A study of implementing theory of constraints healthcare services

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D

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A STUDY OF IMPLEMENTING

THE THEORY OF CONSTRAINTS IN HEALTHCARE SERVICES

GUSTAVO MARÍSIO BACELAR DA SILVA TESE DE DOUTORAMENTO APRESENTADA

À FACULDADE DE MEDICINA DA UNIVERSIDADE DO PORTO EM INVESTIGAÇÃO CLÍNICA E EM SERVIÇOS DE SAÚDE

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A STUDY OF IMPLEMENTING THE THEORY OF CONSTRAINTS IN HEALTHCARE SERVICES

GUSTAVO MARÍSIO BACELAR DA SILVA

TESE DE DOUTORAMENTO APRESENTADA

À FACULDADE DE MEDICINA DA UNIVERSIDADE DO PORTO EM INVESTIGAÇÃO CLÍNICA E EM SERVIÇOS DE SAÚDE

SUPERVISOR

Pedro Pereira Rodrigues

Department of Community Medicine, Information and Health Decision Sciences, Faculty of Medicine, University of Porto

CINTESIS - Center for Health Technology and Services Research, Faculty of Medicine, University of Porto

CO-SUPERVISOR

James F. Cox III

Management Department, Terry College of Business, University of Georgia, Athens, GA, USA

This work was supported by the FCT (Fundação para a Ciência e a Tecnologia; PD/BD/ 129829/2017) and funded by the European Social Fund and national MCTES funds. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of this manuscript.

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Corpo docente catedrático

(Por antiguidade)

Patrício Manuel Vieira Araújo Soares Silva Alberto Manuel Barros da Silva

Jose Henrique Dias Pinto de Barros Maria Fátima Machado Henriques Carneiro Maria Dulce Cordeiro Madeira

Altamiro Manuel Rodrigues Costa Pereira Manuel Jesus Falcao Pestana Vasconcelos

João Francisco Montenegro Andrade Lima Bernardes Maria Leonor Martins Soares David

Rui Manuel Lopes Nunes

Jose Manuel Pereira Dias de Castro Lopes Joaquim Adelino Correia Ferreira Leite Moreira Raquel Ângela Silva Soares Lino

Fernando Manuel Mendes Falcão Dos Reis Francisco José Miranda Rodrigues Cruz José Paulo Alves Vieira de Andrade Jorge Manuel Silva Junqueira Polónia José Luís Dias Delgado

Isaura Ferreira Tavares

Fernando Carlos de Landér Schmitt Acácio Agostinho Gonçalves Rodrigues Maria De Fátima Moreira Martel João Tiago de Sousa Pinto Guimarães José Carlos Lemos Machado

José Carlos de Magalhães Silva Cardoso

Professores catedráticos jubilados e aposentados

Alexandre Alberto Guerra Sousa Pinto Álvaro Jeronimo Leal Machado de Aguiar António Albino Coelho Marques Abrantes Teixeira António Carlos de Freitas Ribeiro Saraiva António José Pacheco Palha

António Manuel Sampaio de Araújo Teixeira Belmiro dos Santos Patricio

Cândido Alves Hipólito Reis Carlos Rodrigo Magalhães Ramalhão Cassiano Pena de Abreu e Lima

Deolinda Maria Valente Alves Lima Teixeira Eduardo Jorge Cunha Rodrigues Pereira Fernando Tavarela Veloso

Francisco Fernando Rocha Gonçalves Isabel Maria Amorim Pereira Ramos Jorge Manuel Mergulhao Castro Tavares José Agostinho Marques Lopes Jose Carlos Neves da Cunha Areias José Eduardo Torres Eckenroth Guimarães

José Fernando Barros Castro Correia José Manuel Costa Mesquita Guimarães José Manuel Lopes Teixeira Amarante Levi Eugénio Ribeiro Guerra

Luís Alberto Martins Gomes de Almeida Manuel Alberto Coimbra Sobrinho Simões Manuel António Caldeira Pais Clemente Manuel Augusto Cardoso de Oliveira Manuel Machado Rodrigues Gomes Manuel Maria Paula Barbosa Maria Amelia Duarte Ferreira

Maria Da Conceição Fernandes Marques Magalhães Maria Isabel Amorim de Azevedo

Rui Manuel Almeida Mota Cardoso Rui Manuel Bento de Almeida Coelho Serafim Correia Pinto Guimarães

Valdemar Miguel Botelho dos Santos Cardoso Walter Friedrich Alfred Osswald

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Exmo. Senhor

Diretor da Faculdade de Medicina

PORTO

v.referência v.comunicação n.referência data

FOA.26. 4397-2021 2021.12.10

assunto

Provas de Doutoramento do Mestre Gustavo Marísio Bacelar da Silva

Informo V. Exª. que, por meu despacho de 2021.12.10, proferido no âmbito de delegação reitoral, nomeei o júri proposto para as provas de doutoramento requeridas pelo Mestre Gustavo Marísio Bacelar da Silva, com a seguinte constituição:

Presidente: Doutor Rui Manuel Lopes Nunes, Professor Catedrático da Faculdade de Medicina da Universidade do Porto.

Vogais:

- Doutora Victoria Jane Mabin, Professora Emérita da Victoria University of Wellington, New Zealand;

- Doutor Roy Stratton, Associate Professor da Nottingham Trent University, UK;

- Doutor Pedro Pereira Rodrigues, Professor Auxiliar da Faculdade de Medicina da Universidade do Porto;

- Doutor Fernando Manuel Ferreira Araújo, Professor Auxiliar Convidado da Faculdade de Medicina da Universidade do Porto;

- Doutor Francisco Nuno Rocha Gonçalves, Professor Auxiliar Convidado da Faculdade de Medicina da Universidade do Porto.

Nesta data, é notificado o candidato deste despacho.

Solicito a V. Exª. se digne providenciar a afixação em lugar público dessa Instituição a constituição deste júri, nos termos do nº 2 do artº 18º do Regulamento Geral dos Terceiros Ciclos de Estudos da Universidade do Porto.

Com os melhores cumprimentos,

O Vice-Reitor,

(Professor Doutor Fernando Manuel Augusto da Silva)

(2/2)/PV

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Acknowledgments

I dedicate this work and express my gratitude to all those who supported it. Particularly, Prof. Jim Cox, who started as my co-supervisor and TOC mentor, and became a very special friend after our weekly meetings.

To my supervisor, Pedro Rodrigues, who supported my TOC projects in Portugal long before the PhD program.

To my beloved wife, Daniele Bacelar, who always supported me, particularly during these challenging years. To our two lovely daughters, Sophia and Diana (they were born during this journey).

To my father-in-law, Edilson Menezes, who introduced me to the theory of constraints, and guided me at the beginning of my journey in 2005. To my mother-in-law, Virginia Menezes for her support in visiting my family every year on the other side of the Atlantic Ocean.

