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«Luis J Maseda B.S. Engineering Science and Biomechanics (1997) University of Florida Submitted to the System Design and Management Program in partial ...»

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Real Options Analysis of Flexibility in a Hospital Emergency

Department Expansion Project, a Systems Approach

by

Luis J Maseda

B.S. Engineering Science and Biomechanics (1997)

University of Florida

Submitted to the System Design and Management Program in partial

Fulfillment of the Requirements for the Degree of

Master of Science in Engineering and Management

at the

Massachusetts Institute of Technology

May 2008

© 2008 Luis J Maseda

All rights reserved

The author hereby grants to MIT permission to reproduce and to distribute publicly paper and electronic copies of this thesis document in whole or in part.

Signature of Author:

Luis J Maseda System Design and Management Program

Certified by:

Richard de Neufville Thesis Supervisor Professor of Engineering Systems

Certified by:

Patrick Hale Director System Design and Management Program 1 This Page Intentionally Left Blank 2 Real Options Analysis of Flexibility in a Hospital Emergency Department Expansion Project, a Systems Approach by Luis J Maseda Submitted to the System Design and Management Program On May 9, 2008 in partial Fulfillment of the Requirements for the Degree of Master of Science in Engineering and Management

ABSTRACT

Hospital Emergency Departments across the United States have been experiencing demand in excess of their capacity to treat patients for the last two decades. This research considers a hypothetical case inspired by a hospital in the Greater Boston undergoing an ED expansion to meet existing and projected demand. A traditional infrastructure expansion project approach to plan, design and immediately build for expected demand 10 to 15 years into the future is compared to a flexible design able to meet short term demands and then adapt to future demand realization. It is the overall objective of this research to identify, characterize and quantify the parameters that should be considered in ED expansion projects and provide useful modeling techniques to drive investment decisions that best allow hospital administrators to provide expected level of service to their patient population.

Thesis Supervisor: Dr. Richard de Neufville Title: Professor of Engineering Systems

–  –  –

First and foremost, I would like to thank my ever patient thesis advisor Professor Richard de Neufville whose guidance and knowledge were paramount in making this thesis the product that it is. He drove me to up my game and increase my critical thinking to new levels. His wit and command of Spanish colloquialisms brought well timed humor in the toughest of times. ¡Gracias Profesor Richard!

I would like to thank my classmates, many of who have become lifelong friends. They were unknowingly my mentors in many ways and humbling in their accomplishments.

Ignacio Aguirre, his calm manner always kept us on track and his competence enriched every project we worked on. Jim Casey, our animated discussions broadened my perspective and long work sessions were part of the crucible that is SDM. Jeff Manning, his endurance made me embarrassed to ever admit I was tired, and his technical knowledge was a constant source of learning for me. Roberto Acosta, his dedication was always worth emulating and served as my coding guru. Bob Corby, who inspired me to give another lifelong dream one more try. All of them, by just being themselves pushed me to be better.

To my TA, classmate and friend Jorge Oliveira who introduced me to the good folk of GBH, thank you. His support and mentoring made me a better student and professional.

I wish him most success as he advances game changing concepts in the healthcare field during his PhD work. To Paul, Caroline, Tim and Joe at GBH who allowed me to observe their work, provided endless data requests and ultimately inspired this work.

To Janet Hart, Steve Moreci and others of the Boston Scientific management team Boston Scientific who believed in me enough to sponsor my time at MIT and Sloan. I am truly grateful to you for taking a chance and stepping off the beaten path to try a new way. May our paths cross again in calmer waters.

To my mother Carmen who always made me believe I could do anything I set my mind to. Her own pursuit of higher education later in life was a living example of it never being too late or too hard. To my father Luis who has always been an inspiration of integrity, dedication, tenacity and professional success.

Saying that I would like to thank my wife Jen seems to fall short of my gratitude for having her in my life and her role in this my journey through the hallowed halls of MIT. I drew strength from her devotion and unyielding faith in me through all of this. The late nights into very early mornings and sacrificed weekends always seemed worthwhile to her as a price to pay for this one dream of mine; I say dream, she would say birthright.

