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Performance Improvement in Health Care Organizations
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DOI: 10.1561/0200000039
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Performance Improvement in Health Care Organizations
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Performance Improvement in Health Care Organizations
Hummy Song University of Pennsylvania
Anita Tucker Boston University
Boston — Delft
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Contents
1 Introduction 3 Framework for Performance Improvement in Health Care Organi-
zations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 An Overview of the U.S. Health Care System . . . . . . . . . . 5 The Need for a Health Care-Specific Framework . . . . . . . . . 11 Introduction to Key Operations Management Concepts in Perfor-
mance Improvement . . . . . . . . . . . . . . . . . . . . . 15 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2 Model of Transformational Performance Improvement 24 Overview of the Model . . . . . . . . . . . . . . . . . . . . . . 25 Other Models of Improvement in Health Care . . . . . . . . . . 26 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3 Determining and Communicating a System-Level Goal 35 Developing System-Level Goals . . . . . . . . . . . . . . . . . . 37 Operations Management Literature Related to System-Level
Goals: Operational Focus . . . . . . . . . . . . . . . . . . 39 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
4 Developing and Using System-Level Measures of Performance 45 Considerations in Developing Performance Measures . . . . . . . 48
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Operations Management Literature Related to Performance Mea- sures: Health Information Technology . . . . . . . . . . . . 50
Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
5 Understanding and Managing Interdependencies 59 Considerations in Understanding and Managing Interdependencies 59 Operations Management Literature Related to Interdependence:
Patient Flow . . . . . . . . . . . . . . . . . . . . . . . . . 64 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
6 Selecting a Portfolio of Projects Aligned with System-Level Goals 70 Aligning Projects with Objectives in Health Care Organizations . 70 Operations Management Literature Related to a Portfolio of
Improvement Projects: Appointment Scheduling . . . . . . 72 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
7 Creating an Engine for Improvement 78 Four Aspects of Creating an Improvement Engine . . . . . . . . 79 Operations Management Literature Related to Total Quality
Management, Lean, and Six Sigma . . . . . . . . . . . . . 81 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
8 Implementing, Spreading, and Sustaining Improvements 95 Facilitating the Spread of Best Practices . . . . . . . . . . . . . 96 Operations Management Literature Related to Spread and Sus-
tainability . . . . . . . . . . . . . . . . . . . . . . . . . . 96 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
9 Common Barriers to Successful Performance Improvement 102 Barriers Related to the External Context . . . . . . . . . . . . . 103 Barriers Within the Organization . . . . . . . . . . . . . . . . . 106 Barriers Related to the Implementation Process . . . . . . . . . 106 Barriers Related to the Improvement Project . . . . . . . . . . . 107 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
10 Future Directions in Research on Performance Improvement
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in Health Care Organizations 108 Opportunities for Research Related to the Impact of External
Environment On Performance Improvement . . . . . . . . 110 Opportunities for Research Related to Performance Improvement
Within Organizations . . . . . . . . . . . . . . . . . . . . 117 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
11 Conclusion 121
Acknowledgements 123
References 124
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Performance Improvement in Health Care Organizations Hummy Song1 and Anita Tucker2
1University of Pennsylvania, USA [email protected] 2Boston University, USA [email protected]
ABSTRACT Performance improvement is an important organizational capa- bility that is essential for health care organizations to achieve excellence on the three components of the Triple Aim: patient experience, health, and cost. In this monograph, we present a framework for performance improvement in health care organiza- tions: the Model of Transformational Performance Improvement. This model takes a system-level approach to performance im- provement and comprises six key components: (1) determining and communicating a system-level goal; (2) developing and us- ing system-level performance measures; (3) understanding and managing interdependencies; (4) selecting a portfolio of projects aligned with system-level goals; (5) creating an organizational engine for improvement; and (6) implementing, spreading, and sustaining improvements. In addition to presenting this model, we review the operations management literature on performance improvement with a special focus on operations management tools and principles that may help with successful implementation of these six components. Though work has already been done in these areas, much remains unknown and many opportunities for future research exist. This monograph seeks to inform the research of operations management scholars and to equip clinicians and health care leaders with techniques that may be leveraged to improve performance in health care organizations.
Hummy Song and Anita Tucker (2016), “Performance Improvement in Health Care Organizations”, Foundations and Trends R© in Technology, Information and Operations Management: Vol. 9, No. 3-4, pp 153–309. DOI: 10.1561/0200000039.
The full text is available at http://dx.doi.org/10.1561/0200000039
List of Acronyms
ACO Accountable care organization AMI Acute myocardial infarction CCHMC Cincinnati Children’s Hospital Medical Center CMS Centers for Medicare and Medicaid Services CPOE Computerized provider order entry DMAIC Define, Measure, Analyze, Improve, and Control ED Emergency department EHR Electronic health record FDA Food and Drug Administration HCAHPS Hospital Consumer Assessment of Healthcare Providers and Systems HITECH Health Information Technology for Economic and Clinical Health ICU Intensive care unit IHI Institute for Healthcare Improvement IT Information technology JCAHO Joint Commission on Accreditation of Health Care Organizations NCQA National Committee for Quality Assurance PACU Post-anesthesia care unit PDSA Plan-Do-Study-Act RFID Radio-frequency identification devices STEMI ST-segment elevation myocardial infarction TPI Transformational Performance Improvement TQM Total Quality Management
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1 Introduction
Managers of health care organizations are responsible for achieving the “triple aim”, which is simultaneous excellence on patient experience, health, and cost (Berwick et al., 2008). Reaching the triple aim requires that organizations improve their patients’ experience, improve clinical outcomes for individual patients as well as for a population of patients, and reduce the per capita costs of health care. Rising cost pressures coupled with increased public reporting of clinical outcomes and patient experiences serve to increase competitive pressures on health care orga- nizations (Chou et al., 2014, Moody, 2014, O’Neill, 2015). Therefore, managers must learn how to improve performance across one or more of the three goals of the triple aim.