To my parents, Maria das Graças Bacelar da Silva and Ubirajara Paulo da Silva, for their unconditional love and guidance during my life.

To my family and friends in Brazil, in Portugal—particularly to three bright physicians/managers who embraced TOC: Maria Daniel Loureiro, José Miguel Diniz Oliveira, and Henrique Vasconcelos—and all over the world (particularly to my sister Carolina Bacelar, in Finland).

To Hospital São João obstetrics department, particularly those who supported the TOC Project, which includes doctors (Ana Paula Machado, Gabriela Namora, Marina Moucho, Mariana Guimarães), nurses (Cristina Martins, Carmo Prucha, Isabel), managers (Xavier Barreto), and admin assistants (Andreia Teixeira).

To God, the energy that fulfills the universe.

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List of abbreviations and acronyms

5FS Five focusing steps

AAMC Association of American Medical Colleges BM Buffer management

CQS Change question sequence CRT Current reality tree CTG Cardiotocography DBR Drum-Buffer-Rope DE Desirable effects ED Emergency department FRT Future reality tree GDP Gross domestic product

GREAT Guidelines for Research and Evaluation of Applications of TOC

I Investment

IO Intermediate objectives LOS Length of stay

NBR Negative branch reservation

NHS National health service (from the United Kingdom) OE Operating expense

PASS Provider appointment scheduling (and execution) system POOGI Processes of ongoing improvement

PRISMA Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement

PRT Prerequisite tree

T Throughput

TA Throughput accounting TOC Theory of constraints TP Thinking processes TPS Toyota Production System UDE Undesirable effects

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List of Figures

Figure 1. Flow of information through the different stages of this systematic review. 77

Figure 2. (a) Schedule design and (b) schedule execution before implementing TOC.

... 101

Figure 3. (a) Schedule design and (b) schedule execution after implementing TOC.

Patients in black color represent additional slots available after 4 weeks of TOC (a). A buffer located before the provider (strategic constraint) protects him from uncertainty and maintains patient flow (b). ... 107

Figure 4. Obstetrics outpatient schedule. (a) Real schedule from October 2019. (b) Schedule proposed after TOC analysis. ... 125

Figure 5. Patient flow since the primary care referral till finishing the obstetrics appointment. The estimate duration of each process based on interviews is in gray, while the number of days in red represents the time between processes. ... 128

Figure 6. What to change: CRT with long arrows (dotted lines) showing overview of EC and schedule design UDEs. Adapted from Cox & Boyd (2020). ... 137

Figure 7. What to change: CRT with long arrows (dotted lines) showing overview of EC and schedule execution UDEs. Adapted from Cox (2021a). ... 138

Figure 8. To what to change: FRT with long arrows showing overview of the EC primary injections and desirable effects of schedule design. Adapted from Cox & Boyd (2020).

... 139

Figure 9. To what to change: FRT with long arrows showing overview of the EC primary injections and desirable effects of schedule execution. Adapted from Cox (2021a). . 140

Figure 10. (a) Example of how to initially set up the board to play. (b) Implications of the patient-“batching” policy; notice some left-without-treatment patients (LWOT) on top

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of SUTURE ROOM and IMAGING EXAMS, while LAB EXAMS is at risk of receiving its second delayed care token. ... 158

Figure 11. Game score sheets, including all the three shifts in the standard mode. (a) Shift 1 is equivalent to Strategy I, (b) Shift 2 is equivalent to Strategy IV, and (c) Shift 3 is equivalent to Strategy V (see the description of each strategy in Statistical analysis).

... 161

Figure 12. Evaporating clouds illustrating a real-life healthcare example (a) and the game (b). An explanation about the cloud is at the bottom. ... 169

Figure 13. A chart illustrating the mean and the confidence interval (95% confidence level) of the number of patients discharged (total and per round), including regular discharge and referrals to external GPs, for all the different strategies. Strategies I, II, III, and VI—traditional; strategies IV and V—TOC. ... 177

Figure 14. (a) Example of how to set up the board to play. (b) Implications of the patient

“batching” policy; notice some left-without-treatment patients (LWOT) on the top of SUTURE ROOM and IMAGING EXAMS, and LAB EXAMS is at risk of receiving its second delayed care token. ... 223

Figure 15. Game score sheets of a play, including all three shifts in the standard mode.

Shift 1 is equivalent to Strategy I (traditional management + random), Shift 2 is equivalent to Strategy IV (TOC + BM), and Shift 3 is equivalent to Strategy V (TOC + BM + elevating capacity at the constraint). See the Table 8. ... 228

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List of Tables

Table 1. Search strategy including TOC terms and healthcare terms. ... 73

Table 2. Items of the evaluation system created to assess TOC implementations. ... 75

Table 3. Summary of participating studies. Includes publication source, the number of implementations, bias analysis (bias score), health service details (e.g., country, setting), results, and UDEs. ... 78

Table 4. Summary of groups of positive outcomes reported after implementing TOC.

... 80

Table 5. Summary of performance outcomes reported after implementing TOC in healthcare services. ... 82

Table 6. Methods and tools used to apply TOC in healthcare services. ... 88

Table 7. Summary of provider’s schedule before and after implementing TOC. ... 111

Table 8. Monte Carlo (MC) simulation results for the six strategies with their respective statistical analysis after 10,000 runs. Strategies I, II, and III represent variations of the traditional management philosophy with different priorities utilized for MEDICAL ASSESSMENT. Strategy IV represents the TOC approach of applying the first three steps of the 5FS and Buffer Management. Strategy V is similar to Strategy IV but includes step 4 “Elevate”. Strategy VI represents the traditional management approach after adding a new resource (die) at MEDICAL ASSESSMENT to improve the ED performance (as in Strategy V). ... 166

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Summary of Ph.D. outputs

Articles published

Bacelar-Silva, G. M., Cox, J. F., Baptista, H. R., & Rodrigues, P. P. (2021). Identifying and Addressing the Underlying Core Problems in Healthcare Environments: An Illustration Using an Emergency Department Game. International Journal of Environmental Research and Public Health, 18(19):10083. https://doi.org/10.3390/ijerph181910083. (Quartile 1, Web of Science).

Bacelar-Silva, G. M., Cox, J. F., & Rodrigues, P. P. (2022). Outcomes of managing healthcare services using the Theory of Constraints: A systematic review. Health Systems, 11(1), 1–16. https://doi.org/10.1080/20476965.2020.1813056. (Quartile 3, Web of Science).

Bacelar-Silva, G. M., Cox, J. F., & Rodrigues, P. (2022). Achieving rapid and significant results in healthcare services by using the theory of constraints. Health Systems.

https://doi.org/10.1080/20476965.2022.2115408. Quartile 3, Web of Science).

