AIMC Topic: Waiting Lists

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Data-driven queueing modelling: a simulation case study of emergency department crowding.

BMJ health & care informatics
OBJECTIVES: Emergency department crowding refers to a complex state of congestion associated with a set of performance indicators such as occupation levels, waiting times and specific scores. Among current methods to model it, an objective gap exists...

An Artificial Intelligence-Based Framework for Predicting Emergency Department Overcrowding: Development and Evaluation Study.

JMIR medical informatics
BACKGROUND: Emergency department (ED) overcrowding remains a critical challenge, leading to delays in patient care and increased operational strain. Current hospital management strategies often rely on reactive decision-making, addressing congestion ...

Predicting patient risk of leaving without being seen using machine learning: a retrospective study in a single overcrowded emergency department.

BMC emergency medicine
Emergency department (ED) overcrowding has become a critical issue in hospital management, leading to increased patient wait times and higher rates of individuals leaving without being seen (LWBS). This study aims to identify key factors influencing ...

Artificial Intelligence Solutions to Improve Emergency Department Wait Times: Living Systematic Review.

The Journal of emergency medicine
BACKGROUND: Overcrowding and long wait times in emergency departments (EDs) remain global challenges that negatively affect patient outcomes and staff satisfaction. As an emerging technology, artificial intelligence (AI) offers the potential to optim...

Health insurance and kidney transplantation outcomes in the United States: a systematic review and AI-driven analysis of disparities in access and survival.

Renal failure
BACKGROUND: Kidney transplantation is the preferred treatment for end-stage kidney disease (ESKD) in the United States, yet access and outcomes vary by insurance type, race, and socioeconomic status. This systematic review synthesizes U.S.-based evid...

The Effectiveness of a Chatbot Single-Session Intervention for People on Waitlists for Eating Disorder Treatment: Randomized Controlled Trial.

Journal of medical Internet research
BACKGROUND: Early treatment is critical for improving eating disorder prognosis. Single-session interventions (SSIs) can provide short-term support to people on waitlists for eating disorder treatment; however, it is not always possible to access SSI...

Interpretable machine learning models for prolonged Emergency Department wait time prediction.

BMC health services research
OBJECTIVE: Prolonged Emergency Department (ED) wait times lead to diminished healthcare quality. Utilizing machine learning (ML) to predict patient wait times could aid in ED operational management. Our aim is to perform a comprehensive analysis of M...

Development of a Machine Learning-Powered Optimized Lung Allocation System for Maximum Benefits in Lung Transplantation: A Korean National Data.

Journal of Korean medical science
BACKGROUND: An ideal lung allocation system should reduce waiting list deaths, improve transplant survival, and ensure equitable organ allocation. This study aimed to develop a novel lung allocation score (LAS) system, the MaxBenefit LAS, to maximize...

Gender-Equity Model for Liver Allocation Using Artificial Intelligence (GEMA-AI) for Waiting List Liver Transplant Prioritization.

Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association
BACKGROUND & AIMS: We aimed to develop and validate an artificial intelligence score (gender-equity model for liver allocation using artificial intelligence [GEMA-AI]) to predict liver transplantation (LT) waiting list outcomes using the same input v...

Real-Time Analytics and AI for Managing No-Show Appointments in Primary Health Care in the United Arab Emirates: Before-and-After Study.

JMIR formative research
BACKGROUND: Primary health care (PHC) services face operational challenges due to high patient volumes, leading to complex management needs. Patients access services through booked appointments and walk-in visits, with walk-in visits often facing lon...