Performance improvement is one approach that organizations can use to learn how processes can be altered to yield higher quality care, better patient experience, and lower costs. We define performance improve- ment as a structured approach that uses repeated cycles of hypothesis testing to discover how processes can be modified so that they produce output that meets the performance target. In this monograph, we are particularly interested in transformational performance improvement— a change effort that crosses organizational boundaries with the goal of
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4 Introduction
dramatically improving performance. Transformational improvement often requires fundamental alterations to the underlying business model and processes used to deliver service, such that staff and customers will shape new ways of working together that are more efficient and yield better outcomes.
Successful execution of a transformational performance improvement initiative is challenging. Less successful improvement initiatives may focus on local (e.g., unit-level) performance, overlooking opportunities to improve organizational-level performance. They may also create unanticipated negative effects on downstream departments. Thus, it is important to develop and utilize a comprehensive system-level approach to transformational performance improvement in health care organi- zations that actively seeks to overcome common barriers to making change in complex organizations.
Framework for Performance Improvement in Health Care Organiza- tions
In this monograph, we review the literature on performance improve- ment in health care organizations. Based on prior studies, we present a framework that synthesizes the factors associated with successful trans- formational performance improvement. The model, which we call the Model of Transformational Performance Improvement (TPI), comprises six key components. We describe the model in greater detail in section 2 and list the components below.
1. Determining and communicating a system-level goal
2. Developing and using system-level measures of performance
3. Understanding and managing interdependencies
4. Selecting a portfolio of projects aligned with system-level goals
5. Creating an engine for improvement
6. Implementing, spreading, and sustaining improvements
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An Overview of the U.S. Health Care System 5
This monograph is intended for two audiences. First, it informs operations management scholars who conduct research on or teach about improvement in health care organizations. It provides a framework that can be useful for teaching about the subject, as well as a summary of the literature that can aid future research projects. Second, the monograph provides clinicians and health care leaders with knowledge about operations management techniques that can be leveraged to improve performance.
The remainder of the monograph is organized as follows. In this section, we first provide an overview of the U.S. health care system. We then discuss the need for a health care specific framework for improvement. Finally, we provide a brief introduction of key opera- tions management concepts relevant for performance improvement. In section 2, we present the Model of Transformational Performance Im- provement. We also review other models for improvement and compare them to our model. In sections 3-8, we present each of the six key components of the model, respectively. We draw on case studies and empirical research to explain the components in more depth and to provide examples of their implementation. We also link each component to relevant operations management literature streams. The literature discussed includes operational focus, health information technology (IT), patient flow, appointment scheduling, Total Quality Management (TQM), Lean, and Six Sigma. In section 9, we discuss common barriers to performance improvement that we hope can be avoided by applying the framework and the operations management principles outlined in this monograph. In sections 10-11, we provide ideas for future research and conclude.
An Overview of the U.S. Health Care System
In this section, we present a brief overview of the U.S. health care system and define key terms and concepts that will be discussed throughout this monograph. Specifically, we describe types of health care organizations, financing, and regulation. Though we frame our discussions within the U.S. health care system, many of the operations management-based
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6 Introduction
lessons of this monograph are applicable to performance improvement in health care organizations in other countries as well.
Health care in the U.S. is provided by several types of organizations. The two most predominant types of health care delivery organizations are hospitals and physician practices, though there are also nursing facilities, rural health clinics, and others (National Center for Health Statistics, 2016). Of the 4,900 general hospitals in the U.S., approxi- mately 60% are non-profit, 20% are for-profit, and 20% are state or local government-owned (Henry J. Kaiser Family Foundation, 2015). The state or local government-owned hospitals comprise much of the public delivery system that forms the safety net for uninsured individ- uals and those without the means to pay for care. Hospitals provide services to patients in inpatient units such as medical units, surgical units, and obstetrics units, but also in outpatient units such as emer- gency departments (EDs) and hospital-based primary care practices. Altogether, hospital care accounts for nearly 40% of personal health care expenditures, which we can see in Figure 1.1 (National Center for Health Statistics, 2016).
Physician practices account for the other predominant site of health care delivery. Figure 1.1 shows that physician and other clinical services account for nearly 25% of personal health care expenditures (National Center for Health Statistics, 2016). As of 2007, the majority of physicians work in group practices, making coordination of care an important aspect of work not only across practices, but also within practices. The number of single-specialty medical groups is increasing, and nearly 60% of the 900,000 professionally active physicians in the U.S. are specialist physicians. As a result, with few integrated care delivery systems across specialties and across the continuum of care, fragmentation of care delivery is a significant and pervasive issue (Burns and Pauly, 2012).
When it comes to financing this health care system, there are three main sources of funding: private insurance plans, government insurance programs, and the patients themselves (see Figure 1.2). Financing is an important and influential factor in thinking about performance improve- ment in health care organizations, because health care organizations are affected by insurance policies and reimbursement systems. Changes
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An Overview of the U.S. Health Care System 7
11
Figure 1.1. Distribution of Personal Health Expenditures by Type of Service, 2014 Note: Other personal health care includes dental and other professional health services, durable medical equipment, and other nondurable medical products. Source: Calculations using 2014 National Health Expenditure Accounts data from Centers for Medicare & Medicaid Services, Office of the Actuary, National Health Statistics Group, National Health Expenditure Accounts, National Health Expenditures.
