AI Medical Compendium Journal:
Journal of patient safety

Showing 11 to 14 of 14 articles

Applying Intelligent Algorithms to Automate the Identification of Error Factors.

Journal of patient safety
OBJECTIVES: Medical errors are the manifestation of the defects occurring in medical processes. Extracting and identifying defects as medical error factors from these processes are an effective approach to prevent medical errors. However, it is a dif...

Assessment of Automating Safety Surveillance From Electronic Health Records: Analysis for the Quality and Safety Review System.

Journal of patient safety
BACKGROUND AND OBJECTIVES: In an effort to improve and standardize the collection of adverse event data, the Agency for Healthcare Research and Quality is developing and testing a patient safety surveillance system called the Quality and Safety Revie...

Using Natural Language Processing to Extract Abnormal Results From Cancer Screening Reports.

Journal of patient safety
OBJECTIVES: Numerous studies show that follow-up of abnormal cancer screening results, such as mammography and Papanicolaou (Pap) smears, is frequently not performed in a timely manner. A contributing factor is that abnormal results may go unrecogniz...

Screening Electronic Health Record-Related Patient Safety Reports Using Machine Learning.

Journal of patient safety
INTRODUCTION: The objective of this study was to develop a semiautomated approach to screening cases that describe hazards associated with the electronic health record (EHR) from a mandatory, population-based patient safety reporting system.