Rohner, & Winter, 2011).

Computer-based algorithms provide patient-specific assistance. An early warning system that provides timely alerts designed to ensure that appropriate actions are initiated as soon as problems begin to develop. Four key applications have been developed to achieve these goals.

A healthcare chief information officer (CIO) is “an executive at a healthcare organization that oversees the operation of the information technology (IT) department and consults with other C-level personnel on technology-related needs and purchasing decisions” (Margaret, 2015). The emerging role of a CIO is versatile and quite challenging. Besides providing software and computer support, nowadays CIO’s role also involves providing strategic business leadership along with operational and tactical activities such as ensuring maintenance, safety and privacy of patient’s medical records. The CIO possess various responsibilities such as assessing current and future technological needs of the organization, managing day-to-day operations of the

This includes creating, managing and following patient data. The American Health Information Management Association (AHIMA) defines information governance as “an organization wide framework for managing information throughout its lifecycle and for supporting the organization’s strategy, operations, regulatory, legal, risk, and environmental requirements.” In today’s healthcare system, it is more important than ever to know and understand how healthcare information is created, transferred and used. Due to the development of systems such as electronic health records and clinical decision support systems it is important that health information maintains its reliability and validity throughout its

Week 9 Overcoming Factors That Impact Informatics Initiatives DB Main Post Informatics impacts the healthcare setting, through the implementation of EHRs. A nurse informaticist not only manages the implementation of technology but follows guidelines set by ANA. Growth in nursing is moving forward as technology is erupting on the scene. The purpose of this paper does nurse impact leadership change for nurses moving into nursing informatics. Can implementation of technological transformation the care of patients, and components of ANCC Magnet health care set?

Technology in today 's Health Care The United States health Care system is in need of an overhaul. Electronic Health Records helps to maintain and ensure safe

Abstract The use of medical AI in the healthcare industry has been a topic of much discussion and excitement in recent years. However, there is a growing concern that the hasty adoption of these technologies may be premature, and that the potential risks and drawbacks outweigh the potential benefits. This paper argues that at this stage, it is advisable to avoid using medical AI in healthcare.

The Health Information Technology for Economic and Clinical Health Act promoted the adoption and meaningful use of health information technology. This Act enacted as part of the American Recovery and Reinvestment Act of 2009. It encouraged the widespread use of electronic health records across the country; the largest in United States to date. The purpose of this paper will summarize the benefits of an Electronic Health Record. The three key functionalities of Electronic Health Records are computerized order entry systems, health information exchange and clinical decision support systems.

Health Information Exchange (HIE) sounds like a lofty concept but it enables health care professionals and patients to securely share and access a patient’s vital medical information electronically. It is the ability to transmit healthcare information across organizations within a healthcare system such as a hospital, a community, state or region. state. In this paper, I will focus on the key concerns of healthcare leaders have about health information exchanges and whether it has helped healthcare in terms of delivery, quality of care and cost savings. Also, whether health information exchanges have become an essential part of the healthcare system and how close is the United States to the goal of nationwide implementation.

However, if no appropriate technique is developed to find great potential economic values from big healthcare data, these data might not only become meaningless but also requires a large amount of space to store and manage. Over the past two decades, the miraculous evolution of data mining technique has imposed a major impact on the revolution of human’s lifestyle by predicting behaviors and future trends on everything which can convert stored data into meaningful information. These techniques are well suitable for providing decision support in the healthcare setting. To speed up the diagnosis time and improve the diagnosis accuracy, a new system in healthcare industry should be workable to provide a much cheaper and faster way for diagnosis [1]. Clinical Decision Support System (CDSS), with various data mining techniques being applied to assist physicians in diagnosing patient diseases with similar symptoms, has received a great attention

Dr. Song, Clinical Decision Support has been defined as a “process for enhancing health-related decisions and actions with pertinent, organized clinical knowledge and patient information to improve healthcare, as well as, healthcare delivery (Campbell & CPHIMS, 2013). Clinical Decision-supporting tools are utilized to manage and support patient care. Healthcare information systems and information-retrieval systems are tools that manage information. There are various programs that provide custom tailored assessments or advice based on sets of patient specific data (Musen, Middleton, & Greenes, 2014, p. 701). Decision tools may follow simple logics (such as algorithms), may be based on decision theory, cost benefit analysis, or may use numerical approaches only as an adjunct to symbolic problem solving (Musen, Middleton, & Greenes, 2014, p. 701).

We must filter and customize that downloaded data for the health conditions that we primarily try to improve. Once data is customized and filtered properly, it gives us “care gaps”. Those care gaps can be easily closed out by accessing patient’s EMR or by referral. This updated data then gets uploaded back to the healthcare insurance company data set for reporting purpose. Data analytics helps health profession close the care gaps and improv care coordination between

Population Health Management means proactive application of strategies and interventions to defined cohorts of individuals across the continuum of healthcare delivery in an effort to maintain and/or improve the health of the individuals within the cohort at the lowest necessary cost. With the new era of healthcare, a good population management system in place is critical to a health system. Organizations will grow to become dependent on data and analayis in order to carry out actions or what not within the said system. Furthermore, with the advent of information technology and a well-designed population health tools, it can create substantial impact to the patient through electronic medical records and healthcare information exhancge,;

Or in simple terms it may be defined as the process for extracting or mining knowledge from large amounts of data. So the chapter 3 will provide a brief overview on the various datamining techniques. This is because there should be a clear understanding on the basic principles of the area of concern because any research is incomplete without the knowledge of the basic principles. So not only that the chapter gives the idea about data mining it also describes some of its techniques which leads to the ability to differentiate each one of them from other and allows one to explore the possibilities amongsts them. To do so the techniques studied in this chapter in brief are Association Rule, classification rule, Frequent Episodes and Deviation