Planning and scheduling in healthcare for better care coordination: Current understanding, trending topics, and future opportunities
This study reviews the research on planning and scheduling in healthcare published in
Production and Operations Management (POM) and other prestigious operations …
Production and Operations Management (POM) and other prestigious operations …
[HTML][HTML] Hospital surge capacity preparedness in disasters and emergencies: a systematic review
Background Adequate and effective emergency preparedness for hospital surge capacity is
a prerequisite to ensuring standard healthcare services for disaster victims. This study aimed …
a prerequisite to ensuring standard healthcare services for disaster victims. This study aimed …
[HTML][HTML] Resource planning strategies for healthcare systems during a pandemic
We study resource planning strategies, including the integrated healthcare resources'
allocation and sharing as well as patients' transfer, to improve the response of health …
allocation and sharing as well as patients' transfer, to improve the response of health …
Optimal resource and demand redistribution for healthcare systems under stress from COVID-19
When facing an extreme stressor, such as the COVID-19 pandemic, healthcare systems
typically respond reactively by creating surge capacity at facilities that are at or approaching …
typically respond reactively by creating surge capacity at facilities that are at or approaching …
Admission, discharge, and transfer control in patient flow logistics: Overview and future research
Patient flow logistics involves managing and coordinating the movement of patients within a
healthcare system. It aims to optimize the patients' flow from their arrival to discharge or …
healthcare system. It aims to optimize the patients' flow from their arrival to discharge or …
Management of resource sharing in emergency response using data-driven analytics
This research models a medical resource-sharing problem with three powerful techniques in
analytics: mixed-integer linear programming (MILP), deep q-learning (DQL), and double …
analytics: mixed-integer linear programming (MILP), deep q-learning (DQL), and double …
Design mechanism to coordinate a hierarchical healthcare system: Patient subsidy vs. capacity investment
ZP Li, Z Zou - Omega, 2023 - Elsevier
Motivated by the problems of imbalance between the supply of and demand for the different
levels of hospitals in a hierarchical healthcare system, we propose two contract …
levels of hospitals in a hierarchical healthcare system, we propose two contract …
[HTML][HTML] Variation of daily care demand in Swiss general hospitals: longitudinal study on capacity utilization, patient turnover and clinical complexity levels
N Sharma, R Schwendimann, O Endrich… - Journal of medical …, 2021 - jmir.org
Background Variations in hospitals' care demand relies not only on the patient volume but
also on the disease severity. Understanding both daily severity and patient volume in …
also on the disease severity. Understanding both daily severity and patient volume in …
Optimal admission and queuing control with reneging behavior under premature discharge decisions
Queues or waiting lines are a common phenomenon in healthcare facilities. The increasing
number of admissions to hospital emergency departments (EDs) has resulted in …
number of admissions to hospital emergency departments (EDs) has resulted in …
An Interactive Decision-Support Dashboard for Optimal Hospital Capacity Management
F Parker, DA Martínez, J Scheulen… - arXiv preprint arXiv …, 2024 - arxiv.org
Data-driven optimization models have the potential to significantly improve hospital capacity
management, particularly during demand surges, when effective allocation of capacity is …
management, particularly during demand surges, when effective allocation of capacity is …