When it comes to financing this health care system, there are three main sources of funding:
private insurance plans, government insurance programs, and the patients themselves (see Figure
1.2). Financing is an important and influential factor in thinking about performance improvement
in health care organizations, because health care organizations are affected by insurance policies
and reimbursement systems. Changes and reforms of these policies shape the financial incentives
of health care organizations, which in turn have important implications for health care markets,
access to care, and performance improvement initiatives.
Figure 1.1: Distribution of Personal Health Expenditures by Type of Service, 2014.
Note: Other personal health care includes dental and other professional health services, durable medical equipment, and other nondurable medical products.
Source: Calculations using 2014 National Health Expenditure Accounts data from Centers for Medicare & Medicaid Services, Office of the Actuary, National Health Statistics Group, National Health Expenditure Accounts, National Health Expenditures.
and reforms of these policies shape the financial incentives of health care organizations, which in turn have important implications for health care markets, access to care, and performance improvement initiatives.
Private insurance is purchased from insurance companies, which can be either for-profit or not-for-profit. Most private insurance is pur- chased by employers and provided to employees as a benefit (employer- sponsored insurance); this is a preferable source of insurance because employers can effectively pool risks in a way that individuals cannot. Nevertheless, individuals may also purchase private health insurance themselves (private non-group insurance). As of 2013, approximately half of the total U.S. population had employer-sponsored insurance and
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8 Introduction
12
Figure 1.2. Sources of Payment for Health Care, 2012
Source: Calculations using 2012 Medical Expenditure Panel Survey data from Agency for Healthcare Research and Quality, Center for Financing, Access, and Cost Trends.
Private insurance is purchased from insurance companies, which can be either for-profit or
not-for-profit. Most private insurance is purchased by employers and provided to employees as a
benefit (employer-sponsored insurance); this is a preferable source of insurance because
employers can effectively pool risks in a way that individuals cannot. Nevertheless, individuals
may also purchase private health insurance themselves (private non-group insurance). As of
2013, approximately half of the total U.S. population had employer-sponsored insurance and 6%
of the population had private non-group insurance (Henry J. Kaiser Family Foundation 2015).
Among the government insurance programs, the two largest programs are Medicare and
Medicaid. Medicare funds health care for the elderly (aged 65 and above), the permanently
disabled with a work history, and individuals with end-stage renal disease. It is comprised of four
components: Part A (primarily hospital service coverage; automatic), Part B (outpatient service
coverage, including physicians’ fees and ED visits; optional with a monthly premium), Part C
Figure 1.2: Sources of Payment for Health Care, 2012.
Source: Calculations using 2012 Medical Expenditure Panel Survey data from Agency for Healthcare Research and Quality, Center for Financing, Access, and Cost Trends.
6% of the population had private non-group insurance (Henry J. Kaiser Family Foundation, 2015).
Among the government insurance programs, the two largest pro- grams are Medicare and Medicaid. Medicare funds health care for the elderly (aged 65 and above), the permanently disabled with a work his- tory, and individuals with end-stage renal disease. It is comprised of four components: Part A (primarily hospital service coverage; automatic), Part B (outpatient service coverage, including physicians’ fees and ED visits; optional with a monthly premium), Part C (Medicare Advantage, or alternative plans including managed care and fee-for-service care plans; optional with a monthly premium), and Part D (prescription drug coverage; optional with a monthly premium). As of 2013, Medi-
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An Overview of the U.S. Health Care System 9
care beneficiaries constituted 15% of the total U.S. population and Medicare spending exceeded 20% of national health spending (Henry J. Kaiser Family Foundation, 2015). Medicare is federally funded and largely financed by payroll taxes of current workers and by the optional premiums. It has a relatively narrow scope of coverage and involves deductibles, coinsurance, and coverage ceilings. Almost all hospitals and physicians participate in Medicare.
On the other hand, Medicaid is a program funded jointly by the federal and state governments for low-income families and/or individuals with disabilities. As of 2013, 16% of the total U.S. population had Medicaid, and Medicaid spending constituted 15% of national health spending (Henry J. Kaiser Family Foundation, 2015). The criteria for eligibility are complex with both income and categorical criteria that vary from state to state. The services covered also vary by state, though they are generally broader than those covered by Medicare and involve limited or no cost sharing for enrollees. That said, access to care is a key issue for Medicaid beneficiaries, due to the historically low reimbursement rates to hospitals and physicians that results in a shortage in the supply of health care providers who are willing to accept Medicaid patients (Cunningham and Nichols, 2005).
Health care is a heavily regulated industry, both in terms of how the services are delivered and in terms of the various products and tech- nologies utilized in its delivery (Field, 2007). Table 1.1 summarizes the primary regulatory functions of some of the key health care regulatory agencies and organizations in the United States. The regulations and policies that surround the industry significantly influence health care delivery and often determine what a health care organization can and cannot do. Often times, this means that transformational performance improvement efforts are subject to external regulations and policies. For example, in the United States, health care organizations are required to meet certain standards and guidelines in order to be accredited by bodies including the Joint Commission on Accreditation of Health Care Organizations (JCAHO) and the National Committee for Quality Assurance (NCQA) (Iglehart, 1996). In most states, accreditation is a regulatory requirement, without which health care organizations cannot
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10 Introduction
Table 1.1: Key Health Care Regulatory Agencies and Organizations.
Type Agency or Organization Primary Regulatory Function
Food and Drug Administration (FDA)
Oversees the safety of food, drugs, vaccines, biopharmaceuticals, medical devices, and cosmetics
Environmental Protection Agency (EPA)
Regulates the discharge of environmental pollutants
Federal Occupational Safety and Health Administration (OSHA)
Regulates workplace safety and health
United States Department of Agriculture (USDA)
Regulates food safety
Boards of medicine Regulates the practice of medicine through the licensure, registration, and certification of physicians
State Boards of other health professions
Regulates the practice of medicine through the licensure, registration, and certification of allied health professionals
Accreditation Council on Graduate Medical Education (ACGME)
Accredits post-graduate medical training programs
Joint Commission on Accreditation of Healthcare Organizations (JCAHO)
Accredits and certifies hospitals and other kinds of health care facilities
Private
Medical specialty societies Certifies physicians as qualified to practice in medical specialties
National Committee on Quality Assurance (NCQA)
Accredits individual physicians, health plans, and medical groups
Note: Adapted from Field (2007).
