AIMC Topic: Appointments and Schedules

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[Prioritized appointment allocation in new patients, what is really decisive? : Comparative analysis of manual appointment allocation with automated and AI-assisted approaches].

Zeitschrift fur Rheumatologie
BACKGROUND: The timely allocation of appointments for new patients is a daily challenge in rheumatological practice, which can be supported by digital solutions. The question is to find the simplest and most effective possible method for prioritizati...

Revolutionizing Schedules: The Power of AI in Physician Practices.

Frontiers of health services management
Since the early 2000s, artificial intelligence (AI) has raised concerns regarding its use in healthcare to manage vast amounts of patient data, ensure proper handling, and maintain robust security measures. Nevertheless, contemporary healthcare organ...

Machine Learning-Based Approach to Predict Last-Minute Cancellation of Pediatric Day Surgeries.

Computers, informatics, nursing : CIN
The last-minute cancellation of surgeries profoundly affects patients and their families. This research aimed to forecast these cancellations using EMR data and meteorological conditions at the time of the appointment, using a machine learning approa...

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

Journal of healthcare engineering
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...

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
"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...

Word Embedding and Clustering for Patient-Centered Redesign of Appointment Scheduling in Ambulatory Care Settings.

AMIA ... Annual Symposium proceedings. AMIA Symposium
. 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...

Efficient Prediction of Missed Clinical Appointment Using Machine Learning.

Computational and mathematical methods in medicine
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...

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
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...

Application of Machine Learning to Predict Patient No-Shows in an Academic Pediatric Ophthalmology Clinic.

AMIA ... Annual Symposium proceedings. AMIA Symposium
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...

Patient-Centered Appointment Scheduling: a Call for Autonomy, Continuity, and Creativity.

Journal of general internal medicine
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...