Handbook of Healthcare Logistics: Bridging the Gap between Theory and Practice (International Series in Operations Research & Management Science, 302)

This book presents healthcare logistics solutions that have been successfully implemented at a variety of healthcare facilities. In each case, a major challenge is presented, along with the solution approach and implementation steps, followed by the impact on hospital operations. Problems encountered when implementing the results in practice are also discussed. Much of the work presented is drawn from the experiences of members of the Center for Healthcare Operations Improvement and Research (CHOIR) at Twente, along with the CHOIR spin-off company, Rhythm. Contents Making an Impact on Healthcare Logistics 1 Introduction 2 The Ecosystem of Education, Research, and Impact 2.1 The Ecosystem 2.2 Stakeholders 2.3 Education 2.4 Research 2.5 Impact 3 Deliberations for Impact 3.1 Theoretical Projects vs. Practical Projects 3.2 Theoretical Solutions vs. Solutions from Practice 3.3 Building Relationships 3.4 Bottom-Up and Top-Down 4 The Handbook of Healthcare Logistics References Part I Overview of the State-of-the-Art A Survey of Literature Reviews on Patient Planning and Scheduling in Healthcare 1 Introduction 2 A 3D Classification of Planning Decisions in Healthcare 2.1 Hierarchical Planning Levels and Uncertainty 2.2 Planning Complexity 2.2.1 Single Activity Planning 2.2.2 Multidisciplinary Planning 2.2.3 Care Pathway Planning 2.3 A 3D Framework for Planning Decisions in Healthcare 3 Positioning of Overview Papers on Patient Planning and Scheduling Decisions in Healthcare in the 3D Framework References Theoretical and Practical Aspects of Outpatient Clinic Optimization 1 Introduction 1.1 The Outpatient Clinic: The Gate to Elective Hospital Care 1.2 Crucial Concepts: Access and Waiting Time 1.3 Outpatient Clinic Capacity Management 2 Planning and Control of Outpatient Clinics 2.1 Strategic Planning 2.2 Tactical Planning 2.3 Offline Operational Planning 2.4 Online Operational Planning 3 Operations Research Models for Outpatient Clinic Optimization 3.1 Patient Flow Analysis 3.2 Appointment Planning 3.2.1 Single Appointment Planning 3.2.2 Multidisciplinary Appointment Planning 3.2.3 Care Pathway Planning 4 Lessons Learned from a Case Study 5 Current Challenges in Outpatient Clinic Management References Robust Surgery Scheduling: A Model-Based Overview 1 Introduction 2 Internal Variability 2.1 Overtime 2.2 Deviation from the Schedule 3 External Variability 3.1 Overtime 3.1.1 Non-elective Surgery Policy 3.1.2 Required Capacity 3.1.3 Scheduling Elective Surgeries Anticipating Emergencies 3.2 Waiting Time of Emergency Patients 3.2.1 Maximum Waiting Time 3.2.2 Average Waiting Time 4 Artificial Variability 4.1 Blocking Time 5 Multiple Sources of Disturbance 5.1 Overtime 5.2 Waiting Time Emergency Patients 5.3 Deviation from the Schedule 6 Conclusion References Applications of Hospital Bed Optimization 1 Introduction 2 Ward Capacity Management 2.1 Strategic Ward Capacity Management 2.1.1 The Desired Case-Mix of the Hospital 2.1.2 Hospital Layout Planning 2.1.3 Setting Performance Targets 2.1.4 The Number of Beds 2.1.5 Workforce Planning 2.2 Tactical Ward Capacity Management 2.2.1 Master Schedules 2.2.2 Flexible Allocation of Capacity 2.2.3 Regulating the Demand for Care 2.3 Operational Ward Capacity Management 2.3.1 Patient Scheduling 2.3.2 Staff Scheduling 2.4 Feedback Between the Hierarchical Levels 3 Operations Research Models for Wards 3.1 Dimensioning Wards 3.1.1 Queueing Theory 3.1.2 Integer Programming 3.1.3 Markov Chains 3.1.4 Simulation 3.2 Chain Logistics or Flow Optimization 3.2.1 Queueing Theory 3.2.2 Simulation 3.2.3 Mixed Integer Programming 3.2.4 Markov Chains 3.3 Admission Planning 3.3.1 Mixed Integer Programming 3.3.2 Queueing Theory 3.4 Patient Scheduling and Bed Assignment 3.4.1 Mixed Integer Programming 3.4.2 Heuristics 3.4.3 Queueing Theory 3.4.4 Markov Decision Theory 3.4.5 Simulation 3.5 Nurse-to-Patient Ratio 3.5.1 Integer Programming 3.6 Length of Stay and Readmission Forecast 3.6.1 Heuristics 3.6.2 Queueing Theory 3.6.3 Simulation 3.7 Conclusion 4 Impact in Practice of OR at Wards 4.1 Case Study I: Balancing Bed Census 4.1.1 Project Organization 4.1.2 Analysis of Possible Interventions 4.1.3 Choosing an Intervention 4.1.4 After Intervention 4.1.5 Lessons Learned 4.2 Case Study II: Dimensioning Wards 4.2.1 