Jen‘s own journey in pursuit of educational excellence at that school up the river fueled my drive to not settle for anything short of the becoming part of the best. In short, she is my muse and inspiration for everything I do that is worth doing. My daughter Isabella, who dropped into this crazy ride just as it was coming to a close. She brought joy and perspective to many a tough day of balancing life, work and school. She loved reviewing this thesis while I carried her in my arms and was always a kind critic; mostly smiling and making happy baby sounds. This and all I do is dedicated to both of them.





–  –  –

Abstract

Acknowledgements

Table of Contents

List of Figures

List of Tables

Chapter 1. Introduction

1.1 Current State of Emergency Care

1.2 National and Local Context

1.3 Organization of Thesis and General Approach

Chapter 2. Real Options Background, Traditional Project Valuation Methods and Real Options ‗in‘ Engineering Systems

2.1 Real Options Background

2.2 Traditional Project Evaluation Methods

2.2.1 Net Present Value

2.2.2 Benefit-Cost Analysis and Benefit-Cost Ratio

2.2.3 Internal Rate of Return

2.2.4 Payback Period

2.3 Real Options Analysis in Engineering Systems

2.3.1 Evaluating Flexibility

Chapter 3. Real Options Analysis of the ED System

3.1 The spreadsheet model

3.2 Simulation steps

3.3 ED Expansion Configurations

3.4 The Analysis

Chapter 4. Conclusion and Suggestion for Future Work

4.1 Conclusion

4.2 Recommendations for Future Work

Bibliography

Appendix A. ED as an Engineering System

The Healthcare Enterprise

7 Enterprise Systems Architecture view of the ED

Strategy View

Policy View

Process View

Information Technology View

Determining Service Area

Demand for ED Services

Expansion as the solution

Process Improvement as the solution

Level of Service

Appendix B. JCHAO Guidelines for ED Patient Flow Planning

8List of Figures

FIGURE 1-1 TRENDS IN EDS, VISITS AND HOSPITALS IN THE US

FIGURE 1-2 ED VISITS AND HMO PENETRATION RATES IN MA (MCMANUS 2001)................. 19

FIGURE 2-1 COMPARISON OF NPV AND REAL OPTIONS ANALYSIS USING DECISION TREES

(WILLIAMS, MAMMES ET AL. 2007)

FIGURE 3-1 REAL OPTIONS MODEL SCREENSHOT EXAMPLE FOR THE GBH ED SIMULATION... 39

FIGURE 3-2 EXAMPLES OF NPV SIMULATION HISTOGRAM AND CDF SIMULATION.................. 41

FIGURE 3-3 COMPARISON OF ED CONFIGURATIONS FROM THE ADVISORY BOARD COMPANY

INNOVATIONS CENTER (2007)

FIGURE 3-4 SUMMARY OF EXPANSION SCENARIOS MODELED

FIGURE 3-5 COMPARISON OF DEMAND AND CAPACITY OVER THE LIFE OF THE 45 BED

DETERMINISTIC EXPANSION CASE SCENARIO.

FIGURE 3-6 COMPARISON OF DETERMINISTIC 45 BED EXPANSION AND RANDOMIZED

SIMULATION.

FIGURE 3-7 SUMMARY OF 2/4/14 EXPANSION SIMULATION RESULTS

FIGURE 3-8 SUMMARY OF FLEXIBLE SCENARIO 3/5/10

FIGURE 3-9 COMPARISON OF EQUAL END NUMBER OF BEDS

FIGURE 3-10 VARG CURVES FOR SAME TOTAL NUMBER OF BED RIGID AND FLEXIBLE

EXPANSION

FIGURE 3-11 FLEXIBLE EXPANSION SCENARIOS NORMALIZED TO AN EQUAL POD SIZE............. 49 FIGURE 3-12 VARG COMPARISON OF STATIC AND FLEXIBLE EXPANSION SCENARIOS............. 50 FIGURE 3-13 SUMMARY OF SIMULATION RUNS FOR EACH FLEXIBLE EXPANSION SCENARIO...... 51 FIGURE 3-14 SUMMARY OF MODELED SCENARIOS

FIGURE 3-15 COMPARISON OF 50 BED 3/5/10 CONFIGURATION TO OTHER EXPANSION SCENARIOS

–  –  –

TABLE 3-1 SUMMARY OF EXPANSION SCENARIOS MODELED

TABLE 3-2 COMPARISON OF DETERMINISTIC 45 BED EXPANSION AND RANDOMIZED SIMULATION.

