Constraint Management in a Bottleneck Environment (DRAFT)

2018 ◽  
Author(s):  
Boaz Ronen ◽  
Joseph S Pliskin ◽  
Shimeon Pass
Keyword(s):  
Waiting Times ◽  
Healthcare Systems ◽  
Operating Rooms ◽  
Theory Of Constraints ◽  
Clinical Quality ◽  
Constraint Management ◽  
System Constraint

This chapter introduces steps 4 through 7 of the theory of constraints—that, respectively, decide how to exploit and utilize the constraint, subordinate the system to the constraint, elevate and break the constraint, and do not let inertia become the system constraint. The chapter shows how to achieve more using the existing resources by focusing on the bottleneck. For example, reducing waste (“garbage time”) of the bottleneck can quite quickly increase the system’s throughput. The subordination of the rest of the system to the bottleneck is then discussed. For this purpose, the scheduling mechanism of drum–buffer–rope can be implemented in some areas of healthcare systems, like operating rooms, leading to increased throughput and reduction of waiting times as well as improved clinical quality.

The Hospital and Clinic Improvement Handbook

2018 ◽  
Author(s):  
Boaz Ronen ◽  
Joseph S. Pliskin ◽  
Shimeon Pass ◽  
Donald M. Berwick
Keyword(s):  
Emergency Department ◽  
Performance Measures ◽  
Waiting Times ◽  
Implementation Process ◽  
Operating Rooms ◽  
Theory Of Constraints ◽  
Limited Time ◽  
Healthcare Organizations ◽  
Clinical Quality

The Hospital and Clinic Improvement Handbook is about doing more using existing resources. For example, achieving more throughput in the operating rooms, reducing waiting times at the emergency department, and improving clinical quality. This is done using the well-established Lean techniques together with the breakthrough philosophies and techniques of the theory of constraints (TOC). These methods and their underlying tools are put together with techniques and methodologies implemented by the authors in dozens of healthcare organizations. The tools include the complete kit concept, the Pareto methodology, the focusing table, and the focusing matrix. The book introduces simple tools that can be implemented quite easily in any hospital or clinic. It also focuses on the implementation process using tools like the 3–1–1 model that directs managers where to focus their limited time resources to best improve the performance of their organizations. Finally, the book introduces effective yet simple performance measures and prescribes the process of ongoing improvement.

The Seven Focusing Steps of the Theory of Constraints (DRAFT)

2018 ◽  
Author(s):  
Boaz Ronen ◽  
Joseph S Pliskin ◽  
Shimeon Pass
Keyword(s):  
Performance Measures ◽  
Operating Rooms ◽  
Theory Of Constraints ◽  
Full System ◽  
System View ◽  
Global Performance ◽  
System Constraint ◽  
Cost Utilization ◽  
The Cost ◽  
Measures Of Performance

The theory of constraints has the potential to increase throughput significantly, using existing resources. It consists of seven focusing steps that, when applied, can create extra capacity in operating rooms, emergency departments, imaging services, labs, and so on. The seven steps are simple, intuitive, and easy to implement. This chapter discusses the first three steps of the theory of constraints: determining the system’s goal, establishing global performance measures, and identifying the system constraint. Tools are provided for identifying bottlenecks and determining measures of performance for the system. It also introduces the cost-utilization diagram that provides managers with a full-system view.

Constraint Management under a Market Constraint (DRAFT)

2018 ◽  
Author(s):  
Boaz Ronen ◽  
Joseph S Pliskin ◽  
Shimeon Pass
Keyword(s):  
Healthcare Organization ◽  
Theory Of Constraints ◽  
Excess Capacity ◽  
Healthcare Organizations ◽  
Constraint Management ◽  
Long Run ◽  
Increasing Demand

Having a market constraint means that the system has excess capacity. For such cases, this chapter shows how the seven steps of the theory of constraints (TOC) can help in increasing demand for healthcare organizations’ services. The chapter adds two other important issues: peak management and the three strategic questions for constraint management. Peak management provides tools for managing systems that are characterized by peaks and dips in demand. The three strategic questions determine whether we should design the healthcare organization with excess capacity or with a bottleneck. In the latter case, the chapter analyzes where the constraint should be located in the long run.

Success Stories (DRAFT)

2018 ◽  
Author(s):  
Boaz Ronen ◽  
Joseph S Pliskin ◽  
Shimeon Pass
Keyword(s):  
United States ◽  
Emergency Department ◽  
United Kingdom ◽  
Emergency Room ◽  
The United States ◽  
Healthcare Systems ◽  
Theory Of Constraints ◽  
Wait Times ◽  
Success Stories ◽  
Specific Contribution

This chapter describes some success stories that show how the tools, methods, and philosophies were used in a variety of healthcare systems. The cases presented here include successful implementations in the United States, United Kingdom, and Israel. Each story highlights the objectives and the results of the organization. Objectives include reducing emergency room wait times, reducing delayed admissions, improving emergency department and operating room throughput, improving quality and customer satisfaction. Although the cases use a variety of methods, approaches include eliminating dummy constraints, using specific contribution for prioritization, and working with complete kits, focusing on the theory of constraints, and reducing work in progress.

