Clinical Decision Support System Essay

Standing (2011), defines clinical decision-making as a complex process that involves observation, gathering information, critical thinking, evaluating evidence, applying necessary knowledge, reflection and problem-solving skills. Every day nurses make important clinical decisions and these decisions have important implications for patient outcomes and deserve serious consideration. Therefore, it is important for nurses to have a better insight of the decision-making process, be able to deliver holistic care and meet essential and complex physical and mental health needs of the patient.

UHN in Toronto is a major community care network that reaches out to and provides care to the masses. However in order to provide this kind of care they must have a very powerful decision support system. UHN utilizes an advanced CPR to support computerized physician order entry (CPOE). (Wu, Perters, & Morgan, 2002) A CPR system is a computer-based patient record system. A CPR system must provide a comprehensive clinical decision support it must include both a patient focus and a population focus. The physical computer system that is installed on the computers at UHN is called Patient 1® which is a clinical information system developed by Atlanta Based Per-Se

Healthcare can be known for a complex industry. Every day is a new day facing complicated clinical administrative transactions with electronic medical records and safety? Health Information technology is suppose to realize errors using electronic medical records. Leaders must understand the complexity and safety issues in order to help mandate electronic medical records with design, development, implement and use. In the last decade, this article has informed executives, clinicians, and technology. Their main focus was on these three areas computerized physicians order entry. Their main focus was to work all three areas computer physician order entry, computer decision support system,

Clinical Decision Support System (CDSS) has potential chances to enhance general security, quality what's more, cost-adequacy of human services. The CDSS has existed for over four decades, yet its selection rate by therapeutic groups is not empowering even in the nations that have been a pioneer in creating them. At numerous locales, it was hazardous, slowed down in the arranging stages or never at any point endeavored. To date, CDSS is considered as an incompletely effective framework. A few current difficulties have not been enough tended to amid the improvement of CDSS. According to most recent research, the arrangements of difficulties are: enhance the human-PC interface,

I think the use of clinical decision support in healthcare organization is very paramount, because of its numerous advantages, just to mention a few, through the use of CDS there is increased in quality of care and positive outcome

Part of this CDS system would drive key decision making development process for provider as well as real time support, information and diagnosis related pieces. Complex rules once added to CDS, while placing orders through CPOE, system can alert user to check for allergies, overdose of medication and duplication of medication or orders. CPOE along with CDS would not only have these limited benefits but could also help improve hospital’s workflow, rapid and accurate plan of care, quality of care, reduce the cost of care along with being compliant on department of health regulations and guidelines. CPOE has reach not only to inpatient but ancillary environment as well making it more efficient for hospital use. Since both the system CDS and CPOE work alongside it make the process of orders rapid, accurate, decreases order confirmation time to zero and better turnaround time for outcome results.

The purpose of this study is to develop and assess the usability and effect of a problem focused clinical decision support tool designed to improve medical decision-making. The overall goal is to design an effective dashboard that will support both rapid pattern recognition and slower, more deliberative reasoning and analysis of information, when managing the care of complex patients. The dashboard design may support cognition by simplifying and grouping information to enhance pattern recognition and prompt situational awareness. It is anticipated that by lowering the effort required to obtain needed information, greater efforts in managing the problem will occur. Specifically, we want to know if the dashboard enhances knowledge of patients baseline cognitive status & delirium risk, if confidence in this knowledge is increased by providing supportive information, and if more appropriate risk prevention strategies will be ordered, as compared to the regular presentation of information.

Clinical decision making is a contextual, continuous, and evolving process, where data are gathered, interpreted, and evaluated in order to select an evidence-based choice of action. An Effective Practitioner is tasked with making clinical decisions with patients and clients many times during their health and care journey. Factors that affect decision making There are many factors involved in clinical decision making and each of the core skills has the potential to impact effective decision making. 1.Knowing the evidence – Any clinical decision maker should rely on a knowledge base which contains a wide array of literature review. Thanks to the digital advancements and technology, we can embed a wide variety of information in the form of E-books, articles, journals, reference materials related to the current practice, so that we as a clinical decision makers can rely on them for decision making process or even patients if they want information about the disease or treatment protocols, can utilise to research the evidence base, many of the physicians as well are simply referring them a bunch of latest treatment articles or their website link in their portals to justify their

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

You bring up an excellent point about Clinical Decision Support (CDS) tools, workflow and cultural changes must occur to ensure success of implementation. This will be a major paradigm shift for providers. Clinicians tend to hold on to what we know and what makes our workflow seamless. However, personally, I have survived several major changes to my workflow process over the years, in fact, at the start of every Federal fiscal year, I need to adjust my workflow to integrate regulatory changes to the Minimum Data Set (MDS). After a period of pain and resistance, I adjust to the change and continue within my new workflow.

Clinical Decision Support Systems (CDSS) can be described as information systems to improve the decision making ability of people interacting with it (Niès, Colombet et al. 2010). Hospitals with integrated Health Information Systems (HIS) are encouraged to utilize CDSS (Jonathan Teich 2012). Multiple fragments such as Electronic Health Record (EHR), laboratory information system, Computerized Physician Order Entry (CPOE), radiology information system and pharmacy information system combine together to form an integrated HIS (Niès, Colombet et al. 2010). Each piece of the HIS is essential to generate proper CDSS suggestions in the form of on screen alerts, that have been found to be most effective (Shojania, Jennings et al. 2009).

Clinical Decision Support Systems (CDSS) can be described as information systems to improve the decision making ability of people interacting with it(Niès et al., 2010). Hospitals with integrated Health Information Systems (HIS) are encouraged to utilize CDSS(Jonathan Teich, Saldana, & Levick, 2012). Multiple fragments such as Electronic Health Record(EHR), laboratory information system, Computerized Physician Order Entry (CPOE), radiology information system and pharmacy information system combine together to form an integrated HIS(Niès et al., 2010). Each piece of the HIS is essential to generate proper CDSS suggestions in the form of on screen alerts, that have been found to be most effective(Shojania et al., 2009).

The development and implementation of decision support systems within the clinical field represent a myriad of methodologies. While most institutions have adopted the IT centric or traditional approaches of DSS development and implementation, experts have recommended a user centric approach as an alternative method. If the user centric model is initiated within the industry, it makes it possible for the management to justify decisions through value analysis (Burstein & Holsapple, 2008). The development and implementation of DSS within the clinical setting demands a set of continuous and expensive endeavors. Project managers must initiate coordinated technical, human, and clinical efforts in engineering the required expertise for a prolonged period.

The introduction of the computerized management systems into healthcare took place over 50 years ago. Since then systems have evolved and become more intricate. They now serve many purposes that benefit patient care. It is a very large and important decision when a healthcare system must choose a specific computerized management system; from function, security, user friendliness, and cost. When this decision is made by a healthcare organization, one must take into account many aspects of this choice, which is defined as:

Abstract: In this paper, a new Clinical Decision Support System (CDSS) Framework was proposed which satisfies the compatibility, interoperability, and scalability objectives of EHR. The system will also have a set of Distributed Electronic Health Records and centralized Knowledge Engines. These Electronic Health Records are minimized and distributed In some parts of the country Knowledge Engines are centralized and work together. Each centralized Knowledge Engine is specialized in a specific domain.