Articles under review

Cox, J. F., & Bacelar-Silva, G. M. (n.d.). A comparative analysis of the outpatient no-show problem: Data analytics and artificial intelligence approach versus the theory of constraints approach. Journal of the Operational Research Society, Submitted on 14-Jul- 2022. Status: Under 2nd external review. (Quartile 2, Web of Science).

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Articles to be submitted

Bacelar-Silva, G. M., Cox, J. F., & Rodrigues, P. P. (n.d.). Impact of implementing the theory of constraints in an obstetrics service.

Oral presentations at international conferences

Bacelar, G. (2019). How a doctor implemented TOC and improved his ophthalmology practice over 50% in a few weeks. TOCICO 2019 International Conference Proceedings. 2019 TOCICO International Conference: THE PRODUCTIVITY JOURNEY, Chicago, IL, USA.

https://www.tocico.org/page/2019Bacelar

Bacelar, G., & Cox, J. F. (2020). How to achieve breakthrough improvement in healthcare services by applying TOC principles and tools – Examples from all levels of care. TOCICO 2020 International Virtual Conference Proceedings. 18th Annual International Virtual Conference, Online. https://www.tocico.org/page/2020BacelarandCox

Master thesis co-supervision

Loureiro, M. D. D. de S. (2020). Identifying problems in the appointment scheduling system of a major Portuguese public hospital – Is there room for improvement? [Master Thesis]. Faculty of Medicine – University of Porto.

Dissemination activities for the scientific community

Bacelar, G. (2020, September). Improving the performance of healthcare services using the Theory of Constraints [1 ECTS]. Summer School (Faculty of Medicine—University of Porto), Porto, Portugal.

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Other contributions not directly associated with this research

Rêgo, S., Dutra-Medeiros, M., Bacelar-Silva, G. M., Borges, T., Soares, F., & Monteiro- Soares, M. (2021). Reliability of Classification by Ophthalmologists with Telescreening Fundus Images for Diabetic Retinopathy and Image Quality. Journal of Diabetes Science and Technology, 15(3), 710–712. https://doi.org/10.1177/19322968211000418

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Abstract

Medicine is evolving faster than ever, and healthcare is consuming an average of 10%

of a country’s gross domestic product (GDP). However, the increasing healthcare improvements and their rising costs do not reflect as better quality and timeliness of care delivered worldwide. Healthcare is in crisis. Long wait lists for appointments, emergency department crowding, shortage of hospital beds, and cancellation of elective surgeries are examples of chronic healthcare problems.

Many believe the shortage of medical providers is the cause of this timeliness problem.

Therefore, the most common solution suggested is to hire more doctors and nurses.

However, healthcare organizations hiring more doctors and nurses would increase costs above the already high current levels. It is truly a chronic conflict.

The solution to the chronic healthcare problems may come from a disruptive management philosophy that emerged late in the last century: the theory of constraints (TOC). TOC is a holistic management philosophy because it views every organization as a system composed of many interacting resources working together towards achieving the system goal. At least one resource limits the capacity of the whole system;

otherwise, its throughput would be infinite. This limiting resource is the constraint. It is the most important resource of any organization because it determines the performance of the whole system.

TOC's significant results in other areas support its investigation as an effective solution for the chronic healthcare problem. The primary objective of this thesis is to explore

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the potential of TOC as a solution to improve healthcare services performance and eliminate chronic healthcare problems.

Study #1 presents an overview and analysis of TOC implementations in healthcare services and their effects. Study #2 provides action research describing the implementation of TOC in a simple healthcare environment (a single provider). Study

#3 provides action research describing the implementation of TOC in a complex healthcare environment (multiple providers). Study #4 consists of designing a Socratic educational game to support TOC learning and implementations in healthcare environments.

These studies surfaced and defied the usually spoken assumption that healthcare services are already fully utilizing their constraints (e.g., physicians) as effectively as possible. This thesis demonstrated that it is possible to apply TOC in a few days and achieve significant benefits just by using existing resources. In addition, it provided evidence that applying TOC can significantly benefit healthcare delivery, improving both the volume and timeliness of care and, consequently, the quality of care.

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Resumo

A medicina está evoluindo numa velocidade sem precedentes ao mesmo tempo que os cuidados de saúde consomem em média 10% do produto interno bruto (PIB) de um país. No entanto, as melhorias na área de saúde e seus custos crescentes não refletem em um atendimento de melhor qualidade e mais atempado em todo o mundo. A saúde está em crise. Longas listas de espera por consultas, departamentos de emergência lotados, falta de leitos hospitalares e cancelamento de cirurgias eletivas são exemplos de problemas crónicos de saúde.

Muitos acreditam que a falta de profissionais de saúde é a causa desse problema.

Portanto, a solução mais comum sugerida é a contratação de mais médicos e enfermeiras. No entanto, caso as organizações de saúde contratassem mais médicos e enfermeiras, os seus custos aumentariam acima dos já elevados níveis atuais. É realmente um conflito crônico.

A solução para os problemas crónicos de saúde pode vir de uma filosofia de gestão disruptiva que surgiu no final do século passado: a teoria das restrições (TOC). A TOC é uma filosofia de gestão holística porque vê cada organização como um sistema como um conjunto de muitos recursos interativos que trabalham coordenados para atingir o objetivo do sistema. Sendo assim, ao menos um recurso limita a capacidade de todo o sistema; caso contrário, a sua produtividade seria infinita. Este recurso limitante é a restrição. É o recurso mais importante de qualquer organização porque determina o desempenho de todo o sistema.

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Os resultados significativos da TOC em outras áreas apoiam sua investigação como uma solução eficaz para o problema crónico de saúde. O objetivo principal desta tese é explorar o potencial da TOC como uma solução para melhorar o desempenho dos serviços de saúde, eliminando os seus problemas crônicos.

O Estudo #1 é um estudo de síntese que apresenta uma visão geral e uma análise das implementações de TOC em serviços de saúde e seus efeitos. O Estudo #2 é uma investigação-ação que descreve a implementação da TOC num ambiente de saúde simples (com um único médico). O Estudo #3 é uma investigação-ação que descreve a implementação da TOC num ambiente de saúde complexo (com vários médicos). O Estudo #4 consiste no projeto de um jogo educacional socrático desenvolvido para apoiar a aprendizagem e as implementações de TOC em ambientes de saúde.

Esses estudos destacaram e desafiaram a suposição comumente referida de que os serviços de saúde já utilizam totalmente as suas restrições (e.g., médicos) da forma mais eficaz possível. Esta tese demonstrou que é possível aplicar a TOC em poucos dias e obter benefícios significativos apenas com o uso de recursos existentes. Além disso, forneceu evidências de que a aplicação da TOC pode beneficiar significativamente a prestação de cuidados de saúde aumentando o volume de pacientes atendidos ao mesmo tempo que reduz o tempo de espera até o atendimento, o que por consequência melhora a qualidade do atendimento.

