AIMC Topic: No-Show Patients

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Predictive Optimization of Patient No-Show Management in Primary Healthcare Using Machine Learning.

Journal of medical systems Jan 14, 2025
The "no-show" problem in healthcare refers to the prevalent phenomenon where patients schedule appointments with healthcare providers but fail to attend them without prior cancellation or rescheduling. In addressing this issue, our study delves into ...
Appointments and Schedules No-Show Patients Multivariate Analysis Humans Machine Learning Primary Health Care
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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 Jan 6, 2025
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...
Humans Artificial Intelligence Female Adult United Arab Emirates Waiting Lists Appointments and Schedules Male No-Show Patients Middle Aged Primary Health Care
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Public health nurse perspectives on predicting nonattendance for cervical cancer screening through classification, ensemble, and deep learning models.

Public health nursing (Boston, Mass.) May 17, 2024
OBJECTIVES: Women's attendance to cervical cancer screening (CCS) is a major concern for healthcare providers in community. This study aims to use the various algorithms that can accurately predict the most barriers of women for nonattendance to CS.
Adult Uterine Cervical Neoplasms Middle Aged Deep Learning Humans Female Nurses, Public Health Public Health Nursing Mass Screening Early Detection of Cancer No-Show Patients
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Efficient Prediction of Missed Clinical Appointment Using Machine Learning.

Computational and mathematical methods in medicine Oct 22, 2021
Public health and its related facilities are crucial for thriving cities and societies. The optimum utilization of health resources saves money and time, but above all, it saves precious lives. It has become even more evident in the present as the pa...
Data Interpretation, Statistical Bayes Theorem Appointments and Schedules No-Show Patients Support Vector Machine Decision Trees Area Under Curve Stochastic Processes Humans Neural Networks, Computer Machine Learning Computational Biology Logistic Models Algorithms Databases, Factual
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Application of Machine Learning to Predict Patient No-Shows in an Academic Pediatric Ophthalmology Clinic.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
Patient "no-shows" are missed appointments resulting in clinical inefficiencies, revenue loss, and discontinuity of care. Using secondary electronic health record (EHR) data, we used machine learning to predict patient no-shows in follow-up and new p...
Appointments and Schedules Ambulatory Care Facilities Child Efficiency, Organizational ROC Curve Humans Office Visits Academic Medical Centers Ophthalmology Machine Learning No-Show Patients Electronic Health Records
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Artificial Intelligence Predictive Analytics in the Management of Outpatient MRI Appointment No-Shows.

AJR. American journal of roentgenology Sep 9, 2020
Outpatient appointment no-shows are a common problem. Artificial intelligence predictive analytics can potentially facilitate targeted interventions to improve efficiency. We describe a quality improvement project that uses machine learning techniqu...
Magnetic Resonance Imaging Ambulatory Care No-Show Patients Middle Aged Adolescent Child Prospective Studies Humans Female Machine Learning Aged Forecasting Adult Aged, 80 and over Male Young Adult
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Prediction of hospital no-show appointments through artificial intelligence algorithms.

Annals of Saudi medicine Dec 5, 2019
BACKGROUND: No-shows, a major issue for healthcare centers, can be quite costly and disruptive. Capacity is wasted and expensive resources are underutilized. Numerous studies have shown that reducing uncancelled missed appointments can have a tremend...
Appointments and Schedules Sex Factors No-Show Patients Outpatient Clinics, Hospital Middle Aged Artificial Intelligence Age Factors Algorithms Models, Statistical Electronic Health Records Humans Risk Factors Female Aged Male
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Machine-Learning-Based Prediction of a Missed Scheduled Clinical Appointment by Patients With Diabetes.

Journal of diabetes science and technology May 3, 2016
BACKGROUND: About 10% of patients with diabetes discontinue treatment, resulting in the progression of diabetes-related complications and reduced quality of life.
Male ROC Curve Logistic Models Diabetes Mellitus Humans Machine Learning Area Under Curve Algorithms No-Show Patients Female
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Predicting Patient No-Shows: Situated Machine Learning with Imperfect Data.

Studies in health technology and informatics Aug 22, 2024
Patients who do not show up for scheduled appointments are a considerable cost and concern in healthcare. In this study, we predict patient no-shows for outpatient surgery at the endoscopy ward of a hospital in Denmark. The predictions are made by tr...
Machine Learning Denmark Appointments and Schedules Humans No-Show Patients
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Machine Learning and Medical Appointment Scheduling: Creating and Perpetuating Inequalities in Access to Health Care.

American journal of public health Apr 1, 2020
Machine Learning Socioeconomic Factors Humans Black or African American Health Services Accessibility Appointments and Schedules No-Show Patients
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