Patient no-show predictive model development using multiple data sources for an effective overbooking approach

Medicine & Life Sciences

• No-Show Patients 100%
• Information Storage and Retrieval 50%
• Costs and Cost Analysis 17%
• Appointments and Schedules 15%
• Datasets 14%
• Outpatients 13%
• Electronic Health Records 9%
• Insurance 9%
• Health Care Costs 8%
• Statistics 7%
• Logistic Models 6%
• Demography 5%
• Pediatrics 5%
• Physicians 5%

Engineering & Materials Science

• Costs 20%
• Scheduling 18%
• Pediatrics 18%
• Insurance 16%
• Logistic regression 15%
• Productivity 10%
• Statistics 10%
• Health 10%