TABLE 3-3 SUMMARY OF 2/4/14 EXPANSION SIMULATION RESULTS.

TABLE 3-4 SUMMARY OF FLEXIBLE SCENARIO 3/5/10

TABLE 3-5 COMPARISON OF EQUAL END NUMBER OF BEDS

TABLE 3-6 FLEXIBLE EXPANSION SCENARIOS NORMALIZED TO AN EQUAL POD SIZE................. 49 TABLE 3-7 SUMMARY OF SIMULATION RUNS FOR EACH FLEXIBLE EXPANSION SCENARIO......... 51 TABLE 3-8 SUMMARY OF MODELED SCENARIOS

TABLE 3-9 COMPARISON OF 50 BED 3/5/10 CONFIGURATION TO OTHER EXPANSION SCENARIOS

–  –  –

The purpose of this thesis is to provide hospital administrators with methods to manage the uncertain future of an ED engineering system with only the benefit of today‘s perspective. More precisely, this work takes a systems approach to the application of Real Options (RO) analysis to manage uncertainty as it relates to a hospital Emergency Department (ED) expansion project.

This work is inspired by a hospital in the Greater Boston area that is undertaking an ED expansion project of a 20 year old facility to address current capacity issues and meet future demand. A traditional deterministic approach to facility design and project valuation (i.e. NPV or IRR) is compared to a flexible design and RO framework appropriate for the healthcare context. The hospital is referred to as Greater Boston Hospital (GBH) for purposes of discretion.

This research compares a traditional infrastructure expansion project approach to plan, design and immediately build for expected demand 15 to 20 years into the future with a flexible design able to meet short term demands and then adapt to future demand realization. The traditional approach creates an initial excess in capacity and ties up funds that could be better invested in other more present and pressing needs of the enterprise. Specifically in the case of an ED, these spent funds could be directed to address system hospital system constraints that cause ED issues. The flexible approach provides a way to allocate investments to meet immediate needs and to then allocate future funds as uncertainty is resolved over time. It is the overall objective of this research to identify, characterize and quantify the parameters that should be considered in ED expansion projects and provide a useful modeling technique to drive investment decisions that best allow hospital administrators to provide expected level of service to their patient population.

13 There are plenty of examples in the literature of RO analysis of big industry projects such as ore mining and the oil field development. Well known examples of RO analysis also exist in aviation, pharmaceuticals, and various other manufacturing industries.

Examples of RO analysis in hospital projects, and specifically in the design of an ED expansion, are uncommon or unheard of. This work attempts to expand upon the limited examples of RO analysis in healthcare infrastructure to help further advance the practice of RO analysis and provide a holistic framework for the evaluation and design of healthcare facility expansion projects.

As such, the objective of this research is threefold:

1. To describe the complexity of the ED system as it relates to operational and capacity planning uncertainty

2. Introduce the concepts of design flexibility in a healthcare context; specifically, Emergency Department design.

3. Contribute a healthcare infrastructure case to the growing body of knowledge of Real Options analysis of flexible designs.

1.1 Current State of Emergency Care It is useful to introduce the current state of Emergency Care in the United States to fully understand the scope of this work. It should become apparent throughout this introduction that the ED is a complex engineering system heavily influenced by its local context.

The United States has been facing an impending healthcare crisis rooted in demographic driven increases in demand for services, unaffordable costs, facility capacity shortfalls, inefficient processes and lagging infrastructure investment. This has been especially the case when it comes to Emergency Care and Emergency Departments (ED) across the nation. The issues are readily observable at most any ED where waiting times frustrate patients and lengths of stay are longer than they need be.

These strains on capacity lead EDs to regularly go on diversion for periods of time that essentially shuts the door to any patients incoming via emergency service transport.

The causes of these capacity issues are numerous and vary from hospital to hospital;

–  –  –

The following terms are used throughout this work and defined as follows by the

American College of Emergency Physicians (2003):

ED Overcrowding: A situation in which the identified need for emergency services exceeds the available resources in the ED. Evidence of ED overcrowding is typically found when the number of patients receiving care exceeds the number of staffed ED beds, which may lead to the use of hallways and other non-treatment areas to assess or monitor patients and is usually associated with lengthy waiting times for treatment.



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