Clinical Decision Support Systems ( Cdss )

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

An interview with an Assistant Professor at Duke University Health System in the Department of Medicine, Maestro Care Provider Champion and Clinical Content Architect. This physician works to incorporate clinical decision support tools into the electronic health record at Duke Health System. He manages the best practice advisory committee that may provide a way to deploy alerts to clinicians at the point of care. Alerts with order sets and recommended actions are created and updated to notify providers of current patient care guidelines or patient safety concerns.

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,

Alert fatigue and using a clinical decision support system (CDS) in an electronic health record is a growing concern in health care. Although alerts and warnings in an EHR are well intended, the volume of alerts EHR end-users receive is surprising. The Agency for Healthcare Research and Quality (AHRQ) estimates that in some EHR end-users have the potential to receive over 100 CDS alerts per day (Agency for Healthcare Research and Quality [AHRQ], 2015, p. 1). This cause’s alert fatigue when the end-users become desentized to the alerts and even the most important alerts become meaningless.

Technology, decision-making processes, and data accessibility have changed dramatically in recent years. This paper will discuss systems and informatics theories. The paper will confer on the Data, Information, and Knowledge (DIK) Model. The role of expert system in nursing care and medicine will be provided. Decision aids and decision support systems are used everyday providing focus, leadership and direction within technology and will be examined. The use of technology for patient and client management will be explored. An analysis of the

Electronic Health Systems are equipped with many features that are designed to reduce medical errors and help navigate patients through the healthcare system. One system that is worth looking at is the MedicsDocAssistant™ (MDA™). MDA™ supports many features such as alerts (“MedicsDocAssistant,”). Alerts will pop up on a provider’s screen letting them know that there is something wrong with the patient’s care. Alerts can range from prescription alerts, warning physicians of potential adverse drug effects or allergy complications, to alerts pertaining to clinical decisions regarding patient examinations, procedures and screenings that may be crucial. For example, the system will alert to the physician to remind female patients of a certain age to schedule a mammogram screening. The objectives of these alerts are to aid in properly diagnosing patients, identifying gaps in care, running appropriate tests as well as improving patient outcomes (“How EHR Alerts,” 2012).

As the technology is being implemented in health care system, computerized provider order entry (CPOE) has become the standard of care in most hospitals. According to Cherry and Jacob (2014), “CPOE contributes to safety and quality by eliminating lost orders automatically, monitoring for duplicate or contradictory orders, and reducing time to fill orders” (p 256). However, there are some barriers using the system which leads to medical errors including alarm However; some barriers are using the system which leads to medical errors including alarm fatigue, lack of communication, and clinicians’ hesitance to adapt to new system. CPOE alert physicians on a constant basis about “various drug-drug, drug-patient, and guideline-based recommendations during the ordering process” causing alert fatigue in clinicians (Payne & Weir, 2015, p 6).

Wager, K. A., Lee, F. W., & Glaser, J. P. (2009). Health care information systems, a practical approach for health care management. (2nd ed.). Jossey-Bass Inc Pub.

Real time data entry, real time data driven medical decisions, provides real time transport of medical records, increased productivity as there is shift from paper-based medical record and the real time approach. It helps in efficient patient care management. The EHR embedded with clinical decision support system also helps in improving health care services delivery. The rules and decision algorithms helps in healthcare decision making. CPOE allow providers to enter order and both CPOE and CDS help in reducing medical errors. One of the studies have showed that the serious medication errors can be reduced by as much as 55% when a CPOE system is used alone, and by 83% when coupled with a CDS system that creates alerts based on what the physician orders [3].

The scenario selected for this evaluation project focuses on the electronic health record. The scenario involves patient documentation, clinical decision support, and performing nursing notes. The project involves evaluation and implementation of EHR. The electronic health record and clinical decision support are not only relevant to my current organization but also are particular interest of mine. The electronic health record has helped to reduce the amount of paper which was a nightmare to maintain with the number of new patients being admitted daily. The electronic health record has also reduced the amount of missed documentation and errors. Any clinician can testify to the wasted time and poor communication among providers that sometimes results because antiquated paper records still predominate in our offices and on the hospital wards (Shortliffe, E. H., Tang, P. C., & Deimer, D. E., 1991). The clinical decision support system has been a great assistance to clinicians. Nurses, health visitors and midwives, as the largest group of healthcare professionals, record and generate most of the information used to maintain and improve patient care (Levy, S., & Heyes, B., 2012). Clinical support systems (CDSS) integrate information (ideally from high-quality research studies) with the

The Clinical Decision Support Systems have challenges to overcome such as information technology must be design a effective system which notify certain outlier medical information data input. This requires a very through collaboration between the Information Technology Department and the medical facility. Once the specified notifications are designed the medical facility will perform a test run to confirm accuracies and promptness of the required notifications. The next challenge with Clinical Decision

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

Health Informatics created two main categories such as clinical and administrative information systems to meet the needs of one or more department within the health care organization. For the clinical information system, it is set to meet the needs in improving patient care. Therefore, the clinical information system (CIS) categories provide nurses information systems (NIS) that support the way nurses documents the care that given to the patients. However, to improve the delivery of nursing care, the healthcare organization must adopt a computer system that can successfully incorporate tools that will benefit nursing. There is two vendors’ software that implies these characteristics for the

There are a lot of problems and challenges involved in implementing a clinical decision support system. It is important for medical staff (doctors, administrators etc.) to be an integral part in the implementation and development of CDSS. Our limited research concluded that acceptance of such technology is not easy amongst physicians. One of the main reasons for non acceptance is that the physicians want to be a standalone entity. We plan to investigate many challenges such as lack of technical expertise, cost, integration, misdiagnosis, speed etc involved in implementation of different types of CDSS in the health care industry today. Our research paper will focus on the different decision problems involved in these challenges.

Technology can assist healthcare workers on every clinical and administrative level to use information more effectively in clinical decision-making for patients, and in implementing strategic goals within an organization.