At its core, clinical informatics, also known as applied clinical informatics, centers on providing better patient care using technology. Clinical informaticists evaluate the efficacy and operation of clinicalinformation systems, how the information is used and how to best improve the quality of care ...
Introduction of a nontrivial clinical information system (CIS) generates major cultural challenges.1 The most obvious relate to the need for health care workers to acquire new skills and do their work in new ways. More subtle challenges relate to alteration of roles and workflow throughout an ...
A clinical decision support system (CDSS) is an application that analyzes data to help healthcare providers make decisions and improve patient care. It is a variation of the decision support system (DSS) commonly used to support business management. Different kinds of decision support systems can ...
National clinical portal programme: What information do doctors want? Electronic patient health information in secondary care is often stored on different IT systems and not accessible to doctors involved in clinical decision... K Strachan,C Kelly - 《Scottish Medical Journal》 被引量: 1发表: 2011...
A laboratory information management systems (LIMS) is a software solution that manages lab data, reagents, test results, workflows and teams and increase lab operational efficiency, productivity and effectiveness in delivering high-quality results. The definition of a LIMS may vary depending on the so...
Clinical decision support systems are designed to improve health and healthcare delivery by enhancing health-related decisions and actions. CDS does this by providing clinicians, staff, or patients with clinical knowledge and patient-specific information, which is intelligently filtered or presented at co...
protected health information (PHI) data from disparate systems into a managed service based on Fast Health Interoperability Resources (FHIR) helps create a longitudinal record of the patient. This data is then able to fuel improved patient care, clinical insights, data analytics, machine learning, ...
It contributes to the advancement of our knowledge in various fields and has implications for both research and clinical settings. As DVC is becoming more popular, datasets are getting larger and require an increasing computational demand. We’ve added to this version a multidomain approach and ...
The systems aim to analyze information that is unique for the patient. They cross-reference that information with clinical guidelines and the available research to provide patient-tailored recommendations to the physicians. CDSSs tend to be extremely useful as they can guide anyone toward good clinica...
Implementing guidelines into clinical practice: what is the value? Rationale and objective In budget-constrained health systems, decision makers need to consider both the costs and effects of introducing and actively i... T Hoomans,AJHA Ament,SMAA Evers,... - 《Journal of Evaluation in Clin...