Impact of a Clinical Decision Support System on Computed Tomographic Pulmonary Angiogram Yield and Utilization in Hospitalized Patients.

Objective: To determine whether point-of-order clinical decision support (CDS) based on the Wells Criteria improves CT pulmonary angiogram (CTPA) yield and utilization in hospitalized patients in an enterprise-wide health system and identify yield-related factors.

Methods: This retrospective IRB-approved cross-sectional study in an urban, multi-institution health system included hospitalized patients undergoing CTPA 12 months before and after CDS implementation (entire cohort). Chi-square test was used to compare PE yield in patients in whom providers overrode vs.

Establishing responsible use of AI guidelines: a comprehensive case study for healthcare institutions.

This report presents a comprehensive case study for the responsible integration of artificial intelligence (AI) into healthcare settings. Recognizing the rapid advancement of AI technologies and their potential to transform healthcare delivery, we propose a set of guidelines emphasizing fairness, robustness, privacy, safety, transparency, explainability, accountability, and benefit. Through a multidisciplinary collaboration, we developed and operationalized these guidelines within a healthcare system, highlighting a case study on ambient documentation to demonstrate the practical application and challenges of implementing generative AI in clinical environments.

Risk stratification of potential drug interactions involving common over-the-counter medications and herbal supplements by a large language model.

Background: As polypharmacy, the use of over-the-counter (OTC) drugs, and herbal supplements becomes increasingly prevalent, the potential for adverse drug-drug interactions (DDIs) poses significant challenges to patient safety and health care outcomes.

Objective: This study evaluates the capacity of Generative Pre-trained Transformer (GPT) models to accurately assess DDIs involving prescription drugs (Rx) with OTC medications and herbal supplements.

Methods: Leveraging a popular subscription-based tool (Lexicomp), we compared the risk ratings assigned by these models to 43 Rx-OTC and 30 Rx-herbal supplement pairs.

The TRIPOD-LLM Statement: A Targeted Guideline For Reporting Large Language Models Use.

Unlabelled: Large Language Models (LLMs) are rapidly being adopted in healthcare, necessitating standardized reporting guidelines. We present TRIPOD-LLM, an extension of the TRIPOD+AI statement, addressing the unique challenges of LLMs in biomedical applications. TRIPOD-LLM provides a comprehensive checklist of 19 main items and 50 subitems, covering key aspects from title to discussion.

Implementation of a Web-Based Chatbot to Guide Hospital Employees in Returning to Work During the COVID-19 Pandemic: Development and Before-and-After Evaluation.

Background: Throughout the COVID-19 pandemic, multiple policies and guidelines were issued and updated for health care personnel (HCP) for COVID-19 testing and returning to work after reporting symptoms, exposures, or infection. The high frequency of changes and complexity of the policies made it difficult for HCP to understand when they needed testing and were eligible to return to work (RTW), which increased calls to Occupational Health Services (OHS), creating a need for other tools to guide HCP. Chatbots have been used as novel tools to facilitate immediate responses to patients' and employees' queries about COVID-19, assess symptoms, and guide individuals to appropriate care resources.

A Mobile Health Application Integrated in the Electronic Health Record for Rheumatoid Arthritis Patient-Reported Outcomes: A Controlled Interrupted Time-Series Analysis of Impact on Visit Efficiency.

Objective: Patient-reported outcome (PRO) collection between visits for rheumatoid arthritis (RA) could improve visit efficiency, reducing in-person visits for patients with stable symptoms while facilitating access for those with symptoms. We examined whether a mobile health PRO application integrated in the electronic health record (EHR) could reduce visit volume for those with RA.

Methods: We developed an application for RA that prompted patients every other day to complete brief PRO questionnaires.

Assessing the Utility of ChatGPT Throughout the Entire Clinical Workflow: Development and Usability Study.

Background: Large language model (LLM)-based artificial intelligence chatbots direct the power of large training data sets toward successive, related tasks as opposed to single-ask tasks, for which artificial intelligence already achieves impressive performance. The capacity of LLMs to assist in the full scope of iterative clinical reasoning via successive prompting, in effect acting as artificial physicians, has not yet been evaluated.

Objective: This study aimed to evaluate ChatGPT's capacity for ongoing clinical decision support via its performance on standardized clinical vignettes.

A Pilot of Digital Whiteboards for Improving Patient Satisfaction in the Emergency Department: Nonrandomized Controlled Trial.

Background: Electronic paper (E-paper) screens use electrophoretic ink to provide paper-like low-power displays with advanced networking capabilities that may potentially serve as an alternative to traditional whiteboards and television display screens in hospital settings. E-paper may be leveraged in the emergency department (ED) to facilitate communication. Providing ED patient status updates on E-paper screens could improve patient satisfaction and overall experience and provide more equitable access to their health information.

Assessing the Utility of ChatGPT Throughout the Entire Clinical Workflow.

