Clinical Decision Support For Best Practice

Health informatics consists of many components, the main components focused on are electronic medical records, clinical decision support systems, and telemedicine. The electronic medical record (EMR) is a medical record in digital format. EMR's facilitate access of patient data by clinical staff at any given location, accurate and complete claims processing by insurance companies, building automated checks for drug and allergy interactions, clinical notes, prescriptions, scheduling, and sending /viewing of labs. Research has shown that electronic health records provide greater accessibility, accuracy, and completeness of clinical information: therefore reducing uncertainty[2]. Clinical decisions support systems are computerized systems designed to assist physicians and other health professionals in decision making. Telemedicine is the use of information technology and communication to deliver care. Telemedicine uses electronic information and communications technologies to provide medical diagnosis and/or patient health care when distance separates the participants.

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.

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).

The task support field has been revolutionized through the implementation of the electronic medical record in conjunction with EPIC. The universalization of the electronic medical record will increase the accessibility of patient information to clinicians as well as increase the amount of data available for clinical use, reducing medical error significantly. However, the greatest tool to increase the standardization of care, reduction of practice pattern variation, successful and effective diagnosis, and correct care path choice will result from the development of Information system facilitating true interdisciplinary care. Clinical Information specialists offer the possibility to improve the quality and reduce the cost of care by influencing medical decisions at the time and place that these decisions are made. Our clinical Nurse Information specialist would alert physicians and Nurses when outlier results are returned from data entry of laboratory testing. The data attained for a specific patient can then be compared to the general population to indicate whether the data is within the normal fit or is an outlier that may require further analysis. Such a practice would induce the physician and Nurses to notice certain data that may otherwise go unnoticed, and therefore, alter the diagnosis of the patient. A physician may enter a possible diagnosis into the system and then receive feedback from

Develop a Clinical Alert Management Committee to facilitate management of alerts. Include key stakeholders and contributors from clinical, technical, and information technology with interest and experience in medication alert management. Team members include:

Electronic Health Reports allow a consistent message to be delivered to every team member involved in the patient’s care plan. The

CDI programs increase patient safety and care by “recognizing the most frequent kind of documentation errors and putting procedures in place to stop them before they strike (Butler).” Examples of such documentation disasters, as Butler puts it, is over use of the copy and paste function in the EHR and missing or incomplete documentation. Copy and paste can lead to important details of patient care or progress being omitted, while incomplete documentation can affect everything from adverse medication interactions to a misdiagnosis. CDI programs address issues such as these with focused training programs, the implementation of policies and procedures, and the use of software to prompt physician queries.

CDSS can reduce errors related to prescribing; however, poor acceptance has been a significant barrier. In many settings, ignoring alerts of a CDSS is the norm rather than the exception due to a lack of clinical specificity and is referred to as alarm fatigue. Alert burden can be countered by refining knowledge bases to increase tailored feedback. HCO's should evaluate both the intended and unintentional consequences, which include interfering with clinical workflow and intellectual burden. Furthermore, competing elements of clinical decision support tools should be addressed. We must minimize the barriers of CDS to providers while promoting healthcare technology innovation and improving healthcare quality. Another concern of providers is keeping up with pace for new evidence and guidelines while allowing clinicians also to use their clinical judgment within their scope of care (Seidling et al., 2014).

I agree with you that the rush to meet compliance created haphazard and fragmented clinical decision support (CDS) tools throughout the health care industry. I also agree that workflows in health care can be complex; so what is the solution for usable and effective CDS tools? First and foremost an organization needs to have a clear picture of what the need is that will be supported by the implementation of CDS tools. Not all tools are relevant to all areas of health care.

There is opportunity to improve the quality of health care in Jones Hospital. Information technology (IT) offers the potential to address the organization’s most pressing dilemmas: care fragmentation, medical errors, and rising costs. The leading example of this is the electronic health record (EHR). An EHR, as explained by HealthIT.gov (n.d.), is a digital version of a patient’s paper chart. It includes, but is not limited to, medical history, diagnoses, medications, and treatment plans. The EHR, then, serves as a resource that will aid Jones Hospital clinicians in decision-making by providing comprehensive patient information.

Despite their potential to significantly improve health care, advanced clinical decision support (CDS) capabilities are not widely available in the clinical setting. An important reason for this limited availability of CDS capabilities is the application-specific and institution-specific nature of most current CDS implementations. There is a critical need to enable CDS capabilities on a much larger scale is the development and adoption of standards that enable current and emerging CDS resources to be more effectively leveraged across multiple applications and care settings. Standards required for such effective scaling of CDS include (i) standard terminologies and information models to represent and communicate about health care data; (ii) standard approaches to representing clinical knowledge in both human-readable and machine-executable formats; and (iii) standard approaches for

Everything from paying bills, to shopping, to connecting with friends and family has been forever changed by advances in technology. It seems like everyday someone has found a faster, more efficient, less costly way of doing something. Technology has impacted virtually every person and every industry in the world and healthcare is no exception. From minimally invasive procedures, to magnetic renaissance imaging, to the perpetual Electronic Health Record (EHR), technological advances have changed the way healthcare is accessed, delivered, and reimbursed. The implementation of the outpatient EHR however, is the most significant healthcare innovation I experienced in my career.

Sophisticated electronic records and computer systems for tracking patient care is another important attribute of Kaiser. Since five years, Kaiser is using the electronic information to identify and evaluate providers’ strengths and weaknesses in order to improve the quality of care (Abelson, 2013). The organization also uses the electronic records to improve its care delivery, e.g. by identifying at-risk patients and establishing alert and reminder systems for quick and timely care

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