Project Organization 4.2.2 Analysis of Possible Interventions 4.2.3 Choosing an Intervention 4.2.4 After Intervention 4.2.5 Lessons Learned 4.3 Case Study III: Bed Assignment Optimization 4.3.1 Project Organization 4.3.2 Analysis of Possible Interventions 4.3.3 After Intervention 4.3.4 Lessons Learned 4.4 Increasing Impact in Practice 5 The Future State of OR for Wards References Part II OR Applications in Healthcare Planning A Markov Modelling Approach for Surgical Process Analysis in Cataract Surgery 1 Introduction 2 Literature 3 Cataract Surgery and Data Collection Approach 4 Markov Model 5 Data Analysis and Results 6 Conclusions References Emergency Operating Room or Not? 1 Introduction 2 Literature 3 Approach 3.1 Case Mix 3.2 Performance Indicators 4 Simulation Model and OR Analyzer Tool 4.1 Simulation Model 4.2 OR Analyzer Tool 5 Results 5.1 The Effect of Scale 5.2 The Effect of Load and Case Mix Variability 5.3 The Effect of Break-in-Moment Optimization 6 Conclusions References Implementing Algorithms to Reduce Ward Occupancy Fluctuation Through Advanced Planning 1 Introduction 1.1 Problem Description 2 Methodology 2.1 Model Inputs 2.2 Recovering Patients in the Hospital 2.3 Ward Occupancy 2.4 Admission Rate/Discharge Rate 2.5 Patients in Day n of Their Recovery 2.6 Assumptions 3 Application 3.1 Results 3.1.1 Projected Results 3.1.2 Observed Results 3.2 Discussion 4 Conclusion References Bed Census Predictions and Nurse Staffing 1 Introduction 2 Literature 3 Hourly Bed Census Predictions 3.1 Demand Predictions for Elective Patients 3.2 Demand Predictions for Acute Patients 3.3 Demand Predictions Per Care Unit 3.4 Bed Census Predictions 3.5 Performance Indicators 4 Flexible Nurse Staffing 4.1 Staffing Requirements 4.2 Fixed Staffing 4.3 Flexible Staffing 5 Quantitative Results 5.1 Case Study Description 5.2 Case Study Results: Bed Census 5.3 Case Study Results: Nurse Staffing 6 Discussion References Part III Case Studies Workload Forecasting and Demand-Driven Staffing: A Case Study for Post-operative Physiotherapy 1 Introduction 2 Context 2.1 Clinical Physiotherapy in the Sint Maartenskliniek 2.2 Surgery and Physiotherapy Planning in the Original Situation 3 Methods 3.1 Performance Indicators 3.1.1 Definition of Demand 3.1.2 Definition of Supply 3.2 Clinical Workload Prediction 3.3 Staffing Requirements 3.3.1 Management Trade-Off and Insights 4 Implementation 4.1 Pre-measurement of Performance 4.2 Work Group and Considerations 4.3 Participative Staff Rostering 5 Results 6 Conclusion and Discussion Appendix: Demand Prediction for Physiotherapy Treatments References A Quantitative Analysis of Integrated Emergency Posts 1 Introduction 2 Context 2.1 NIP and IEP 2.2 Case Studies 3 Simulation Models 3.1 General Set-Up 3.2 NIP Case Almelo 3.3 IEP Case Almelo 3.4 Changes and Additions Needed for Case Enschede 3.5 Implementation 3.6 Performance Measures 4 Experimental Design 4.1 Case Almelo 4.2 Case Enschede 4.3 Simulation Settings 5 Results 5.1 Case Almelo 5.1.1 Before-After Analysis 5.1.2 Different Configurations 5.1.3 Sensitivity Analysis 5.2 Case Enschede 5.2.1 Before-After Analysis 5.2.2 Process and Capacity Changes 6 Conclusions References Minimizing Variation in Hospital Bed Utilization by Creating a Case Type Schedule for the Operating Room Planning 1 Introduction 2 Formal Problem Description and MILP Model Formulation 3 Quadratic Assignment Problem Model 4 Results of the Case Study 5 Creating Case Types 6 Input Data (Tables 4, 5, and 6) 7 Computational Results 8 Results in Practice 9 Discussion 9.1 Restrictions 9.2 Further Research 10 Valorization Epilogue: Reported Results in Practice References Case Study: Capacity Management in the General Hospital of ZGT, Almelo (NL) 1 Introduction 2 A Shift Toward Capacity Management 2.1 External and Internal Developments that Motivated the Shift 2.2 Introducing Capacity Management at ZGT 3 Key Elements of Capacity Management at ZGT 3.1 Centralized Versus Decentralized Planning 3.2 Management of Variability 3.3 Capacity Allocation for Urgent Surgeries 3.4 Relationship Between Outpatient Clinic and the OT and Wards 3.5 Master Surgical Schedule for the OT 3.6 Waiting List Management 3.7 Improving Ward Utilization 4 Implementation of Capacity Management at ZGT 5 Results and Lessons Learned 5.1 Results 5.1.1 Costs 5.1.2 OT Utilization, Access Time, and Turnover 5.1.3 Ward Utilization and Turnover 5.2 Lessons Learned References