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Digital dashboards are used to monitor patients and improve inpatient outcomes in hospital settings. A systematic review assessed the impact of dashboards across five outcomes of hospital mortality, hospital length of stay (LOS), economic impacts, harms, and patient and carer satisfaction.

To develop and evaluate machine learning (ML) models for predicting length of stay (LOS) in elective spine surgery, with a focus on the benefits of temporal modeling and model interpretability.

To compare different machine learning models of loss to follow-up among people with HIV (PWH).

Federated analysis is a method that allows data analysis to be performed on similar datasets without exchanging any data, thus facilitating international research collaboration while adhering to strict privacy laws. This study aimed to evaluate the feasibility of using federated analysis to benchmark mortality in 2 critical care quality registry databases converted to the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM), describing challenges to and recommendations for performing [...]

To assess the calibration of 9 large language models (LLMs) within biomedical natural language processing (BioNLP) tasks, furthering understanding of trustworthiness and reliability in real-world settings.

We aim to leverage more comprehensive phenotypic and genotypic clinical data to enhance the treatment response predictions.

To determine whether a novel digital tool, the Community Vulnerability Compass (CVC), built using large datasets, can accurately measure neighborhood- and individual-level social determinants of health (SDOH) at scale. Existing SDOH indexes fall short of this dual requirement.

To assess the effect of a digital scribe among pediatric providers on documentation time, cognitive load, burnout, and caregiver satisfaction.

This study aims to evaluate the impact of using a large language model (LLM) for generating draft responses to patient messages in the electronic health record (EHR) system on clinicians and support staff workload and efficiency.We partnered with Epic Systems to implement OpenAI's ChatGPT 4.0 for responding to patient messages. A pilot study was conducted from August 2023 to July 2024 across 13 ambulatory specialties involving 323 participants, including clinicians [...]

This study compared the time efficiency of the hospital admission process using personal mobile devices to traditional walk-in methods, thereby assessing the effectiveness of the mobile admission process.This retrospective study was conducted at Chung-Ang University Gwangmyeong Hospital in South Korea (August 2022-January 2023). Turnaround times for the walk-in and mobile admission processes were compared. Patients were divided into mobile and walk-in groups based on their admission process. Collected timestamp data [...]