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The Need for a Health Care-Specific Framework 11
operate. To stay accredited by JCAHO and NCQA, organizations may need to continually adopt changes to abide by standards and guidelines set externally. This may influence the portfolio of projects being exe- cuted by an organization and the set of performance measures that are being tracked. Another regulatory body in the United States is the U.S. Food and Drug Administration (FDA), which regulates and supervises pharmaceutical drugs, medical devices, vaccines, and other products in- tended for human use. In delivering care, health care organizations must stay abreast of and adapt to changes in the status of various medical products and new innovations. This may affect the way an organization decides to implement, spread, and sustain previous improvements.
For a more detailed description of the U.S. health care system, we refer the reader to Jonas and Kovner’s Health Care Delivery in the United States (Kovner and Knickman, 2008) and the brief by National Center for Health Statistics (2016). For a more detailed review of the relationship between health insurance policies, reimbursement systems, and health service providers, we refer the reader to the Handbook of Health Economics (Culyer and Newhouse, 2000).
The Need for a Health Care-Specific Framework
Performance improvement has been studied in industries outside of health care, such as manufacturing (Ahire et al., 1995). Although there are differences between the health care context and other industries, prior studies nonetheless provide helpful insights for improvement projects undertaken in health care organizations (Boyer et al., 2012). Several practices are linked with successful performance improvement efforts. These include strong support for improvement from top management; a focus on customer needs; positive, cooperative relationships with suppliers; workforce management; information about quality issues; thoughtful product design; and process management (Kaynak, 2003, Meyer and Collier, 2001, Zu et al., 2008). Some of these practices, such as top management support, provide the infrastructure necessary to launch and sustain improvement projects (Flynn et al., 1995, Kaynak, 2003, Meyer and Collier, 2001, Samson and Terziovski, 1999, Sousa and Voss, 2002). Additional infrastructure is also important, such as
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12 Introduction
performance measurement systems, which provides guidance about what processes within an organization are inefficient, and on what competitive dimensions (e.g., quality, cost, flexibility, delivery) the organization is falling behind the competition (Neely et al., 1995). Gaps in performance measures often lead managers to set challenging goals, which serve to engage staff members and spur them to invest in improving performance (Linderman et al., 2003, Zu et al., 2008). Vogus et al. (2010) describe a model where the infrastructure of an enabling culture supports the enacting practices, which are the problem-solving behaviors that lead to improved outcomes (Boyer et al., 2012). Enabling practices of performance improvement include statistical process control and process flow management (Sousa and Voss, 2002). These in turn are associated with improved quality performance and business performance (Anderson et al., 1995, Flynn et al., 1995).
Key findings from quality improvement studies in manufacturing are that quality is a multi-dimensional outcome and that there is no universal set of improvement practices that lead to high performance. Instead, organizations should tailor their quality practices to achieve high performance on their strategic dimensions of performance (Sousa and Voss, 2002). Although many of the lessons learned in studies of other industries can be applied to health care organizations, health care warrants its own coverage of this topic (Asch et al., 2014, Field et al., 2014, Meyer and Collier, 1998).
There are special conditions present in health care delivery that dis- tinguish it from manufacturing and other similar industries. Successful performance improvement requires attention to these conditions, which we outline in Table 1.2.
First, individual patients with similar underlying medical conditions can have very different biological responses to the same treatment. As a result, there can be greater variability and uncertainty in health care operations than in manufacturing (Bradley et al., 2010a). For example, patients have differently-shaped gallbladders, which requires surgeons to adapt how they remove an infected gallbladder (Gawande, 2007). As a result of uncertainty in exactly what medical care will be needed for a patient, and how she will respond to that treatment, health care
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The Need for a Health Care-Specific Framework 13
Table 1.2: Characteristics that Distinguish Health Care Organizations from Other Industries.
Characteristic Description Implication for Performance Improvement Efforts
Variation in biological response to treatment by patient
Individual patients with similar underlying medical conditions can have very different biological responses to the same clinical treatment.
There is an inherent level of flexibility that will be required of clinicians to appropriately respond to individual patient differences.
Patient’s integral role in the service delivery process
The patient needs to willingly cooperate with the plan of care to achieve the best quality outcomes.
Processes need to be designed to include communication with the patient, and they must be flexible enough to accommodate patient preferences.
Complex relationship between quality improvement and financial performance of health care organization
The goal of health care provision is to maximize health and minimize patient visits. Therefore, improving quality will not necessarily result in high volume of service provision for health care organizations. In health care provision, the person receiving the service (i.e., the patient) is often not paying for the majority of the cost. This leads to a situation in which the “customer” (e.g., insurance company) is not always willing to pay more for higher quality of care. A patient care episode often requires services from various entities (e.g., physicians and the hospital), making it complicated to implement broader changes that affect multiple parties.
To prevent obstacles to the improvement effort, champions of the improvement effort need to make a business case for quality, find funding to support the efforts, and determine how to appropriately allocate costs and benefits of these efforts.
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14 Introduction
providers must maintain the ability to be flexible with a patient’s care plan, even if they are using standardized processes (Gawande, 2009a). Consequently, improvement efforts need to maintain some flexibility in the prescribed health care processes.
