Decision Support Systems For Aide

This paper looks at the main issues faced by decision makers, analyses them, presents alternatives and makes recommendations based on the analysis.

Analyze the requirements of the system and how this DSS is reducing medical errors and improving clinical practice.

Decision support systems (DSSs) help professionals make decisions by determining the most favorable options to a “What if?” question. Using raw data, DSSs can make comparison and generate new information to assist in decision making.

For the electronic health record to be considered as a true clinical decision support system, it must be possible to access and integrate patients’ clinical information that is collected throughout their lives, guaranteeing up-to-date, safe and congruent information, immediately accessible at the place of care. Moreover, because of the considerable increase in the capacity to develop and manufacture systems that employ smart components highly integrated and miniaturized, wearable devices facilitate the home monitoring of patients with chronic diseases and their information should be integrated in existing electronic health records. Therefore, the interoperability is an essential requirement of eHealth to allow the integration of care into a

Decision support system can be categorized into five types. These types include communication-drive DSS, data-driven DSS, document-driven DSS, knowledge-driven DSS, and model-driven DSS. “Most communications-driven DSSs are targetted at internal teams, including partners.” (Power, n.d., para. 5) “Most data-driven DSSs are targeted at managers, staff and also product/service suppliers.” (Power, n.d., para. 6) “Document-driven DSSs are more

According to Blumenthal-Barby, et al. (2013), patient decision aids are intended to assist the patients to make decisions about health care. These aids are designed to be neutral, non-directive, and unbiased. However, the authors argue that this should not always be the goal of such patient aids. They identify three specific areas where this balance may not be the best alternative. These situations include early stages of prostate cancer, deep vein thrombosis and colorectal cancer screening.

The HITECH Act of 2009, was signed into law as part of the stimulus package which represented the largest US initiative which was designed to encourage the use of electronic health records. The purpose of this paper is to review the benefits and setbacks of clinical decision support system that is combined with computerized physician order entry.

In recent years, there has been a growing interest in the application of clinical decision-support systems (CDSS) in the prevention and control of ischemic heart disease (IHD); this is due to an increasing recognition that stronger CDSS are crucial to achieve a high quality care with attendance lower morbidity and mortality.1 CDSS is defined as “computer-based information systems designed to assist health care providers in implementing clinical guidelines at the point of care. CDSS use patient data to provide tailored patient assessments and evidence-based treatment recommendations for healthcare providers to consider1”. Patient information is entered manually or automatically through an electronic health record (EHR) system2,3.

Murphy, E. (2014, 6 6). Clinical Decision Support: Effectiveness in Improving Quality Processes and Clinical Outcomes and Factors That May Influence Success. Retrieved 10 6, 2017, from www.ncbi.nlm.nih.gov: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4031792/

Clinical decision-support systems (CDSS) apply best-known medical knowledge to patient data for the purpose of generating case-specific decision-support advice. CDSS forms the cornerstone of health informatics research and practice. It is an embedded concept in almost all major clinical information systems and plays an instrumental role in helping health care achieve its ultimate goal: providing high quality patient care while, at the same time, assuring patient safety and reducing costs. This computer based systems designed to impact clinician decision making about individual patients at the point in time that these decisions are made. If used properly, CDSS have the potential to change the way medicine has been taught and

Decision making refers to the process of finding and selecting options according to the priorities and values of the person making the decision. Since there are many choices involved, it is important to identify as many options as possible so as to pick the option that best fits a company’s target, goals, values and vision. Due to the integral role of decision making in company growth and financial progress, many firms such as Amazon.com and EBay are pumping in huge investments in business intelligence systems, which are made up of certain technological tools and technological applications that are created for the purpose of facilitating improved decision making process in

Clinical decision support system (CDSS) is a technology application that assists clinicians at the point of care to make clinical decisions for patients with specific conditions. The healthcare is implementing many electronic tools that are aimed at improving health and health care delivery. It is designed to make clinical decisions about patient care.

Decision analysis has been used in almost every industry. In some areas with more success than in the others but generally we can claim that there is hardly any field of life which has not made use of it. Some areas where these techniques worked well are petroleum, pharmaceuticals and electric power industries (Howard 2007).

Although this system has some persuasive advantages, it could also be opposed because it might be deskilling decision markers. The use of this system could result in the unwarranted reliance on the system in decision-making and the

9. How can computerized DSS support the management at each stage of the Simon's Decision