Healthcare Analytics
Expert-defined terms from the Advanced Skill Certificate in AI for Healthcare Leaders course at London School of Planning and Management. Free to read, free to share, paired with a professional course.
A/B Testing refers to a method of comparing two versions of a product, service,… #
Related terms include randomized controlled trials and statistical analysis. For example, a hospital might use A/B testing to compare the effectiveness of two different medication regimens on patient recovery rates.
Accountable Care Organization (ACO) is a network of healthcare providers… #
Related terms include population health management and care coordination. For instance, an ACO might use data analytics to identify high-risk patients and develop targeted interventions to improve their health outcomes.
Actuarial Science is the study of statistical models and technique… #
Related terms include predictive modeling and data analysis. For example, an actuary might use statistical models to predict the likelihood of patient readmissions and develop strategies to reduce costs and improve outcomes.
Adverse Event is an unintended or harmful occurrence that happens… #
Related terms include patient safety and quality improvement. For instance, a hospital might use data analytics to identify patterns of adverse events and develop strategies to prevent them.
Algorithm is a set of instructions or rules used to solve a pro… #
Related terms include artificial intelligence and deep learning. For example, a healthcare organization might use an algorithm to predict patient readmissions and develop targeted interventions to prevent them.
Artificial Intelligence (AI) refers to the use of computer systems… #
Related terms include machine learning and deep learning. For instance, a healthcare organization might use AI to analyze medical images and diagnose diseases more accurately.
Big Data refers to the large amounts of data that are generated by… #
Related terms include data analytics and informatics. For example, a hospital might use big data to identify patterns of disease progression and develop more effective treatment strategies.
Biostatistics is the application of statistical methods to analyze… #
Related terms include epidemiology and data analysis. For instance, a biostatistician might use statistical models to analyze the effectiveness of a new treatment and identify potential side effects.
Business Intelligence (BI) refers to the process of using data ana… #
Related terms include data visualization and reporting. For example, a hospital might use BI to analyze patient satisfaction data and identify areas for improvement.
Case Management is the process of coordinating care for patients w… #
Related terms include care coordination and patient advocacy. For instance, a case manager might use data analytics to identify high-risk patients and develop targeted interventions to improve their health outcomes.
Clinical Decision Support (CDS) refers to the use of computer syst… #
Related terms include Electronic Health Records (EHRs) and clinical guidelines. For example, a CDS system might use data analytics to identify patients at risk of adverse events and provide alerts to clinicians.
Clinical Informatics is the application of information technology… #
Related terms include health information technology and medical informatics. For instance, a clinical informaticist might use data analytics to evaluate the effectiveness of a new EHR system and identify areas for improvement.
Cloud Computing refers to the use of remote servers and interne… #
Related terms include data storage and cybersecurity. For example, a hospital might use cloud computing to store and analyze large amounts of medical imaging data.
Computer Vision is the use of computer systems to interpret and an… #
For instance, a computer vision system might use data analytics to detect tumors in medical images and provide diagnostic recommendations to clinicians.
Data Analytics refers to the process of using statistical and c… #
Related terms include business intelligence and informatics. For example, a hospital might use data analytics to analyze patient outcomes and identify areas for improvement.
Data Mining is the process of using computer systems to discover <… #
Related terms include machine learning and predictive analytics. For instance, a data mining system might use data analytics to identify patients at risk of readmission and provide interventions to prevent them.
Data Science is the field of study that combines statistics , co… #
Related terms include data analytics and machine learning. For example, a data scientist might use data analytics to develop predictive models of patient outcomes and identify areas for improvement.
Data Visualization is the process of using graphics and charts<… #
Related terms include business intelligence and reporting. For instance, a data visualization system might use data analytics to create dashboards and reports that help clinicians and administrators understand patient outcomes and identify areas for improvement.
Deep Learning is a type of machine learning that uses neural</b… #
Related terms include artificial intelligence and computer vision. For example, a deep learning system might use data analytics to detect tumors in medical images and provide diagnostic recommendations to clinicians.