Second, the product—health—is the joint output of both the provi- der(s) and the patient. In other words, patients are not only involved in the production process, but integral to it. Without the cooperation and participation of the patient, it is difficult to achieve a high quality outcome (i.e., good health). This necessitates effective communication between the provider and the patient, which enables individual patient preferences to be taken into consideration when designing her care plan. Consequently, performance improvement efforts are more likely to be successful if the patient is an integral part of the improvement team (Uhlig and Raboin, 2015).
Third, the link between the quality and efficiency of services delivered and the profitability to the organization is less direct for health care organizations than it is for other service industries. The lack of a direct financial reward for improving quality and efficiency of care has been raised as an impediment to performance improvement in health care (Gawande, 2010). This is because, unlike restaurants, hotels, and other experience-based services, the goal for many patients and their health care organizations is to minimize repeat visits (Kocher and Adashi, 2011). As a result, high quality service delivery is not as clearly linked with profitability-driving repeat visits for health care organizations as it is for other service businesses depicted in the Service-Profit Chain (Heskett et al., 1997). In addition, a unique feature of health care is that service is typically at least partially paid for by a third party—such as government agencies, insurance companies, and employers—rather than being paid solely by the customer. The three-party financial relationship weakens the link between customer satisfaction with service quality and willingness to pay higher prices for a higher quality experience (Gawande, 2010, Toussaint et al., 2010). Furthermore, health care delivery for a patient is not conducted by a single entity—even if that care takes place within the same health care organization. Different providers working in the facility may be reimbursed separately (e.g., the physician
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Introduction to Key Operations Management Concepts in... 15
versus the hospital, ED versus the surgical department) (Harris, 1977). The financial silos impede the ability to work across boundaries to improve efficiency and quality (Burns and Pauly, 2012, Pham et al., 2014). Additional funding mechanisms may be needed to embark on ambitious performance improvement programs (Gawande, 2010).
Thus, there is a need to study performance improvement in the context of health care organizations. Performance improvement projects in health care would need to maintain flexibility and responsiveness to individual patient needs, involve patients in the effort, consider the impact of these efforts on patient experience, and find alternate funding mechanisms.
Introduction to Key Operations Management Concepts in Perfor- mance Improvement
Many operations management concepts provide relevant insights for improving performance in health care organizations. In this section, we introduce four that pertain closely to our model: performance frontiers, queuing theory, capacity management, and the theory of swift, even flow. Below, we define each concept and explicitly state the link between the concept and a component of our model. We also provide a brief overview of the operations management literature on the concept, with particular emphasis on implications for transformational performance improvement in health care organizations. We focus on the literature most closely related to health care settings, but we also draw on other relevant research. We provide an overview of the mapping of operations management topics to the model components and monograph sections in Table 1.3.
Performance Frontiers
The first two components of our model—setting a system-level goal and creating system-level measurements to gauge progress—relate to the concept of performance frontiers. These topics are covered in sections 3 and 4, respectively.
There are multiple dimensions on which an organization can com- pete, including cost, quality, responsiveness (e.g., short waiting time
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16 Introduction
Table 1.3: Mapping of Operations Management Concepts on the Components of the Model of Transformational Improvement.
Component of the Model of Transformational Improvement
Operations Management Concepts
Section
1. Determining and communicating a system-level goal
2. Developing and using system-level measurements of performance
Performance frontiers - Operational focus
Section 3.2: Operational focus Section 4.2: Health information technology
3. Understanding and managing in- terdependencies
Queuing theory - Pooling
Section 5.2: Patient flow
4. Selecting a portfolio of improvement projects aligned with system-level goals
Capacity management - Appointment scheduling
Section 6.2: Appointment scheduling
5. Creating an engine for improvement
Theory of swift, even flow - Standardization - Experimentation
Section 7.2: Total Quality Management, Lean, and Six Sigma
6. Implementing, spreading, and sustaining improvements
Theory of swift, even flow - Standardization - Experimentation
Section 8.2.1: Organization-related factors that aid spread and sustainability Section 8.2.2: Implementation process-related factors that aid spread and sustainability
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Introduction to Key Operations Management Concepts in... 17
for service) and flexibility (Boyer and Lewis, 2002). Achieving excellent performance on one of the four different strategic goals requires aligning the facility’s structural elements—such as technology, capacity and layout—and infrastructure elements—such as human resource policies and quality programs—to achieve that goal (Boyer and Lewis, 2002, Butler et al., 1996). Skinner’s seminal article from his experience with over 50 manufacturing plants finds that the best performing manufactur- ing plants produce a narrow range of products that enables alignment of the production system with the strategic objective (Skinner, 1974). Such alignment is called “operational focus”.
As a result of the need for operational focus, production facilities that have industry-best performance on one dimension (e.g., low cost) face tradeoffs if they want to improve performance on different dimensions (e.g., delivery speed) (Boyer and Lewis, 2002). To illustrate, a facility that has optimized its processes and product portfolio to have the lowest costs in the industry would likely have to increase its inventory costs to reduce its delivery time.
Graphically, as shown in Figure 1.3, the tradeoff can be depicted by a performance frontier that represents the explicit competitive position of each company on these two dimensions. For example, the x-axis measures performance on inventory costs, while the y-axis measures performance on quality. Values farthest from the origin represent better performance. Best-in-industry companies lie on the outermost curve, which is called the performance frontier. Assuming that the performance frontier stays the same, improving performance on one dimension will result in decreased performance on the second dimension (Hayes and Pisano, 2009, Schmenner and Swink, 1998). However, companies that are not best-in-industry on either dimension (e.g., Company A or Company B in Figure 1.3) can adopt existing best practices and improve their performance without decreasing performance on the other dimension (Boyer and Lewis, 2002). Finally, technological and process innovations— such as Lean manufacturing—can push the industry’s performance frontier outward because tradeoffs are broken (Hayes and Pisano, 2009, Schmenner and Swink, 1998).
