Iatrogenic injuries are common among hospitalized patients and are frequently preventable. The Institute of Medicine (IOM) reported that an estimated 44,000 to 98,000 peo [...]

Building on previously developed ontology for clinical orders, this work undertakes to answer questions about the usefulness of continued ontology development. Three ques [...]

Medication errors affect millions of patients each year. These errors contribute to significant harm, including adverse events, increased costs of care, and even deaths. [...]

The goal of this project is to specify and develop an algorithm that will check for drug and problem list mismatches in an electronic medical record. The algorithm is bas [...]

Chemotherapy, the prescription and administration of drugs to cancer patients, has traditionally been prescribed according to standard protocols through paper-based syste [...]

Healthcare professionals aim to provide the best care possible, but in the worst situations, the healthcare provided sometimes causes harm to patients. In 1999, the Insti [...]

This work is the first step towards developing an ontology of intensive care unit orders. A data set comprised of 625 ICU orders from 34 randomly selected patients of sev [...]

Medication errors and adverse drug events ADE are a constant challenge for healthcare providers. The fast-paced and unpredictable setting of an emergency department is es [...]

An expanding elderly population worldwide, with associated needs for medication and adherence assistance, requires an improved understanding of elders’ general medication [...]

Order sets are collections of orders that can be entered into a patient's chart in a single step. Order sets can improve the physician's efficiency and satisfaction with [...]