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.

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.

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,

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).

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

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.

In the United State, hospitals, less than two-thirds of hospitals have any type of CDS. (Byrne et al., n.d.). We might be wondering why the use of CDC is low among health care provider, based on my study the following are some of the barriers in implantation of CDS: Usability issues (Byrne et al., n.d.). This include rate of the process of information, user what the information that he or she wanted as fasted rate as possible, it graphical User Interface is not as friendly as it should be. Secondary ,the CDS Alarms functionality include lists of possible diagnoses, drug interaction alerts, or preventive care reminders and the overused of theses alarm may lead to the clinician not paying too much attention to them as it would be seen as normal sound (Bolch, 2012).These are some of the way, in which these barrier can be remove, need for better user friendly design , if the interface is well design and easy to use more physician who like to use it in making clinical decision, There is needs for the vendor and researcher to address this design failure ("Clinical Decision Support (CDS) Initiative | AHRQ National Resource Center; Health Information Technology: Best Practices Transforming Quality, Safety, and Efficiency," 2014). It is imperative to customize CDS after it is implemented failure to do this can lead to failure. For example, disabling some of the alarm system that is redundant or lack practical value, and constantly training of clinician to ensure important reminder do receive necessary attention (Bolch,

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].

30). According to Brunstein (2016), individual tests can be moved to a patient’s bedside or in other less formal settings to provide faster diagnosis, allowing for quicker response times when medical interventions are needed (p. 30). Bedside testing uses a method called point-of-care testing (POCT) and presents both new possibilities as well as challenges (Brunstein, 2016, p. 30). Brunstein (2016) points out some of the challenges are decreased sensitivity, specificity, or sometimes both, especially when compared to the testing that is done in the core lab (p.30). However, POCT can prove to be advantageous because of reduced response times for medical interventions. POCT with moderate sensitivity and high specificity have proven to be convenient, cost effective first-line screening tools (Brunstein, 2016, p. 30). Molecular POCT has positive implications for the future but there are some limitations. POCT used for molecular diagnosis (Madix) are limited to only

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

Even though conventional laboratory testing is traditionally utilized in the nations ED’s, each additional test ordered, contributes to an increased ED LOS of up to 17 minutes (Li et al., 2015). In comparison, POCT results were

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

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.