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18 Introduction
The operations management concepts of performance frontiers and operational focus are directly relevant to performance improvement in health care organizations. A focused organization that is on the performance frontier can improve its performance via new innovations that break tradeoffs. Organizations not on the performance frontier can improve along multiple dimensions by adopting existing technology or processes used by leading organizations (Chandrasekaran et al., 2012, Senot et al., 2016).
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homogenous patients should also reduce complexity (Clark and Huckman 2012) and result in
faster rates of individual and organizational learning (KC and Terwiesch 2011).
Figure 1.3. Performance Frontier
Despite the arguments for the benefit of focused hospitals, empirical studies find that
specialized hospitals have better performance not because of operational excellence, but because
they treat healthier patients than do general hospitals (KC and Terwiesch 2011). Specialized
hospitals also improve care in their region not through their own performance, but by inducing
competition among the non-specialty hospitals in their region (Barro et al. 2006). However, there
does appear to be a benefit of focus at the unit level (Huckman and Zinner 2008, KC and
Terwiesch 2011) if there is “related” diversification across units within the hospital. Related
diversification is the capability of treating a medical condition that often accompanies the
primary diagnosis, such cardiovascular disease (primary focus) and kidney disease (related
Figure 1.3: Performance Frontier.
The impact of operational focus on performance has been studied in health care. Specialty hospitals, which treat a narrow set of patient conditions—such as cardiac care—are analogous to a focused factory (Barro et al., 2006). In theory, a focused hospital should have better clinical outcomes and lower costs of treatment because it can hone its processes and equipment to meet its patient population’s specific needs.
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Introduction to Key Operations Management Concepts in... 19
The classic case study of Shouldice Hospital (Heskett, 1983) describes how focusing only on hernia patients enables the center to design its facility and procedures to achieve shorter length of stay and better patient outcomes. The higher volume of homogenous patients should also reduce complexity (Clark and Huckman, 2012) and result in faster rates of individual and organizational learning (KC and Terwiesch, 2011).
Despite the arguments for the benefit of focused hospitals, empirical studies find that specialized hospitals have better performance not be- cause of operational excellence, but because they treat healthier patients than do general hospitals (KC and Terwiesch, 2011). Specialized hospi- tals also improve care in their region not through their own performance, but by inducing competition among the non-specialty hospitals in their region (Barro et al., 2006). However, there does appear to be a benefit of focus at the unit level (Huckman and Zinner, 2008, KC and Terwiesch, 2011) if there is “related” diversification across units within the hospital. Related diversification is the capability of treating a medical condition that often accompanies the primary diagnosis, such cardiovascular dis- ease (primary focus) and kidney disease (related diversification) (Clark and Huckman, 2012). This literature suggests that managers seeking to use the concept of focus to improve their organization’s performance should ensure that the facility has the capability to treat not only the primary targeted medical condition, such as cardiovascular care, but also the most common comorbidities associated with that targeted condition.
Queuing Theory
Queuing theory uses mathematical formulas to approximate the average waiting time for service, given average system parameters, such as arrival rates, processing times, and utilization. Queuing theory can inform efforts to reduce waiting for services and to improve patient flow (see section 5 for a more detailed discussion). Patients often progress through multiple departments, such as the ED to the medical unit, during their health care treatment. Therefore, improving patient flow involves the third component of our model: paying attention to the interdependence
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20 Introduction
among various departments affected by the improvement project. Queuing theorists have investigated how to improve patient flow in
hospitals. One of the most significant lessons from this body of literature is that managerial decisions, such as day-to-day variation in the number of elective surgery patients, pose a bigger problem for patient flow than does the random nature of health care, such as variation in arrival rates of emergency patients (McManus et al., 2003). Studies have shown that patient flow can be significantly improved by leveling the flow of elective surgery patients to provide a more constant number of patients arriving to inpatient units across the seven days of the week (Haraden and Resar, 2004, Ryckman et al., 2009).
22
diversification) (Clark and Huckman 2012). This literature suggests that managers seeking to use
the concept of focus to improve their organization’s performance should ensure that the facility
has the capability to treat not only the primary targeted medical condition, such as cardiovascular
care, but also the most common comorbidities associated with that targeted condition.
1.4.2 Queuing Theory
Queuing theory uses mathematical formulas to approximate the average waiting time for
service, given average system parameters, such as arrival rates, processing times, and utilization.
Queuing theory can inform efforts to reduce waiting for services and to improve patient flow
(see section 5.2 for a more detailed discussion). Patients often progress through multiple
departments, such as the ED to the medical unit, during their health care treatment. Therefore,
improving patient flow involves the third component of our model: paying attention to the
interdependence among various departments affected by the improvement project.
Queuing theorists have investigated how to improve patient flow in hospitals. One of the
most significant lessons from this body of literature is that managerial decisions, such as day-to-
day variation in the number of elective surgery patients, pose a bigger problem for patient flow
than does the random nature of health care, such as variation in arrival rates of emergency
patients (McManus et al. 2003). Studies have shown that patient flow can be significantly
improved by leveling the flow of elective surgery patients to provide a more constant number of
patients arriving to inpatient units across the seven days of the week (Haraden and Resar 2004,
Ryckman et al. 2009).
Figure 1.4. Pooled versus Dedicated Queue System Figure 1.4: Pooled versus Dedicated Queue System.
