Polski merkuriusz lekarski : organ Polskiego Towarzystwa Lekarskiego
Jan 1, 2023
Artificial Intelligence (AI) has undeniably transformed the landscape of healthcare, offering unparalleled potential to enhance patient care, streamline diagnostics, and improve overall healthcare outcomes. As AI continues to make its way into the me...
Journal of the American College of Surgeons
May 1, 2022
The robotic platform offers many benefits to patients and surgeons; however, incorporating this new surgical tool has also introduced challenges in intraoperative documentation accuracy. In 2019, we began to investigate our institution's robotic intr...
OBJECTIVE: We describe our approach to surveillance of reportable safety events captured in hospital data including free-text clinical notes. We hypothesize that a) some patient safety events are documented only in the clinical notes and not in any o...
Patient safety event (PSE) reports are a useful lens to understand hazards and patient safety risks in healthcare systems. However, patient safety officers and analysts in healthcare systems and safety organizations are challenged to make sense of th...
BACKGROUND AND OBJECTIVES: Medical errors are a leading cause of death in the United States. Despite widespread adoption of patient safety reporting systems to address medical errors, making sense of the reports collected in these systems is challeng...
British journal of nursing (Mark Allen Publishing)
Jul 22, 2021
, Lecturer in Law, Birmingham Law School, University of Birmingham, discusses some recent reports on artificial intelligence (AI) and machine learning in the context of law, ethics and patient safety.
OBJECTIVES: Patient feedback is critical to identify and resolve patient safety and experience issues in healthcare systems. However, large volumes of unstructured text data can pose problems for manual (human) analysis. This study reports the result...
Journal of the American Medical Informatics Association : JAMIA
Dec 9, 2020
Accumulating evidence demonstrates the impact of bias that reflects social inequality on the performance of machine learning (ML) models in health care. Given their intended placement within healthcare decision making more broadly, ML tools require a...
Journal of the American Medical Informatics Association : JAMIA
Nov 1, 2020
OBJECTIVE: To improve patient safety and clinical outcomes by reducing the risk of prescribing errors, we tested the accuracy of a hybrid clinical decision support system in prioritizing prescription checks.