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Chapter 1. Introduction

I believe I have never been a typical physician. Since when I was in medical school, I was different. While my classmates discussed diseases and treatments, I discussed economics and management. They got enthusiastic about reading medical books, I read management and marketing. When they were choosing a residency, I decided on an MBA.

It was 2005, the last year of med school. At this moment, I had attended more management conferences than medical ones. I had read several management books and magazines. However, I was having difficulty understanding cost accounting. I could do the math, but I thought it just did not make any sense. In my mind, the fixed costs were too high, they represented a significant share of a product cost. What if a company’s sales ended up the month below its estimates? Those fixed costs would still be there! The estimated product profit would not be realistic. But who am I to question this sacred cow? Everybody uses cost accounting, there must be something out there that I am missing the point.

I shared those thoughts with just a few people. One Sunday evening, my future father- in-law showed me a book. He said he believed I would enjoy reading that book, but I should only read it if I was willing to change… forever. On that same day, I started reading that book unpretentiously. After a few pages, I notice he was right. I found the answer to my question about cost accounting (it leads us to bad decisions, indeed) and much more. I had to study for an exam scheduled for the end of the week and I was struggling to stop reading the book. It took me about 6 days to finish the book. I read it slowly, trying to absorb as much knowledge as I could. This book was The Goal. My

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father-in-law was right, it changed my life and the way I think. Now, I wanted to know more about the theory of constraints (TOC) and spread it to the world.

In the sequence, I read all Goldratt’s books I could find in Brazil: It’s Not Luck, Critical Chain, and The Haystack Syndrome, and other books, like Bússola Financeira. I visited a Federal University to access scientific articles about TOC and read all of them. It was like a curse to me, very few people knew what I was talking about. Even my MBA professors had no clue about TOC. I tested them by asking how to solve a simple problem, and they all failed. I was astonished. In 2006, I successfully used TOC to improve the scheduling process for appointments in the Public Family Clinic I worked.

In 2007, I still wanted more, so I imported books from Amazon: What Is This Thing Called Theory of Constraints and how Should it be Implemented, The Race, Thinking for a Change, and Focused Operations Management for Health Services Organizations.

This year, my future wife had just opened her private dental practice and was struggling with its operation. I supported her by applying and teaching TOC. Thanks to that, she adopted a completely new approach and achieved excellent results. At this point, I noticed I needed to record some details regarding the results achieved with TOC.

When I was about to finish my MBA, I started the ophthalmology residency, in 2007.

Only a couple of years later I would have the chance to use TOC in an interesting situation again. At the end of 2009, the Chief of Retina invited me to take his place performing some eye exams. At the beginning of 2010, I decided to use TOC to improve my practice in this environment, but I recorded some notes at this time expecting to publish an article. The implementation was a success, but I only would be able to dedicate appropriate time to write this article almost ten years later, as part of my Ph.D.

The details and the results of this case are available in Chapter 5.

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A few months later, I moved from Brazil to Portugal. In 2012, while I was finishing my master’s degree in medical informatics, a project of mine was awarded a scholarship to study how TOC could improve stock replenishment in a pharmacy. A few years later, in 2015, this project was a top 3 finalist in a national contest sponsored by the National Association of Pharmacies. The next year, I decided to enroll in a Ph.D. program to dedicate more time to TOC in healthcare.

The result of this last decision is this document. As much as I try, I believe this document cannot describe how hard this journey was. During this period, I had to convince people about TOC and overcome resistance to change countless times (not only in healthcare environments but also in academia). I got two lovely daughters and had sleepless nights taking care of them. I went through a pandemic that killed millions and forced people to stay at home (which may have not been the best decision (Herby et al., 2022) but it is beyond my objective to discuss it), my family and I got infected twice, and survived.

I have always been a person that defies old habits and rises questions to achieve better results. I am always pursuing improvement. TOC has helped me to better view, understand, and analyze the world under the concept of a system’s constraint and the thinking process. This Ph.D. journey has provided me with more experience in TOC and life. This thesis does not contain all the answers you may have, otherwise, it would never have been finished, but it is enough to fulfill its objective (described in Chapter 4). Hopefully, it will be an important step to eliminating, or significantly reducing, the healthcare chronic problems, which are described below.

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Healthcare chronic problems

Healthcare has evolved dramatically in the last century but managing it has become a conundrum. The 20th century was the stage of extremely relevant discoveries in medicine that affected health conditions all over the world, e.g., penicillin and the pacemaker. After those discoveries, we are living longer, and the population is growing.

However, these improvements led to a higher and rising demand for healthcare services.

As medicine evolves at an impressive rate so do its increasing costs. Healthcare consumes an average of 10% of a country’s gross domestic product (GDP), and its costs are rising faster than economies are growing (Halim, 2019). In the USA, this reached almost 18% of GDP in 2019 and it is projected to rise to 19.7% in 2028 according to a report on a federal government website (Centers for Medicare & Medicaid Services, 2020). Despite this unprecedented investment in healthcare, lack of capacity and timeliness are still problems affecting every country, even the wealthier (World Health Organization, 2010, 2019).

Long wait lists for appointments (Ryu & Lee, 2017), emergency departments crowding (Morley et al., 2018), shortage of hospital beds (Song & Ferris, 2018), and cancellation of elective surgeries (Al Talalwah & McIltrot, 2019) are just some examples of healthcare chronic problems.

An emergency department (ED) is a medical facility where emergency patients can receive timely and specialized care without prior appointments, but it is not the reality in many healthcare organizations. ED crowding is a critical healthcare issue worldwide, and it has been worsening over time. Crowding in the ED leads to long waits, which means longer lengths of stay, delayed care, poor treatment outcomes, and even death.

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Several studies have reported adverse consequences of ED crowding for both patients and staff (Higginson, 2012; Morley et al., 2018; Rasouli et al., 2019; Salway et al., 2017).

Merritt Hawkins published a study (2017) about indirect wait times (time from calling for an appointment till the designated time of the appointment). This study considered the first available slot for a new patient appointment in the US. The reported indirect wait times were incredibly high: primary care physicians had a 54-day wait, cardiology 32 days, dermatology 35 days, obstetrics/gynecology 23 days, and orthopedic surgery 15 days. These long wait times are not unique to the US system. In Brazil, results from a recent survey (Conselho Federal de Medicina, 2018) report the wait time as the most common cause of complaints for 61% of those who need surgery, 56% for those who need an imaging exam, and 55% of those who need an appointment in the Brazilian Unique Health System—Sistema Único de Saúde (SUS). This survey also identified that 45% of the participants had a 6-month wait for an appointment, an exam, or surgery and this percentage has increased since this number was 29% four years earlier.