Pooling similar types of patients (see Figure 1.4) can reduce waiting times by better utilizing available capacity (Best et al., 2015, Saghafian et al., 2012). However, pooling patients is not always beneficial. Patient types with low arrival rates and priority levels may end up with long waits if they are pooled with high priority, high arrival rate patients who have long average lengths of stay (Green and Nguyen, 2001). Pooling can also decrease individual clinicians’ motivation to keep waiting times short. One study found that the average length of stay for ED patients is shorter if incoming patients are assigned upon arrival to a specific physician rather than waiting in a (virtual) pooled queue (Song et al., 2015).
Another key lesson from the queuing literature is that high levels
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Introduction to Key Operations Management Concepts in... 21
of hospital occupancy result in longer length of stay (Berry Jaeker and Tucker, 2016, KC and Terwiesch, 2012, Kim et al., 2015), higher readmission of patients who are discharged early to make room for incoming patients (Anderson et al., 2012), and worse patient outcomes (Kuntz et al., 2015). A recommendation that emerges from this literature is the importance of using state-dependent criteria for admitting patients to intensive care units (ICUs), particularly when occupancy approaches the threshold where performance worsens (Kim et al., 2015).
Capacity Management
The fourth component of our model, having a portfolio of improvement projects, relates to the operations management concept of capacity management because many different interventions can be implemented to better align demand and capacity of a health care organization (Gupta and Potthoff, 2016, Jack and Powers, 2009). Specifically, section 6 reviews the appointment scheduling literature, which is a subfield of capacity management.
Capacity is a measure of an organization’s processing ability, en- abled by its prior investments in a variety of processing resources (van Mieghem, 2003). The amounts and locations of various resources dictate how much and what type of services an organization can offer (van Mieghem, 2003). Uncertainty in quantity, timing, type of future demand, and the lag time in creating additional production resources results in mismatches between supply and demand. For health care organizations, the consequences of mismatches are especially severe. If there is not enough capacity, patients may face long delays in receiving necessary treatment, while excess capacity is expensive for the organization (Jack and Powers, 2009).
At least three comprehensive reviews of the literature on demand and capacity management in health care have been conducted. Smith- Daniels et al. (1988) review papers published between 1970 and 1986. Jack and Powers (2009) pick up from that study and review the literature from 1986 to 2006. Gupta and Potthoff (2016) highlight the operational challenges, state of practice, current operations management approaches, and future research opportunities with regards to capacity management
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22 Introduction
in the operating room, ED, and inpatient settings of a hospital. Demand management identifies causes of demand uncertainty, with
the goal of removing or managing the sources of demand uncertainty (Jack and Powers, 2009). The demand management-related topics cov- ered by the first two reviews include demand management strategies such as predicting demand using mathematical models and simulation, health management organizations, vertical and horizontal integration, and multi-hospital systems (Jack and Powers, 2009, Smith-Daniels et al., 1988). Capacity management is the efficient use of internal resources to meet fluctuating demand for services (Gupta and Potthoff, 2016, Jack and Powers, 2009, Smith-Daniels et al., 1988). Topics addressed by the review articles include capacity management strategies, work- force management, utilization, subcontracting, and IT. Key capacity management tactics are having flexible resources (Jack and Powers, 2004) and effective scheduling policies, such as same-day scheduling (Murray and Berwick, 2003). Performance topics include quality of care outcomes, efficiency, and financial performance (Jack and Powers, 2009, Smith-Daniels et al., 1988).
Theory of Swift, Even Flow
The theory of swift, even flow is relevant for the last two components of our model: creating an organizational engine for change (section 7) and implementing, spreading, and sustaining the changes (section 8). The theory of swift, even flow states that “the more swift and even the flow of materials through a process, the more productive that pro- cess is” (Schmenner and Swink, 1998, p. 102). The flow of materials through a process can be improved by reducing non-value added work, removing impediments to flow, and reducing variability in processing time and arrival rates (Schmenner and Swink, 1998). This philosophy of management is the foundation for performance improvement programs such as TQM and Lean manufacturing. Both programs utilize frontline employees in efforts to reduce non-value added activities. Doing so first requires training them on scientific methods for problem solving. Ex- perimentation is a key component of these methods. Once an improved method for working is discovered, processes are standardized on the
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Summary 23
new method. Despite debate about the applicability of the concepts of swift, even flow to health care (Arndt and Bigelow, 1995), many studies have demonstrated the ability of the principles to improve qual- ity of care and efficiency (Douglas and Fredendall, 2004, Furman and Caplan, 2007, Jimmerson et al., 2005, Shortell et al., 1995). Leadership support and physician involvement are two components of successful implementations in hospital settings (Carman et al., 1996, Douglas and Fredendall, 2004, Harrison et al., 2016).
Summary
In this section, we presented a brief description of the U.S. health care system and outlined conditions that warrant specific study of perfor- mance improvement in health care organizations. We also introduced four operations management concepts that inform improvement efforts in health care settings. In the next section, we outline our Model of Transformational Performance Improvement and review other commonly used models of improvement to highlight similarities and differences between our model and others.
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References
Adams, R., P. Warner, B. Hubbard, and T. Goulding. 2004. “Decreas- ing turnaround time between general surgery cases: A Six Sigma initiative”. J. Nurs. Adm. 34(3): 140–148.
Adler, P. S. and S. W. Kwon. 2013. “The mutation of professionalism as a contested diffusion process: Clinical guidelines as carriers of institutional change in medicine”. J. Manag. Stud. 50(5): 930–962.
Adler, P. S., P. Riley, S. W. Kwon, J. Signer, B. Lee, and R. Satrasala. 2003. “Performance improvement capability: Keys to accelerating performance improvement in hospitals”. Calif. Manage Rev. 45(2): 12–33.
Adler-Milstein, J. and D. W. Bates. 2010. “Paperless healthcare: Progress and challenges of an IT-enabled healthcare system”. Bus. Horiz. 53(2): 119–130.
