Working Group Webinar Library
Webinar Library
Six Machine-Learning Methods for Predicting Hospital-Stay Durations for Patients with Sepsis: A Comparative Study
Sepsis is a life-threatening medical condition that, if not treated promptly, can result in tissue damage, organ failure, and death. According to the Centers for Disease Control, about 270,000 individuals die of sepsis in the United States each year. Further, sepsis expenditures accounted for 13% of total US hospital costs in 2013, totaling more than $24 billion.
TriNetX Journey: Challenges in Building a sustainable global data and analytics platform for clinical trials and research
We look back at the decade of effort to build, operate and grow the TriNetX strategic platform found in research informatics portfolios of many healthcare organizations and academic medical centers world-wide.
Development of a Natural Language Processing System for Extracting Rheumatoid Arthritis Outcomes From Clinical Notes Using the National Rheumatology Informatics System for Effectiveness Registry
Patient reported outcomes (PROs) include any report of the status of a patient's health condition that comes directly from the patient, without interpretation of the patient's response by a clinician or anyone else. PROs for functional status information describes the patient's physical and mental wellness at the whole-person level (as opposed to the cellular or organ level).
Improving Acute Kidney Injury Prediction and Risk Factor Analysis with Personalized Transfer Learning
Acute kidney injury (AKI) is a life-threatening clinical syndrome prevalent in hospitalized patients (10% to 15% affected), especially among critically ill patients (>50% affected), and has exceeded the annual incidence of myocardial infarction. AKI patients are at much higher risk for developing poor long-term outcomes including incident and progressive chronic kidney disease, cardiovascular disease, and death.
Leveraging Procedural Video Data for Quality, Safety, and Knowledge
High-dimensional data from procedural recordings are increasingly being leveraged by institutions for quality, safety, and efficiency. With advances in technology enabling high fidelity recordings and large scale analytics, the possible applications for this data continue to expand. Institutions must consider their data strategy and the ethical, legal, privacy, and insurance implications of recording clinical procedures.