A Simulation Model for Resource Balancing in Healthcare Systems

2017 ◽  
pp. 78-93
Author(s):  
Arzu Eren Şenaras ◽  
Hayrettin Kemal Sezen
Keyword(s):  
Health Care ◽  
Emergency Department ◽  
Simulation Model ◽  
Waiting Times ◽  
Discrete Event ◽  
Healthcare Systems ◽  
Event Simulation ◽  
Package Program ◽  
Effective Policy ◽  
Very High

This study aims to analyze resource effectiveness through developed model. Changing different number of resources and testing their response, appropriate number of resources can be identified as a basis of resource balancing through what-if analysis. The simulation model for emergency department is developed by Arena package program. The patient waiting times are reduced by the tested scenarios. Health care system is very expensive sector and related costs are very high. To raise service quality, number of doctor and nurse are increased but system target is provided by increased number of register clerk. Testing different scenarios, effective policy can be designed using developed simulation model. This chapter provides the readers to evaluate healthcare system using discrete event simulation. The developed model could be evaluated as a base for new implementations in other hospitals and clinics.

A Simulation Model for Resource Balancing in Healthcare Systems

2020 ◽  
pp. 336-351
Author(s):  
Arzu Eren Şenaras ◽  
Hayrettin Kemal Sezen
Keyword(s):  
Health Care ◽  
Emergency Department ◽  
Simulation Model ◽  
Waiting Times ◽  
Discrete Event ◽  
Healthcare Systems ◽  
Event Simulation ◽  
Package Program ◽  
Effective Policy ◽  
Very High

This study aims to analyze resource effectiveness through developed model. Changing different number of resources and testing their response, appropriate number of resources can be identified as a basis of resource balancing through what-if analysis. The simulation model for emergency department is developed by Arena package program. The patient waiting times are reduced by the tested scenarios. Health care system is very expensive sector and related costs are very high. To raise service quality, number of doctor and nurse are increased but system target is provided by increased number of register clerk. Testing different scenarios, effective policy can be designed using developed simulation model. This chapter provides the readers to evaluate healthcare system using discrete event simulation. The developed model could be evaluated as a base for new implementations in other hospitals and clinics.

scholarly journals COVID-19 pandemic and waiting times in outpatient specialist care in Germany: an empirical analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jennifer Muschol ◽  
Christian Gissel
Keyword(s):  
Health Insurance ◽  
Waiting Times ◽  
Healthcare Providers ◽  
Healthcare Systems ◽  
Linear Mixed Effect Model ◽  
Insurance Status ◽  
Specialist Care ◽  
Mixed Effect ◽  
Physician Visits ◽  
Patient Groups

Abstract Background International healthcare systems face the challenge that waiting times may create barriers to accessing medical care, and that those barriers are unequally distributed between different patient groups. The disruption of healthcare systems caused by the COVID-19 pandemic could exacerbate this already strained demand situation. Using the German healthcare system as an example, this study aims to analyze potential effects of the COVID-19 pandemic on waiting times for outpatient specialist care and to evaluate differences between individual patient groups based on their respective insurance status and the level of supply. Methods We conducted an experiment in which we requested appointments by telephone for different insurance statuses in regions with varying levels of supply from 908 outpatient specialist practices in Germany before and during the COVID-19 pandemic. Data from 589 collected appointments were analyzed using a linear mixed effect model. Results The data analysis revealed two main counteracting effects. First, the average waiting time has decreased for both patients with statutory (mandatory public health insurance) and private health insurance. Inequalities in access to healthcare, however, remained and were based on patients’ insurance status and the regional level of supply. Second, the probability of not receiving an appointment at all significantly increased during the pandemic. Conclusions Patient uncertainty due to the fear of a potential COVID-19 infection may have freed up capacities in physicians’ practices, resulting in a reduction of waiting times. At the same time, the exceptional situation caused by the pandemic may have led to uncertainty among physicians, who might thus have allocated appointments less frequently. To avoid worse health outcomes in the long term due to a lack of physician visits, policymakers and healthcare providers should focus more on regular care in the current COVID-19 pandemic.

Comparison of Subsidy Schemes for Reducing Waiting Times in Healthcare Systems

2017 ◽  
Vol 26 (11) ◽  
pp. 2033-2049 ◽  
Author(s):  
Qu Qian ◽  
Pengfei Guo ◽  
Robin Lindsey
Keyword(s):  
Waiting Times ◽  
Healthcare Systems

Modeling Public Health and Healthcare Systems

2017 ◽  
Author(s):  
Sanjay Basu
Keyword(s):  
Public Health ◽  
Operations Research ◽  
Queuing Theory ◽  
Control Strategies ◽  
Waiting Times ◽  
Healthcare Services ◽  
Healthcare Systems ◽  
Systems Science ◽  
Screening Programs ◽  
Modeling Techniques

This book aims to empower readers to learn and apply engineering, operations research, and modeling techniques to improve public health programs and healthcare systems. Readers will engage in in-depth study of disease detection and control strategies from a “systems science” perspective, which involves the use of common engineering, operations research, and mathematical modeling techniques such as optimization, queuing theory, Markov and Kermack-McKendrick models, and microsimulation. Chapters focus on applying these techniques to classical public health dilemmas such as how to optimize screening programs, reduce waiting times for healthcare services, solve resource allocation problems, and compare macroscale disease control strategies that cannot be easily evaluated through standard public health methods such as randomized trials or cohort studies. The book is organized around solving real-world problems, typically derived from actual experiences by staff at nongovernmental organizations, departments of public health, and international health agencies. In addition to teaching the theory behind modeling methods, the book aims to confer practical skills to readers through practice in model implementation using the statistical software R.

Sign in / Sign up

Export Citation Format

Share Document