Patient Scheduling Software

Patient Scheduling Software is a digital tool that makes it easier to book and manage appointments for patients. These tools can optimize clinic workflows, reduce no-shows, and improve patient satisfaction and engagement.

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"A Machine Learning Approach for Predicting Patient No-Show in Hospital Outpatient Departments"

This research was conducted by M. Aloraini, A. Al-Badr, and A. AlDhalaan. It was published in the journal BMC Medical Informatics and Decision Making in 2023. The research showed that machine learning models can be used to predict patient no-shows in hospital outpatient departments, which can help improve patient scheduling and reduce wasted resources. The study used data from a large hospital in Saudi Arabia and found that the Gradient Boosting model had the highest prediction accuracy.

"Bridging pre-surgical endocrine therapy for breast cancer during the COVID-19 pandemic: outcomes from the B-MaP-C study"

This research was conducted by a team of researchers and published in the journal Breast Cancer Research and Treatment in 2023. The study examined the use of 'bridging' endocrine therapy (BrET) as a strategy to manage patient scheduling during the COVID-19 pandemic. The study found that BrET was effective in managing patient care during a period of reduced surgical capacity, and that the majority of patients on BrET had strong ER positivity, suggesting this strategy was reserved for those with tumors that were most likely to respond.

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