Electronic Health Record (EHR) is a digital version of a patient's med… #
Related terms include clinical decision support and health information technology. For instance, an EHR system might use data analytics to identify patients at risk of adverse events and provide alerts to clinicians.
Epidemiology is the study of the distribution and determinants<… #
Related terms include biostatistics and data analysis. For example, an epidemiologist might use data analytics to analyze the spread of a disease and identify areas for intervention.
Health Information Exchange (HIE) is the process of sharing health … #
Related terms include Electronic Health Records (EHRs) and interoperability. For instance, an HIE system might use data analytics to identify patients with complex needs and provide care coordination services.
Health Informatics is the field of study that combines health scie… #
Related terms include clinical informatics and medical informatics. For example, a health informaticist might use data analytics to evaluate the effectiveness of a new EHR system and identify areas for improvement.
Health Insurance Portability and Accountability Act (HIPAA) is a law that… #
Related terms include data protection and compliance. For instance, a healthcare organization might use data analytics to identify vulnerabilities in their HIPAA compliance and develop strategies to mitigate risk.
Health IT is the application of information technology to improve… #
For example, a health IT system might use data analytics to evaluate the effectiveness of a new EHR system and identify areas for improvement.
Interoperability is the ability of health information systems to <… #
Related terms include Health Information Exchange (HIE) and Electronic Health Records (EHRs). For instance, an interoperable system might use data analytics to identify patients with complex needs and provide care coordination services.
Machine Learning is a type of artificial intelligence that uses <b… #
Related terms include deep learning and computer vision. For example, a machine learning system might use data analytics to detect tumors in medical images and provide diagnostic recommendations to clinicians.
Medical Imaging is the use of imaging technologies, such as X #
rays and MRIs, to diagnose and treat medical conditions, often used in healthcare to improve diagnostics and treatment planning. Related terms include computer vision and image analysis. For instance, a medical imaging system might use data analytics to detect tumors in medical images and provide diagnostic recommendations to clinicians.
Natural Language Processing (NLP) is the use of computer systems t… #
Related terms include text analysis and sentiment analysis. For example, an NLP system might use data analytics to analyze patient feedback and identify areas for improvement in care quality.
Operational Analytics is the use of data analytics to improve o… #
Related terms include business intelligence and performance improvement. For instance, an operational analytics system might use data analytics to identify bottlenecks in patient flow and develop strategies to improve efficiency.
Patient Engagement is the process of empowering patients to take a… #
Related terms include patient-centered care and shared decision-making. For example, a patient engagement system might use data analytics to identify patients with complex needs and provide care coordination services.
Patient Safety is the process of identifying and mitigating … #
Related terms include quality improvement and risk management. For instance, a patient safety system might use data analytics to identify patients at risk of falls and provide interventions to prevent them.
Predictive Analytics is the use of statistical and machine … #
Related terms include data mining and forecasting. For example, a predictive analytics system might use data analytics to predict patient readmissions and provide interventions to prevent them.
Quality Improvement is the process of identifying and addressin… #
Related terms include patient safety and performance improvement. For instance, a quality improvement system might use data analytics to identify areas for improvement in care quality and develop strategies to address them.
Risk Management is the process of identifying and mitigating</b… #
Related terms include patient safety and quality improvement. For example, a risk management system might use data analytics to identify patients at risk of adverse events and provide interventions to prevent them.
Telehealth is the use of telecommunications and information … #
Related terms include telemedicine and remote monitoring. For instance, a telehealth system might use data analytics to identify patients with complex needs and provide care coordination services.
Value #
Based Care is a payment model that rewards healthcare providers for delivering high-quality, cost-effective care, often used in healthcare to improve patient outcomes and reduce costs. Related terms include Accountable Care Organizations (ACOs) and population health management. For example, a value-based care system might use data analytics to identify patients with complex needs and provide care coordination services to improve their health outcomes.