A5000839279- Healthcare Operations and Scheduling Optimization
- Healthcare Policy and Management
- Operations Management Techniques
- Emergency and Acute Care Studies
- Hospital Admissions and Outcomes
- Advanced Queuing Theory Analysis
- Facility Location and Emergency Management
- Health Systems, Economic Evaluations, Quality of Life
- Clinical practice guidelines implementation
- Urban Transport and Accessibility
- Trauma and Emergency Care Studies
- Healthcare Technology and Patient Monitoring
- Hemodynamic Monitoring and Therapy
- Medical Coding and Health Information
- Machine Learning in Healthcare
- Supply Chain Resilience and Risk Management
- Statistical Methods in Epidemiology
- Infection Control and Ventilation
- Advanced Statistical Process Monitoring
- Primary Care and Health Outcomes
- Transportation and Mobility Innovations
- Scheduling and Timetabling Solutions
- Quality and Supply Management
- Disaster Response and Management
- Pharmacy and Medical Practices
Dalhousie University
2015-2025
Izaak Walton Killam Health Centre
2015-2016
The Netherlands Cancer Institute
2010-2014
University of Twente
2010-2012
Hospitals traditionally segregate resources into centralized functional departments such as diagnostic departments, ambulatory care centers, and nursing wards. In recent years this organizational model has been challenged by the idea that higher quality of efficiency in service delivery can be achieved when services are organized around patient groups. Examples include specialized clinics for breast cancer patients clinical pathways diabetes patients. struggling with question whether to...
A report from the Canadian Institute for Health Information found unplanned hospital readmissions (UHR) common, costly, and potentially avoidable, estimating a $1.8 billion cost to healthcare system associated with inpatient within 30 days of discharge studied period (11 months). The first step towards addressing this costly problem is enabling early detection patients at risk through detecting UHR factors. We utilized Machine Learning explainability tools examine factors discharge,...
Abstract Background The growing demand for healthcare services challenges patient flow management in health systems. Alternative Level of Care (ALC) patients who no longer need acute care yet face discharge barriers contribute to prolonged stays and hospital overcrowding. Predicting these at admission allows better resource planning, reducing bottlenecks, improving flow. This study addresses three objectives: identifying likely ALC patients, key predictive features, preparing guidelines...
As the demand for health care services increases, need to improve patient flow between departments has likewise increased. Understanding how master surgical schedule (MSS) affects inpatient wards and exploiting this relationship can lead a decrease in surgery cancellations, more balanced workload, an improvement resource utilization. We modeled used model evaluate select new MSS hospital.An operational research was combination with staff input develop MSS. A series of MSSs were proposed by...
Machine learning is a powerful tool that can be used to solve wide range of problems in various applications and industries. The healthcare sector has faced specific challenges have kept machine algorithms from becoming as widely quickly adopted other Data access management challenges, ethical considerations, safety, physician patient perception present bigger barriers implementation than model performance. In this paper, we propose adapting customizing the concept preconditions...
We introduce the categorized reference database ORchestra, which is available online at http://www.utwente.nl/choir/orchestra/ .
Outpatient clinics traditionally organize processes such that the doctor remains in a consultation room while patients visit for consultation, we call this Patient-to-Doctor policy (PtD-policy). A different approach is Doctor-to-Patient (DtP-policy), whereby travels between multiple rooms, which prepare their consultation. In latter approach, saves time by consulting fully prepared patients. We use queueing theoretic and discrete-event simulation to provide generic models enable performance...