AIMC Topic: Appointments and Schedules

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Appointment Scheduling Problem in Complexity Systems of the Healthcare Services: A Comprehensive Review.

Journal of healthcare engineering Mar 3, 2022
This paper provides a comprehensive review of Appointment Scheduling (AS) in healthcare service while we propose appointment scheduling problems and various applications and solution approaches in healthcare systems. For this purpose, more than 150 s...
Appointments and Schedules Markov Chains Patient Satisfaction Humans Artificial Intelligence Computer Simulation
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Predictive and Causal Analysis of No-Shows for Medical Exams During COVID-19: A Case Study of Breast Imaging in a Nationwide Israeli Health Organization.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 21, 2022
"No-shows", defined as missed appointments or late cancellations, is a central problem in healthcare systems. It has appeared to intensify during the COVID-19 pandemic and the nonpharmaceutical interventions, such as closures, taken to slow its sprea...
Israel COVID-19 Humans Causality Pandemics Appointments and Schedules
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Word Embedding and Clustering for Patient-Centered Redesign of Appointment Scheduling in Ambulatory Care Settings.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 21, 2022
. A key to a more efficient scheduling systems is to ensure appointments are designed to meet patient's needs and to design and simplify appointment scheduling less prone to error. Electronic Health Records (EHR) consist of valuable information about...
Ambulatory Care Humans Ambulatory Care Facilities Cluster Analysis Patient-Centered Care Appointments and Schedules
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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...
Humans Neural Networks, Computer Machine Learning Logistic Models Support Vector Machine Decision Trees Algorithms Databases, Factual Computational Biology Stochastic Processes Bayes Theorem Appointments and Schedules No-Show Patients Area Under Curve Data Interpretation, Statistical
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Characterising the nationwide burden and predictors of unkept outpatient appointments in the National Health Service in England: A cohort study using a machine learning approach.

PLoS medicine Oct 12, 2021
BACKGROUND: Unkept outpatient hospital appointments cost the National Health Service £1 billion each year. Given the associated costs and morbidity of unkept appointments, this is an issue requiring urgent attention. We aimed to determine rates of un...
Humans Appointments and Schedules Machine Learning Models, Theoretical Outpatients Delivery of Health Care Health Services England Likelihood Functions Cohort Studies
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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...
Humans Office Visits Academic Medical Centers Machine Learning Appointments and Schedules Child Electronic Health Records No-Show Patients ROC Curve Ambulatory Care Facilities Efficiency, Organizational Ophthalmology
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Patient-Centered Appointment Scheduling: a Call for Autonomy, Continuity, and Creativity.

Journal of general internal medicine Sep 3, 2020
When making an appointment, patients are generally unaware of how much clinician time is available to address their concerns. Similarly, the primary care clinician is often unaware of what the patient expects to accomplish during the visit, leading t...
Patient-Centered Care Appointments and Schedules Artificial Intelligence Primary Health Care Chronic Disease Humans
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A deep learning approach for facility patient attendance prediction based on medical booking data.

Scientific reports Sep 3, 2020
Nowadays, data-driven methodologies based on the clinical history of patients represent a promising research field in which personalized and intelligent healthcare systems can be opportunely designed and developed. In this perspective, Machine Learni...
Appointments and Schedules Office Visits Humans Algorithms Deep Learning
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A Machine Learning-Based Approach for Predicting Patient Punctuality in Ambulatory Care Centers.

International journal of environmental research and public health May 24, 2020
Late-arriving patients have become a prominent concern in several ambulatory care clinics across the globe. Accommodating them could lead to detrimental ramifications such as schedule disruption and increased waiting time for forthcoming patients, wh...
Ambulatory Care Male Time Factors Logistic Models United States Machine Learning Medicare Female Humans Appointments and Schedules Aged Neural Networks, Computer
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Artificial Intelligence: A New Tool in Operating Room Management. Role of Machine Learning Models in Operating Room Optimization.

Journal of medical systems Dec 10, 2019
We conducted a systematic review of literature to better understand the role of new technologies in the perioperative period; in particular we focus on the administrative and managerial Operating Room (OR) perspective. Studies conducted on adult (≥ 1...
Machine Learning Appointments and Schedules Efficiency, Organizational Operating Rooms Models, Organizational Humans Artificial Intelligence
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