REAL-TIME SCHEDULING FOR OUTPATIENT CLINICS
Many outpatient clinics experience variation in their utilization with surge times and down times. We provide a real-time scheduling algorithm to better schedule the patients and improve utilization, patient wait-time, and staff satisfaction.
EFFECTS OF STAFFING PATTERNS ON PATIENT CARE
For patients who are hospitalized, it is often the case that their clinical care team changes, sometimes entirely, during their stay. An interesting question is to understand whether or not such changes in the care team affect patients’ length-of-stay in hospital.
LEVEL-LOADING IN PRIMARY CARE CLINICS
Primary care is the gateway to the healthcare system for many patients. Although primary care itself only accounts for 5% of healthcare spending, the decisions made in primary care setting influences the subsequent medical care including subspecialty referrals, imaging, medical testing, invasive procedures, and hospitalization. We use optimization and data analytics to improve the level-loading for clinical staff in primary care clinics which in turn improves patient flow, wait time, and patient care.
IMPROVING OPERATING ROOMS SCHEDULING UNDER UNCERTAINTY
Operating rooms are one of the main resources in a hospital and any disruption in their workflow can have a cascade effect on the rest of the hospital operations. We use machine-learning, data analytics, and optimization to find a stable schedule to maximize utilization while reducing the risk of operational disruptions.