The delay of care is a significant issue, a persistent and undesirable characteristic of current healthcare systems (Murray & Berwick, 2003; Ryu & Lee, 2017). When patients need to wait for medical assistance, serious consequences happen (Corley, 2016; Ryu

& Lee, 2017). Long waits before care delivery come with emotional consequences (e.g., anxiety, despair) and contribute to worsening clinical conditions, developing avoidable complications, and even death. There are also financial consequences, treating patients in more advanced conditions requires more specialized care resources, which are more costly.

Few studies have reported effective solutions to healthcare chronic problems.

Friedman and Pauly (2020) correctly stated that EDs must have some protective

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capacity to support statistical fluctuations. Nevertheless, like most proposed solutions, their solution involves paying more for more resources. The general belief is that the crowding problem is a consequence of a shortage of resources (e.g., beds, medical providers) (Han et al., 2007). However, before paying for more resources, an underlying assumption needs to be challenged: are currently available resources being utilized as effectively as possible? One management approach distinguishes itself by attaining protective capacity by better managing existing resources: the theory of constraints (TOC) (Bacelar-Silva et al., 2022; V. Mabin & Balderstone, 2003).

Disruptive management philosophies from the last century

Healthcare services are under pressure to deliver better healthcare outcomes to an increasing population, with higher quality care, in less time, and at a stable (or lower) cost. However, current management methods are not providing an effective solution to this chronic problem. Traditional solutions to address this problem often require investment to add more capacity to the system, but without a proper analysis to improve throughput using existing resources, it has the potential to make the situation even worse (Han et al., 2007).

Over the last century, three disruptive management philosophies emerged from manufacturing and considerably improved quality and reduced lead times. The successful results of these management philosophies in manufacturing stimulated their adoption in services. As a natural consequence, researchers also considered the adoption of these management philosophies in the healthcare environment to improve care delivery (C. S. Kim et al., 2006; Young, 2004). These three management philosophies are Lean, Six Sigma, and TOC.

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Lean originated from the Toyota Production System, created by Ohno, in the 1950s.

However, Womack, Jones, and Roos popularized the term Lean when they published their book “The machine that changed the world” (1990). Lean is a continuous improvement methodology that focuses on eliminating waste. Furthermore, Lean strives to provide value by improving productive flow.

In the 1980s, Motorola developed Six sigma based on the ideas of Deming. Still, it only became popular in the 1990s, in the sequence of the great results achieved by Jack Welch applying this management methodology in General Electric (Proudlove et al., 2008; Schroeder et al., 2008).

Authors report a reduction in the wait time, length of stay, costs, and increased capacity as the main outcomes of Lean and Six Sigma, including implementations in healthcare environments (Bhamu & Singh Sangwan, 2014; Blackmore & Kaplan, 2017; Čiarnienė

& Vienažindienė, 2012; C. S. Kim et al., 2006; Smith et al., 2020).

Theory of constraints overview

The Theory of Constraints (TOC) is one of those disruptive management philosophies that emerged late in the last century. Originally developed by Dr. Goldratt to solve production logistics issues, TOC today is considered a holistic management philosophy that views every organization as a system composed of many interacting resources.

These interdependent resources work together towards achieving the system goal;

however, at least one resource limits the capacity of the whole system; otherwise, its throughput would be infinite. This limiting resource is the constraint, and it is the most important resource of any organization since it determines the performance of the whole system (Goldratt, 1999b; Goldratt & Cox, 2004).

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Acknowledging the existence of a constraint introduces a whole new management paradigm. Instead of considering any new improvement idea anywhere as an improvement for the organization, improvement efforts should consider the constraint. If an organization was able to identify and increase throughput at its constraint, more effectively exploit the constraint, or better subordinate other resources to the constraint, then the organization would achieve more of its goal. For instance, if the organization loses a minute at the constraint, this is a minute lost for the whole organization. On the other hand, if any other resource loses a minute (as long as the constraint continues to work), it will not dramatically affect the organization because non-constraint resources can produce more than the constraint (protective capacity) and recover the flow (Goldratt & Cox, 2004). Furthermore, to ensure overall performance, the organization must plan and synchronize its productive flow according to the constraint and protect it from uncertainty, e.g., disruptions.

Since most healthcare academics and practitioners are unfamiliar with TOC, a more detailed description is provided in Chapter 3 for those interested to know more.

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Chapter 2. Objectives

Considering the concerning scenario of healthcare described in chapters 1 and 2, my motivation to always pursue improvement, and my medical and management background, the objective of this thesis is to explore the potential of TOC as a solution methodology to improve healthcare services performance and eliminate chronic healthcare problems.

As the means of achieving the objective of this thesis, I considered four secondary objectives, which include:

• Present an overview and analysis of TOC implementations in healthcare services and their effects—Study #1.

• Provide action research describing the implementation of TOC in a simple healthcare environment (a single provider)—Study #2.

• Provide action research describing the implementation of TOC in a complex healthcare environment (multiple providers)—Study #3.

• Design a Socratic educational game to support TOC learning and implementation in healthcare environments—Study #4.

Structure of this thesis

This thesis was written in "manuscript format," where the main chapters consist of standalone publishable articles between a general introduction and discussion. There is no separate chapter for methodology because this thesis consists of four different studies, and only two of them share similar methodologies. The lack of an overall methodology does not mean the studies have no methodology. The methodology of

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each study is available within their respective chapter. However, the similar methodology (action research) of those two studies mentioned earlier has a dedicated section on the subject within Chapter 3.

Each one of the four studies originated from a secondary objective and was written as a scientific article. Half of the studies are currently published articles (studies #1 and

#4), one is still under minor review (Study #2), and one is about to be submitted (Study

#3). Since each study originated an article including other authors, at the end of each study chapter there is a section describing the contributions made by each author.

Chapter 3 (State of the Art) provides the necessary details about the healthcare chronic problems, the disruptive management philosophies that emerged in the last century, and their application in healthcare, as well as a dedicated section on TOC. However, Chapter 3 does not intend to provide an exhaustive description and analysis of the topics mentioned above, not even TOC and its tools. Otherwise, I would assume the risk of losing focus (the objective provided in the first paragraph of this section) because each of those topics can become an article or even a book. Rather, Chapter 3 seeks to provide sufficient knowledge for those readers who are unaware of the healthcare chronic problems, the management approaches used as solutions, and TOC. Those readers who feel the need to deepen their knowledge on a particular subject can always read the references cited.

Chapter 4 (Study #1) provides a 10,000-foot view of the use of TOC in healthcare services. This chapter is a systematic literature review that included both academic and practitioners’ input to provide an overview and analysis of the empirical use of TOC in healthcare worldwide.

