Feature Engineering and Process Mining to Enable Hazard Detection in Health Information Technology.

In this work, we aim to enhance the reliability of health information technology (HIT) systems by detection of plausible HIT hazards in clinical order transactions. In the absence of well-defined event logs in corporate data warehouses, our proposed approach identifies relevant timestamped data fields that could indicate transactions in the clinical order life cycle generating raw event sequences. Subsequently, we adopt state transitions of the OASIS Human Task standard to map the raw event sequences and simplify the complex process that clinical radiology orders go through.

Understanding barriers and facilitators to the use of Clinical Information Systems for intensive care units and Anesthesia Record Keeping: A rapid ethnography.

Objective: This study evaluated the current use of commercial-off-the-shelf Clinical Information Systems (CIS) for intensive care units (ICUs) and Anesthesia Record Keeping (ARK) for operating rooms and post-anesthesia care recovery settings at three Veterans Affairs Medical Centers (VAMCs). Clinicians and administrative staff use these applications at bedside workstations, in operating rooms, at nursing stations, in physician's rooms, and in other various settings. The intention of a CIS or an ARK system is to facilitate creation of electronic records of data, assessments, and procedures from multiple medical devices.

An analysis of electronic health record-related patient safety concerns.

Objective: A recent Institute of Medicine report called for attention to safety issues related to electronic health records (EHRs). We analyzed EHR-related safety concerns reported within a large, integrated healthcare system.

Methods: The Informatics Patient Safety Office of the Veterans Health Administration (VA) maintains a non-punitive, voluntary reporting system to collect and investigate EHR-related safety concerns (ie, adverse events, potential events, and near misses).