Information Systems in Healthcare
Expert-defined terms from the Postgraduate Certificate in Health Informatics course at London School of Planning and Management. Free to read, free to share, paired with a professional course.
Clinical Decision Support System (CDSS) #
A system that provides healthcare professionals with clinical knowledge and patient information to assist in making clinical decisions. Related terms include expert systems, artificial intelligence, and knowledge management. A CDSS can improve patient care by reducing errors, increasing efficiency, and ensuring evidence-based practice. However, challenges include integrating with existing systems, ensuring data quality, and avoiding alert fatigue.
Electronic Health Record (EHR) #
A digital version of a patient's paper chart that contains all of their medical history from multiple providers. Related terms include personal health record and interoperability. An EHR can improve care coordination, reduce errors, and provide better population health management. However, challenges include data privacy and security, clinician burden, and implementation costs.
Health Information Exchange (HIE) #
The electronic movement of health-related information among organizations according to nationally recognized standards. Related terms include interoperability and data exchange. HIE can improve care coordination, reduce costs, and provide better population health management. However, challenges include data privacy and security, business and technical challenges, and lack of standardization.
Health Information Technology (HIT) #
The application of information processing involving both computer hardware and software that deals with the storage, retrieval, sharing, and use of health care information, data, and knowledge for communication and decision making. Related terms include healthcare informatics and clinical informatics. HIT can improve patient care, reduce costs, and increase efficiency. However, challenges include implementation costs, clinician burden, and data privacy and security.
Healthcare Informatics #
The scientific field that deals with the management and communication of data, information, and knowledge in health and biomedicine. Related terms include health information technology and clinical informatics. Healthcare informatics can improve patient care, reduce costs, and increase efficiency. However, challenges include data privacy and security, lack of standardization, and clinician burden.
Interoperability #
The ability of different information systems, devices, and applications to access, exchange, interpret, and cooperatively use data in a coordinated manner, within and across organizational boundaries. Related terms include health information exchange and data exchange. Interoperability can improve care coordination, reduce costs, and provide better population health management. However, challenges include lack of standardization, business and technical challenges, and data privacy and security.
Machine Learning (ML) #
A method of data analysis that automates the building of analytical models. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns, and make decisions with minimal human intervention. Related terms include deep learning and neural networks. ML can be used in healthcare for predictive analytics, image analysis, and natural language processing. However, challenges include data privacy and security, lack of transparency, and bias.
Personal Health Record (PHR) #
An electronic application through which individuals can access, manage, and share their health information, and that of others for whom they are authorized, in a private, secure, and consumer-friendly manner. Related terms include electronic health record and patient portal. A PHR can improve patient engagement, empowerment, and self-management. However, challenges include data privacy and security, patient burden, and integration with EHRs.
Predictive Analytics #
The use of statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. Related terms include machine learning and artificial intelligence. Predictive analytics can be used in healthcare for patient stratification, risk assessment, and care management. However, challenges include data privacy and security, bias, and lack of transparency.
Telehealth #
The use of electronic information and telecommunications technologies to support long-distance clinical health care, patient and professional health-related education, public health and health administration. Related terms include telemedicine and remote monitoring. Telehealth can improve access, quality, and efficiency of care. However, challenges include licensing and reimbursement, technical issues, and patient and clinician acceptance.
Terminology Standards #
A set of agreed-upon definitions, concepts, and relationships used to represent and exchange health information. Related terms include interoperability and data exchange. Terminology standards can improve data quality, consistency, and comparability. However, challenges include lack of standardization, complexity, and implementation costs.
Usability #
The extent to which a product can be used by specified users to achieve specified goals with effectiveness, efficiency, and satisfaction in a specified context of use. Related terms include human-computer interaction and user experience. Usability is important in healthcare to ensure that health IT is safe, effective, and user-friendly. However, challenges include lack of user involvement, complexity, and changing user needs.
Vendor Neutral Archive (VNA) #
A system for storing, managing, and sharing medical images and other multimedia objects, independent of the vendor or device that created them. Related terms include picture archiving and communication system and interoperability. A VNA can improve data sharing, reduce costs, and ensure long-term access to medical images. However, challenges include data migration, integration with existing systems, and vendor support.
Workflow #
The sequence of operations, tasks, and events that make up a work process. Related terms include process improvement and clinical pathway. Workflow is important in healthcare to ensure efficient, effective, and safe care delivery. However, challenges include variability, complexity, and clinician burden.
eHealth #
The use of information and communication technologies (ICT) for health. Related terms include mHealth, telehealth, and health information technology. eHealth can improve access, quality, and efficiency of care. However, challenges include data privacy and security, lack of standardization, and unequal access.
mHealth #
The use of mobile devices and applications for health. Related terms include telehealth, wearables, and sensors. mHealth can improve patient engagement, empowerment, and self-management. However, challenges include data privacy and security, lack of evidence, and usability.
Artificial Intelligence (AI) #
A branch of computer science that deals with the simulation of intelligent behavior in computers. Related terms include machine learning, deep learning, and neural networks. AI can be used in healthcare for predictive analytics, image analysis, and natural language processing. However, challenges include data privacy and security, bias, and lack of transparency.
Big Data #
Large and complex data sets that cannot be managed or analyzed using traditional methods or tools. Related terms include data analytics, machine learning, and visualization. Big data can be used in healthcare for population health management, research, and quality improvement. However, challenges include data privacy and security, data quality, and technical issues.
Clinical Informatics #
The application of informatics and information technology to deliver healthcare services. Related terms include healthcare informatics, clinical decision support system, and terminology standards. Clinical informatics can improve patient care, reduce costs, and increase efficiency. However, challenges include data privacy and security, lack of standardization, and clinician burden.
Cybersecurity #
The practice of protecting electronic information from unauthorized access, use, disclosure, disruption, modification, or destruction. Related terms include data privacy, encryption, and firewalls. Cybersecurity is important in healthcare to ensure the confidentiality, integrity, and availability of health information. However, challenges include evolving threats, lack of awareness, and insufficient resources.
Data Analytics #
The process of examining data to extract insights, trends, and patterns. Related terms include big data, machine learning, and