Artificial intelligence related safety issues associated with FDA medical device reports.

The Biden 2023 Artificial Intelligence (AI) Executive Order calls for the creation of a patient safety program. Patient safety reports are a natural starting point for identifying issues. We examined the feasibility of this approach by analyzing reports associated with AI/Machine Learning (ML)-enabled medical devices.

Race Differences in a Malpractice Event Database in a Large Healthcare System.

Objectives: This study aimed to determine whether potential malpractice events reported by employees, malpractice events involving claims, and malpractice lawsuits differ based on patient race in a large 10-hospital healthcare system.

Methods: Data in a healthcare system's malpractice database from July 1, 2012, to June 30, 2017, were stratified by patient race using "Black," "White," and "other" categories. χ2 Goodness-of-fit tests were used to compare differences in race proportions in employee-reported observations of events that could lead to payment of a claim, claims not involving the court, and lawsuits involving the court.

Development and pilot evaluation of an electronic health record usability and safety self-assessment tool.

Objective: Poor electronic health record (EHR) usability contributes to clinician burnout and poses patent safety risks. Site-specific customization and configuration of EHRs require individual EHR system usability and safety testing which is resource intensive. We developed and pilot-tested a self-administered EHR usability and safety assessment tool, focused on computerized provider order entry (CPOE), which can be used by any facility to identify specific issues.

Usability and Accessibility of Publicly Available Patient Safety Databases.

Objectives: The aims of the study were to identify publicly available patient safety report databases and to determine whether these databases support safety analyst and data scientist use to identify patterns and trends.

Methods: An Internet search was conducted to identify publicly available patient safety databases that contained patient safety reports. Each database was analyzed to identify features that enable patient safety analyst and data scientist use of these databases.

Race Differences in Reported "Near Miss" Patient Safety Events in Health Care System High Reliability Organizations.

Objectives: This study aimed to determine if race differences exist in voluntarily reported near-miss patient safety events in a large integrated, 10-hospital health care system on its journey to become a high reliability organization.

Methods: From July 1, 2015, to June 30, 2017, employees in a mid-Atlantic health care system voluntarily reported near-miss events by type using an occurrence reporting system referred to as the Patient Safety Event Management System. Inpatients, outpatients, and observation patients were identified as "Black," "White," or "other" (n = 39,390).

Pilot assessment of an on-demand telehealth 'left without being seen' follow-up programme.

Introduction: On-demand telehealth can have a high rate of patients requesting visits and dropping off without being seen by a provider, especially during the COVID-19 pandemic.

Methods: On-demand telehealth requests made to a large healthcare system in the USA between 15 March 2020 and 31 May 2020 were included for analysis with a focus on patients who were defined as left without being seen (LWBS). As part of a pilot program a registered nurse attempted to call LWBS patients within 24 hours of their telehealth request and asked if they were ok, if they sought care for their original visit reason, what that care was, or if they still needed guidance.

The Impact of COVID-19 on Medical Device Reporting and Investigation.

Introduction: The Manufacturer and User Facility Device Experience (MAUDE) database houses medical device reports submitted to the U.S. Food and Drug Administration (FDA).

Lessons Learned from a Systems Approach to Engaging Patients and Families in Patient Safety Transformation.

Background: Effective patient- and family-centered care requires a dedication to engaging patients and family members in health system redesign to improve the quality, safety, and experience of care. Provided here are lessons learned six years after establishing an infrastructure of patient and family advisory councils (PFACs) focused on improving health care quality and safety.

Context: A large regional health care system with multiple hospitals and ambulatory care delivery sites in the eastern United States adopted a systemwide approach to Patient and Family Advisory Councils on Quality and Safety (PFACQS) in 2012.

Qualitative findings from a pilot stage implementation of a novel organizational learning tool toward operationalizing the Safety-II paradigm in health care.

'Safety-II' is a new approach to safety, which emphasizes learning proactively about how safety and efficacy are achieved in everyday frontline work. Previous research developed a new lesson-sharing tool designed based on the Safety-II approach: Resilience Engineering Tool to Improve Patient Safety (RETIPS). The tool comprises questions designed to elicit narratives of adaptations that have contributed to effectiveness in care delivery.

Race Differences in Reported Harmful Patient Safety Events in Healthcare System High Reliability Organizations.

Objectives: The aim of the study was to determine whether race differences exist in voluntarily reported harmful patient safety events in a large 10 hospital healthcare system on a high reliability organization journey.

Methods: From July 1, 2015, to June 30, 2017, employees in a healthcare system based in Washington, District of Columbia, and Maryland voluntarily reported harmful patient safety events by type using a Patient Safety Event Management System. Inpatients, outpatients, and observation patients were identified as "black," "white," or "other" (N = 5038).