Importance: Large language model (LLM) artificial intelligence (AI) chatbots direct the power of large training datasets towards successive, related tasks, as opposed to single-ask tasks, for which AI already achieves impressive performance. The capacity of LLMs to assist in the full scope of iterative clinical reasoning via successive prompting, in effect acting as virtual physicians, has not yet been evaluated.

Objective: To evaluate ChatGPT's capacity for ongoing clinical decision support via its performance on standardized clinical vignettes.

Acceptance of a computer vision facilitated protocol to measure adherence to face mask use: a single-site, observational cohort study among hospital staff.

Objectives: Mask adherence continues to be a critical public health measure to prevent transmission of aerosol pathogens, such as SARS-CoV-2. We aimed to develop and deploy a computer vision algorithm to provide real-time feedback of mask wearing among staff in a hospital.

Design: Single-site, observational cohort study.

Disparities in the Inclusion of Racial and Ethnic Minority Groups and Older Adults in Prostate Cancer Clinical Trials: A Meta-analysis.

Importance: Prostate cancer (PCa) is marked by disparities in clinical outcomes by race, ethnicity, and age. Equitable enrollment in clinical trials is fundamental to promoting health equity.

Objective: To evaluate disparities in the inclusion of racial and ethnic minority groups and older adults across PCa clinical trials.

Results of a Remotely Delivered Hypertension and Lipid Program in More Than 10 000 Patients Across a Diverse Health Care Network.

Importance: Blood pressure (BP) and cholesterol control remain challenging. Remote care can deliver more effective care outside of traditional clinician-patient settings but scaling and ensuring access to care among diverse populations remains elusive.

Objective: To implement and evaluate a remote hypertension and cholesterol management program across a diverse health care network.

Protecting procedural care-cybersecurity considerations for robotic surgery.

Cybersecurity is an increasingly important concern for reliable healthcare delivery and is particularly salient for robotic surgery. Surgical robots are complex systems with numerous points of vulnerability, and there have been real-world demonstrations of successful cyberattacks on surgical robots. There are several ways to improve the risk profile of robotic surgery, including recognizing system complexity, investing in regular software updates, following cybersecurity best-practices, and increasing transparency for all stakeholders.

Development and Testing of an Electronic Health Record-Integrated Patient-Reported Outcome Application and Intervention to Improve Efficiency of Rheumatoid Arthritis Care.

Objective: Many patients with rheumatoid arthritis (RA) have difficulty finding clinicians to treat them because of workforce shortages. We developed an app to address this problem by improving care efficiency. The app collects patient-reported outcomes (PROs) and can be used to inform visit timing, potentially reducing the volume of low-value visits.

User experience with a voice-enabled smartphone app to collect patient-reported outcomes in rheumatoid arthritis.

Objectives: Rheumatoid arthritis (RA) is a chronic disease, requiring frequent patient-provider interaction and self-monitoring. We developed a novel mobile health smartphone app with a voice-enabled feature to help patients virtually track disease activity and ask general questions about RA.

Methods: With a user-centered design (UCD) approach, we developed a voice-enabled app (VEA) which was then tested in two focus groups of patients (n=8) and one with providers (n=4).

Notes From the Field: A Voice-Activated Video Communication System for Nurses to Communicate With Inpatients With COVID-19.

With the relaxing of telehealth regulations through the Health Insurance Portability and Accountability Act (HIPAA) waiver notification for Telehealth Remote Communications during the COVID-19 Nationwide Public Health Emergency, our organization had the opportunity to pilot an innovative virtual care solution using a modified consumer-grade voice-activated video communication system (Amazon Echo Show 8) within one inpatient COVID-19 unit. In this brief report, we describe our experiences with implementing the system and general feedback from clinicians, and discuss areas for future development required to enable future scaling of this solution. Our pilot demonstrates the feasibility of deploying a consumer-grade voice assistant device in COVID-19 patient rooms.

Deploying digital health tools within large, complex health systems: key considerations for adoption and implementation.

In recent years, the number of digital health tools with the potential to significantly improve delivery of healthcare services has grown tremendously. However, the use of these tools in large, complex health systems remains comparatively limited. The adoption and implementation of digital health tools at an enterprise level is a challenge; few strategies exist to help tools cross the chasm from clinical validation to integration within the workflows of a large health system.

Real-World Analysis of Off-Label Use of Molecularly Targeted Therapy in a Large Academic Medical Center Cohort.

Purpose: The primary objective of this study is to quantify the use of off-label molecularly targeted therapy and describe the clinical situations in which off-label targeted therapy are used. A key secondary objective is to report the outcomes of patients treated with off-label use of targeted therapy.

Patients And Methods: We searched the electronic health record between 2000 and 2020 at our center to characterize the volume, clinical settings, and outcomes associated with off-label use of targeted therapies in different types of solid tumors.

Assessing Patient Experience and Orientation in the Emergency Department with Virtual Windows.

Patients have benefitted from increasingly sophisticated diagnostic and therapeutic innovations over the years. However, the design of the physical hospital environment has garnered less attention. This may negatively impact a patient's experience and health.