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Chapter 5 (Study #2) and Chapter 6 (Study #3) are two action research studies that provide empirical knowledge and an in-depth view of TOC implementations in simple (single provider) and complex (multiple providers) healthcare environments.

Chapter 7 (Study #4) introduces a board game I designed to Socratically support TOC learning and implementation, particularly in healthcare environments. Moreover, the article that originated this chapter also validates the board game dynamics.

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Chapter 3. State of the art

Healthcare chronic problems

Timeliness is a critical measure in healthcare. Patients may suffer from a lack of timeliness derived from a couple of reasons: indirect wait time and direct wait time.

When a patient calls to schedule an appointment, the time from that moment till the date of the appointment is the indirect wait time. This indirect wait time is usually measured in days, weeks, and many times months.

Long indirect wait times have psychological consequences (e.g., stress, desperation) and contribute to worsening medical conditions, even to death (Corley, 2016; Ryu &

Lee, 2017). Patients may also have recovered (or in some settings, died) and no longer need the appointment. Treating patients having more advanced conditions also has financial consequences, as it requires more specialized care resources, which increases the cost.

Even when patients have an appointment scheduled, they still may suffer from the lack of timeliness in the treatment process. After arriving at a healthcare service, patients may have to wait long past their designated appointment time to be seen by the provider (this is called direct wait time). This time is usually measured in minutes but sometimes in hours.

Long direct wait times cause patient frustration and may cause late arrivals or the patient not showing up for future appointments. If patients expect a long direct wait for the provider, then many of them do not arrive on time—they arrive earlier (expecting

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the doctor may see them in case of another patient does not show up) or later (to make better use of their time other than be in a waiting room).

Many believe that the lack of timeliness in healthcare delivery is a consequence of a shortage of medical providers. A recent report released by the Association of American Medical Colleges (AAMC) provides a projection of physician shortages of between 54,000 and 139,000 by 2033 in the US (IHS Markit Ltd., 2020). This is comprised of shortages of primary care physicians (the gateway to the healthcare system in many countries) of between 21,400 and 55,200 physicians and in specialty care of between 33,700 and 86,700 physicians. Additionally, the AAMC study reports that other sources (unnamed) suggest that patients receive only 55% of the recommended chronic/preventive services. Authors claim that this shortfall between provided services and recommended services might be due to the time constraints faced by providers when attending to their patients. Additionally, the demand for physicians would increase between 74,000 to 145,000 additional physicians if healthcare access was extended to underserved populations. Similar statistics are available in many other counties. The World Health Organization (2016) estimates a shortage of almost 18 million healthcare workers by 2030, especially in low-income and lower-middle- income countries. These estimates do not even consider an unusual situation, such as the COVID-19 pandemic crisis.

The most common (yet infeasible) solution suggested for this chronic problem is to hire more doctors and nurses, as supported by the timeliness and shortage statistics discussed previously. Based on the statistics, most managers consider this lack of provider resources as the core problem in healthcare environments. It seems to be logical: if we have more doctors, we can treat more patients. However, healthcare

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investment and increase their costs above their already too high current levels. It is truly a chronic conflict.

These statistics seem to reflect a significant shortage of physicians but there is an unspoken assumption in this argument. The unspoken assumption is that currently physicians are utilized as effectively as possible. Is this reality? Or can we schedule physician appointments and execute physician schedules more effectively and thus create far more capacity without increasing expenses significantly? To schedule additional patient appointments without taxing the physician and clinical staff, one must perform two tasks:

• Properly manage providers’ schedules (avoid no-shows, empty slots, and late cancellations, and simultaneously make available slots for those acute patients that cannot wait days for an appointment).

• Streamline the execution of the patient-provider process (how the patient is treated—from arriving to departing the provider’s practice).

Notice there is a connection between scheduling and execution. For instance, if one reduces the no-show rate significantly, eliminates the no-appointment scheduled rate, and does not improve execution, then the provider will be overloaded, and patient wait times will be longer. On the other hand, if one improves execution and does not change the schedule design and scheduling, then the provider will be frequently idle (and will get accustomed to being idle). Therefore, both scheduling and execution must be linked and synchronized.

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Disruptive management philosophies applied to healthcare

The pressure to deliver better healthcare outcomes at a stable (or lower) cost combined with the successful results in manufacturing provided by TOC, Lean, and Six Sigma made researchers naturally consider the adoption of those disruptive management philosophies to improve care delivery.

The most famous approach is Lean Thinking. In the 1950s, Taiichi Ohno developed the Toyota Production System (TPS), a systematic approach for identifying and eliminating waste and improving flow (J. P. Womack & Jones, 2003). This was the tipping point that made Toyota succeed and become the world’s number one auto manufacturer (Goldratt, 2009; McNaughton, 2017; J. P. Womack & Jones, 2003). By the 1990s Womack and Jones developed Lean Thinking, which is essentially the TPS principles and methods. Lean can be applied to production and services as a systematic approach to improve quality and efficiency (J. P. Womack & Jones, 2003).

Since the early 2000s, the investigation of Lean in health care is rising, attracting many researchers worldwide (Mazzocato et al., 2010; Young, 2004). The Institute for Healthcare Improvement, in the United States, the NHS, and the Institution for Innovation and Improvement, in the United Kingdom, advocated the use of Lean. These organizations recognized Lean as a possible solution to promote better healthcare delivery, maximize value, and eliminate waste (Jones & Mitchell, 2006; Miller &

Womack, 2005; Westwood et al., 2007).

Six sigma is a management philosophy that emerged in the 1980s and focuses on improving processes using a statistical approach. Therefore, the use of data is paramount for this approach's success because its definition of excellence is based on

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a mathematical concept, the standard deviation (Proudlove et al., 2008; Schroeder et al., 2008; Shirazi & Pintelon, 2013; Stanton et al., 2014).

The first articles considering the adoption of Lean in healthcare started to be published in 2001 and increased since then (Henrique & Godinho Filho, 2020). Soon after, practitioners and academics started to consider combining Lean and Six Sigma (George, 2002; Hines et al., 2004). Despite the positive outcomes usually reported, many authors highlight the fact that Lean case studies still need to provide more concrete evidence regarding the standardization of the implementation process, benefits provided (e.g., in terms of quality, costs, and productivity), and sustainability (Bhamu & Singh Sangwan, 2014; Čiarnienė & Vienažindienė, 2012; Shirazi & Pintelon, 2013). The same issues are true for Lean in healthcare (Chiarini & Bracci, 2013; Hallam

& Contreras, 2018; Shirazi & Pintelon, 2013; Stanton et al., 2014). Moreover, Henrique

& Godinho Filho (2020) recently reported in their systematic literature review the need for more empirical articles to provide evidence on the effectiveness and sustainability of Lean and Six Sigma in healthcare.

