Does one size fit all? Developing an evaluation strategy to assess large language models for patient safety event report analysis.

Objective: Collecting and analyzing patient safety event (PSE) reports is a key component to the improvement of patient safety yet report analysis has been challenging. Large language models (LLMs) may support analysis; however, PSE reports tend to be a hybrid of clinical and general language.

Materials And Methods: We propose a data-driven evaluation strategy to assess LLM fit for report analysis.

The Maternal Voice: Exploration of Mothers and Birthing Individuals' Voices in Patient Safety Event and Feedback Reports.

Background: There is a growing body of research highlighting that Black women have more adverse maternal health events. Instead of only focusing on severe maternal morbidity and mortality events, patient safety events (PSEs) and feedback reports are data sources that can offer insights into a broader spectrum of maternal safety, including near misses, and unsafe conditions. In this work, we explore the racial differences in the representation of mothers and birthing individuals' (MBIs) voices in PSE and feedback reports.

Understanding Perceptions of Care Coordination and Chronic Illness Management among Black Breast and Prostate Cancer Survivors and Providers: Findings from a Quality Improvement Study.

Navigating cancer care is complex and is exacerbated by pre-existing comorbidities managed by multiple providers. In this quality improvement study, we evaluated changes in perceived care coordination, navigation, and chronic illness care with community health worker (CHW) and mHealth support among Black breast cancer and prostate cancer patients with hypertension and/or diabetes. We collected patient and provider surveys on chronic illness care coordination at baseline and six months and found improvements in multiple domains.

Accuracy of Noninvasive Blood Pressure Monitoring in Critically Ill Adults.

Blood pressure (BP) is routinely invasively monitored by an arterial catheter in the intensive care unit (ICU). However, the available data comparing the accuracy of noninvasive methods to arterial catheters for measuring BP in the ICU are limited by small numbers and diverse methodologies. To determine agreement between invasive arterial blood pressure monitoring (IABP) and noninvasive blood pressure (NIBP) in critically ill patients.

A text mining approach to categorize patient safety event reports by medication error type.

Patient safety reporting systems give healthcare provider staff the ability to report medication related safety events and errors; however, many of these reports go unanalyzed and safety hazards go undetected. The objective of this study is to examine whether natural language processing can be used to better categorize medication related patient safety event reports. 3,861 medication related patient safety event reports that were previously annotated using a consolidated medication error taxonomy were used to develop three models using the following algorithms: (1) logistic regression, (2) elastic net, and (3) XGBoost.

The impact of COVID-19 on primary care accessibility and the role of telehealth for patients with chronic conditions.

Objectives: The objective of this study is to quantify how long patients took to complete their rescheduled primary care appointment pre-pandemic (2019) and during an initial pandemic period (2020). In doing so, the study evaluates telehealth's role in helping primary care patients - particularly in patients with chronic conditions - withstand COVID's significant disruption in care.

Methods: Cancelled and completed primary care appointments for adult patients were extracted from the beginning of the pandemic (March 1 to July 31, 2020) and a similar period pre-pandemic (March 1 to July 31, 2019).

Electronic Health Record Use Issues and Diagnostic Error: A Scoping Review and Framework.

Background: Diagnostic errors are a major source of patient harm, most of which are caused by cognitive errors and biases. Despite research showing the relationship between software systems and cognitive processes, the impact of the electronic health record (EHR) on diagnostic error remains unknown.

Methods: We conducted a scoping review of the scientific literature to (1) survey the association between aspects of the EHR and diagnostic error, and (2) through a human-systems integration lens, identify the types of EHR issues and their impact on the stages of the diagnostic process.

Using Community Detection Techniques to Identify Themes in COVID-19-Related Patient Safety Event Reports.

Objectives: The COVID-19 pandemic has transformed how healthcare is delivered to patients. As the pandemic progresses and healthcare systems continue to adapt, it is important to understand how these changes in care have changed patient care. This study aims to use community detection techniques to identify and facilitate analysis of themes in patient safety event (PSE) reports to better understand COVID-19 pandemic's impact on patient safety.

Evaluation of a Text Message-Based COVID-19 Vaccine Outreach Program Among Older Patients: Cross-sectional Study.

Background: COVID-19 vaccines are vital tools in the defense against infection and serious disease due to SARS-CoV-2. There are many challenges to implementing mass vaccination campaigns for large, diverse populations from crafting vaccine promotion messages to reaching individuals in a timely and effective manner. During this unprecedented period, with COVID-19 mass vaccination campaigns essential for protecting vulnerable patient populations and attaining herd immunity, health care systems were faced with the dual challenges of vaccine outreach and distribution.

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).

Risky Business: Predicting patient mortality at a glance.

Clinicians are constantly forecasting patient trajectories to make critical point of care decisions intended to influence clinical outcomes. Little is known, however, about how providers interpret mortality risk against validated scoring systems. This research aims to understand how providers forecast mortality specifically for that of patients with sepsis.

Rapid development of visualization dashboards to enhance situation awareness of COVID-19 telehealth initiatives at a multihospital healthcare system.

The COVID-19 pandemic has led to the rapid expansion of telehealth services as healthcare organizations aim to mitigate community transmission while providing safe patient care. As technology adoption rapidly increases, operational telehealth teams must maintain awareness of critical information, such as patient volumes and wait times, patient and provider experience, and telehealth platform performance. Using a model of situation awareness as a conceptual foundation and a user-centered design approach we describe our process for rapidly developing and disseminating dashboard visualizations to support telehealth operations.