Another disruptive management philosophy developed by the late 1970s may provide the direction of the solution for this chronic healthcare conflict. The theory of constraints (TOC) considers all organizations as a system made of many interdependent resources that work collectively to achieve the organization’s goal.

Since there is no such organization capable of providing infinite throughput, at least one resource will limit the productivity of the whole system. This resource that limits the system is the constraint, it is the most important/valuable resource of any organization because it determines its overall performance (Goldratt & Cox, 2004).

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Theory of constraints

In contrast to both the traditional management philosophy and Lean (reduce waste) philosophy’s emphasis on cost reduction everywhere, TOC focuses on achieving the organization's goal (e.g., for healthcare being an effective organization in providing healthcare). Its primary focus is on increasing throughput (the number of properly treated patients), although maintaining or reducing operating expenses are very common consequences. TOC also strives for a systems perspective of the environment examining all stakeholders’ perspectives in searching for a win-win solution to satisfy the different stakeholders (the objective is not to compromise on goal achievement and provide a win-win solution for all stakeholders) (Ronen, 2005).

Dissemination of TOC

The adoption of TOC in business environments started in manufacturing and has spread to logistics, distribution, project management, and sales and marketing (Goldratt, 2010; Ronen, 2005). In 1998, Mabin and Balderstone (2003) conducted a literature review to assess the outcomes provided by TOC applications. This study identified 77 different companies across many different purposes (for-profit, not-for- profit, and government), industries, and sizes, including giant multinational corporations (e.g., Boeing and GM), military organizations (e.g., US Air Force), and even a small-town bakery. Their analysis of reported changes presented positive results, though many companies achieved their results with only partial implementations. See the median outcomes below:

• Lead-time reduction of 75%.

• Cycle-times reduction of 66%.

• Due-date-performance improvement of 50%.

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• Inventory levels reduction by 50%.

• Revenue increase of 39% (excluding one outlier, a 600% increase at Lucent Technologies achieved within one year).

These significant results support the investigation of TOC as an effective solution for the chronic healthcare problem. However, the application of TOC still has few case studies published in refereed academic journals (V. Mabin & Mirzaei, 2016; Ronen, 2005), particularly in healthcare. Since academic papers do not entirely reflect the adoption of TOC in healthcare yet, answers to this subject may be covered in grey literature.

Implementing TOC

TOC has many tools available to help organizations achieve their goals, but one can expect to use only some of them during a TOC implementation. In TOC, the improvement efforts focus on the system’s constraint. The system’s constraint is the leverage point for managing (functions include planning, scheduling, executing, and controlling) the system, the reallocation of tasks, and the definition of priorities.

Therefore, the non-constraint resources must operate synchronized, moving parts in support of the constraint. This approach contrasts with traditional management, in which all resources work as individual parts trying to perform tasks as efficiently as possible based on their local priorities to achieve their local goals.

The organization's goal is achieved by implementing three processes of ongoing improvement (POOGI) to align, schedule, and execute the organization's processes to achieve its goal. The three POOGIs are (1) the five focusing steps (5FS) (Cox et al., 2012;

Goldratt & Cox, 2004); (2) buffer management (Cox et al., 2012; Goldratt & Fox, 1986);

and (3) the change question sequence (CQS) (Cox et al., 2012; Goldratt, 1994).

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The three POOGIs are used in TOC healthcare environments to achieve high utilization of the constraint and seamless flow of patients through the system. The 5FS are instrumental in redefining how the parts of a system interact in performing these organizational functions. If someone encounters difficulty within any stage of the 5FS, Goldratt recommended using the CQS to provide the solution. Buffer management is a POOGI that protects the system’s throughput against uncertainty and provides feedback to maintain the workflow and where to improve. These tools are described in more detail below and simple applications in healthcare are provided within the next chapters.

The goal, measures, and necessary conditions

The first step in a TOC implementation is to define the system’s boundaries. The system can be an organization, a specific part of an organization (as described in this article), or even a set of organizations (e.g., a supply chain).

Next, one objectively defines the system’s goal, which is the overall purpose of the organization(s). Only the owners of the organization can determine its goal. However, defining the goal is not enough since any organization has other stakeholders that may influence the achievement of the goal (Goldratt, 2006, Chapter 2). Therefore, one must identify these stakeholders and determine their imposed necessary conditions. As an example, the employees are a group of stakeholders that might compromise the organization’s goal if the organization does not provide both job security and satisfactory wages. If the organization violates the employees’ necessary conditions, they can jeopardize the achievement of the organization’s goal by going on strike, for instance; however, they still do not have the right to determine the organization’s goal

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(Goldratt, 2006, Chapter 2). All stakeholders impose necessary conditions on how the organizations achieve their goals.

Before one starts to improve the system, there is still the need to determine the system’s global measurements. These measures will allow those who play a role in the system functions to know whether their daily decisions are moving the organization closer to its goal or not. For that end, Goldratt developed a management accounting method based on the existence and value of a constraint (Goldratt, 1990a). This new management accounting method is called throughput accounting (TA) and its global measurements are (Corbett, 2005; Goldratt, 2006, Chapters 4–6; Goldratt & Cox, 2004):

• Throughput (T)—the rate at which the system generates "goal units", e.g., money, patients.

• Investment (I)—All the money currently tied up in the system, e.g., equipment, and raw materials.

• Operating expense (OE)—all the money the organization spends on generating

"goal units", e.g., salaries, utilities, taxes.

Five focusing steps

The five focusing steps (5FS) is a systematic process to provide focus and significantly improve performance using limited resources. This POOGI is typically adopted to improve the performance of physical constraints (usually equipment, but can also be a lack of people, a skill set, or physical space, and material shortages) (Cox et al., 2012, p.

57; Goldratt & Cox, 2004; Goldratt & Fox, 1986; Vargas et al., 2017). The 5FS are:

(1) IDENTIFY the system’s constraint(s).

(2) Decide how to EXPLOIT the system’s constraint(s).

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(3) SUBORDINATE everything else to the above decision.

(4) ELEVATE the system’s constraint(s).

(5) WARNING! If in the previous steps a constraint has been broken, go back to step 1, but do not allow INERTIA to cause a system's constraint.

A brief overview of each step is provided below. In the next chapters, there are detailed descriptions of actions taken based on these steps. Before applying these steps, one must first determine the organization’s goal and necessary conditions placed on the organization's operations and have an appropriate measurement system. Given these organization parameters, the five steps define how an organization can manage effectively within this environment.

Step 1. IDENTIFY the system’s constraint(s).

This is an obvious and essential first step, if managers do not know where the constraint is, they are guessing. To identify the current constraint, one must observe and ask questions. What is the resource that limits the system to achieve more units of its goal?

What resource, if only the system had more of it, would enable the system to increase its throughput? What is the resource that most frequently accumulates the largest queue of work in process (measured in hours of work for that resource)? The answer to these questions may provide the location of the constraint (Cox & Spencer, 1997;

Scheinkopf, 1999; Woeppel, 2000). However, it is not rare to have piles of work everywhere in traditionally run organizations. When a resource is incorrectly identified as the constraint, the real constraint will show up as soon as the implementation starts (Woeppel, 2000). And what if the system is capable of producing more than its demand?

That means the constraint is outside the system, it is in the market (Goldratt, 1990a).

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Identifying the constraint also means deciding the most appropriate resource for the organization’s constraint. This decision must consider the resource scarcity, i.e., how difficult it is to increase its capacity in the long term (Cox & Spencer, 1997, Chapter 3;

Goldratt, 1990b, 2006, Chapter 11; Goldratt & Cox, 2004). This resource is a strategic constraint (Cox et al., 2012). In most cases, the initial (or current) constraint is not the strategic constraint (the leverage point of the organization), and actions must be taken to move to the strategic constraint (Ronen & Pass, 2021).

Step 2. Decide how to EXPLOIT the system’s constraint(s).

Once the system’s strategic constraint is determined, it is time to make better use of it.

Remember, the constraint determines the system’s performance. Thus, this is the organization’s leverage point, the one that will provide the highest impact on the global measurements. But before spending money on the constraint, one must assure the constraint’s current capacity is not wasted (Cox & Spencer, 1997, Chapter 3; Goldratt, 1990b, 2006, Chapter 11; Goldratt & Cox, 2004).

Although this seems to be obvious, it is not what usually happens. What is the most common solution to the lack of capacity and timeliness in healthcare? Hire more doctors and nurses. Suppose the doctors are the constraint, is the practice effectively utilizing its existing doctors? Are these doctors performing only high-skill-level tasks or are they wasting time doing things they should not (e.g., scheduling patients, completing forms for governments and insurance companies)?

Before moving immediately to step 4 (elevate the system’s constraint e.g., hiring more doctors), the organization must effectively exploit its constraint(s). That means the constraint should not start processing patients until all the items required to complete the task are available. This collection of items for a given task is called complete kit

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(Leshno & Ronen, 2001), and may include medical records, medical tools, staff, etc.

Starting medical care only with a complete kit is a simple and effective method to better exploit a constraint and avoid waste and performance impairment.

Step 3. SUBORDINATE everything else to the above decision.

To effectively exploit the constraint, the non-constraint resources must align their work with the exploitation decisions. This is often the most difficult step to implement because it requires that all the other resources work accordingly to support the constraint instead of performing their own tasks as efficiently as possible (Cox &

Spencer, 1997, Chapter 3; Goldratt, 1990b, 2006, Chapter 11; Goldratt & Cox, 2004).

That means almost all (particularly clinical personnel) job descriptions must be reviewed and rewritten based on supporting the high constraint utilization and improving patient flow (Cox, 2021a; Cox & Boyd, 2020). To support this step, there are two TOC methods, drum-buffer-rope (DBR) (or Simplified Drum-Buffer-Rope, also known as S-DBR) and buffer management. DBR (or S-DBR) will support scheduling and managing the operation (Cox et al., 2012, p. 46; Schragenheim & Dettmer, 2000b).

Buffer management supports both the planning and execution of operations, offering protection for the constraint, indicating potential risks, and where management should dedicate attention to (Cox et al., 2012, p. 11;14). This section provides more details about DBR and buffer management further.

Step 4. ELEVATE the system’s constraint(s).

The implementation of the previous three steps usually reveals enormous hidden capacity. But suppose the system’s constraint is already working at its limit after implementing the first three steps and the system still needs to increase its throughput.

Then, this is the time to consider an investment or an increase in operating expenses.

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In this case, the payback is often within a few months because there is a validated and high enough demand to justify the investment.

Step 5. WARNING! If in the previous steps a constraint has been broken, go back to step 1, but do not allow INERTIA to cause a system's constraint.

The last step is a reminder that one cannot lay itself to rest on past glories. If the managers were successful in implementing the previous steps, at some point the constraint was broken. When it happens, the system must restart the focusing process and identify the new constraint. Restarting the 5FS is the key to achieving a process of ongoing improvement (POOGI). However, constantly changing a constraint may result in a massive effort, requiring the organization to go through the whole process again (e.g., realigning the system focus by changing all the workers’ tasks and priorities, scheduling and execution rules, etc.). For this reason, moving the strategic constraint is seldom the desired strategy. Thus, it is important to determine, organize, and manage the system according to the strategic constraint mentioned above as soon as possible. Elevating the strategic constraint is accomplished as a known growth strategy.

Change question sequence

The change question sequence (CQS) provides a systems analysis of an environment using the thinking processes (TP) tools. It is particularly useful when a policy, procedure, rule, measure, or behavior is blocking the improvement process of the 5FS (Dettmer, 2007; Goldratt, 1990b, 1994; Scheinkopf, 1999). In these cases, the TP and the CQS are quite useful in identifying and addressing these types of problems.

The CQS provides a gap analysis of system characteristics, an analysis of the current system (and functional) problems (called undesirable effects, UDEs in TOC terminology) to determine the core problem(s), development of a holistic win-win

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solution to the system and functional UDEs and the system core problem(s), construction of an effective implementation plan, and procedures for measuring and sustaining system results (Dettmer, 2007; Goldratt, 1990b, 1994; S. Kim et al., 2008; V.

Mabin & Davies, 2010; Scheinkopf, 1999).

The TP consists of a set of logic diagrams to support answering these questions. One can use these diagrams in combination to address the CQS or independently. Kim, Mabin, and Davies (2008) provide a comprehensive review of the implementation of TOC TP in several environments and include healthcare examples. Furthermore, one can use the TOC TP combined with other tools and methods, such as TRIZ—literally translated from Russian as “theory of inventive problem solving”—(S. Kim et al., 2008), CIMO–context, intervention, mechanism, and outcome—(Cox & Boyd, 2020), and system dynamics (V. J. Mabin et al., 2006) methodologies.

The CQS includes the questions below (followed by a brief description of other TP tools found useful in healthcare environments).

1. Why change?

This first step consists of a gap analysis. One starts by determining the gap between where the organization is and where it should be with respect to its goal. A list of the current system and functional UDEs versus how we would like it to be (desirable effects—DEs, in TOC terminology) should be used to help determine the answer to this question (Cox et al., 2012, p. 25;134; S. Kim et al., 2008). Dettmer (2007, 2011) introduced a new diagram to support this step, the goal tree.

A study of implementing theory of constraints healthcare services

D