Ahire, S. L., R. Landeros, and D. Y. Golhar. 1995. “Total quality management: A literature review and an agenda for future research”. Prod. Oper. Manag. 4(3): 277–306.
Aiman–Smith, L. and S. G. Green. 2002. “Implementing new manufac- turing technology: The related effects of technology characteristics and learning activities”. Acad. Manag. J. 45(2): 421–430.
Anand, G., D. Chhajed, and L. Delfin. 2012a. “Job autonomy, trust in leadership, and continuous improvement: An empirical study in health care”. Oper. Manag. Res. 5(3-4): 70–80.
124
The full text is available at http://dx.doi.org/10.1561/0200000039
References 125
Anand, G., J. Gray, and E. Siemsen. 2012b. “Decay, shock, and renewal: Operational routines and process entropy in the pharmaceutical industry”. Organ. Sci. 23(6): 1700–1716.
Anand, G., P. T. Ward, M. V. Tatikonda, and D. A. Schilling. 2009. “Dy- namic capabilities through continuous improvement infrastructure”. J. Oper. Manag. 27(6): 444–461.
Anderson, D., B. Golden, W. Jank, and E. Wasil. 2012. “The impact of hospital utilization on patient readmission rate”. Health Care Manag. Sci. 15(1): 29–36.
Anderson, J. C., M. Rungtusanatham, and R. G. Schroeder. 1994. “A theory of quality management underlying the Deming management method”. Acad. Manag. Rev. 19(3): 472–509.
Anderson, J. C., M. Rungtusanatham, R. G. Schroeder, and S. Devaraj. 1995. “A path analytic model of a theory of quality management underlying the Deming management method: Preliminary empirical findings”. Decis. Sci. 26(5): 637–658.
Angst, C. M., S. Devaraj, C. C. Queenan, and B. Greenwood. 2011. “Per- formance effects related to the sequence of integration of healthcare technologies”. Prod Oper. Manag. 20(3): 319–333.
Arndt, M. and B. Bigelow. 1995. “The implementation of total quality management in hospitals: How good is the fit?” Health Care Manage Rev. 20(4): 7–14.
Asch, D. A., C. Terwiesch, K. B. Mahoney, and R. Rosin. 2014. “In- sourcing health care innovation”. N. Engl. J. Med. 370(19): 1775– 1777.
Ayanian, J. Z., T. D. Sequist, A. M. Zaslavsky, and R. S. Johannes. 2008. “Physician reminders to promote surveillance colonoscopy for colorectal adenomas: A randomized controlled trial”. J. Gen. Intern. Med. 23(6): 762–767.
Azevedo, S. G. and J. J. Ferreira. 2010. “Radio frequency identification: A case study of healthcare organisations”. Int. J. Secur. Networks. 5(2/3): 147–155.
The full text is available at http://dx.doi.org/10.1561/0200000039
126 References
Baicker, K., S. L. Taubman, H. L. Allen, M. Bernstein, J. H. Gruber, J. P. Newhouse, E. C. Schneider, B. J. Wright, A. M. Zaslavsky, and A. N. Finkelstein. 2013. “The Oregon experiment – Effects of Medicaid on clinical outcomes”. N. Engl. J. Med. 368(18): 1713– 1722.
Balasubramanian, H., S. Biehl, L. Dai, and A. Muriel. 2014. “Dynamic allocation of same-day requests in multi-physician primary care practices in the presence of prescheduled appointments”. Health Care Manag. Sci. 17(1): 31–48.
Balasubramanian, H., A. Muriel, A. Ozen, L. Wang, and X. Gao. 2013. “Capacity allocation and flexibility in primary care”. In: Handbook of Healthcare Operations Management. Methods Applications. Ed. by B. T. Denton. 1–25.
Balasubramanian, H., A. Muriel, and L. Wang. 2012. “The impact of provider flexibility and capacity allocation on the performance of primary care practices”. Flex. Serv. Manuf. J. 24(4): 422–447.
Baldrige National Quality Program. 2005. Health Care Criteria for Performance Excellence. Gaithersburg, MD.
Barro, J. R., R. S. Huckman, and D. P. Kessler. 2006. “The effects of cardiac specialty hospitals on the cost and quality of medical care”. J. Health Econ. 25(4): 702–721.
Bartlett, J. 2014. “Boston Children’s Hospital asthma initiative receives Medicaid endorsement”. Bost. Bus. J. September 25, 2014.
Bates, D. W., L. L. Leape, D. J. Cullen, N. Laird, L. A. Petersen, J. M. Teich, E. Burdick, M. Hickey, S. Kleefield, B. Shea, M. V. Vliet, and D. L. Seger. 1998. “Effect of computerized physician order entry and a team intervention on prevention of serious medication errors”. JAMA. 280(15): 1311–1316.
Bekker, R. and P. M. Koeleman. 2011. “Scheduling admissions and reducing variability in bed demand”. Health Care Manag. Sci. 14(3): 237–249.
Bell, L. M., R. Grundmeier, R. Localio, J. Zorc, A. G. Fiks, X. Zhang, T. B. Stephens, M. Swietlik, and J. P. Guevara. 2010. “Electronic health record-based decision support to improve asthma care: A cluster-randomized trial”. Pediatrics. 125(4): e770–e777.
The full text is available at http://dx.doi.org/10.1561/0200000039
References 127
Bendavid, R. 2001. “The Shouldice repair”. In: Abdominal Wall Hernias. Ed. by R. Bendavid, J. Abrahamson, M. E. Arregui, J. B. Flament, and E. H. Phillips. New York, NY: Springer. 370–375.
Berenholtz, S. M., P. J. Pronovost, P. A. Lipsett, D. Hobson, K. Earsing, J. E. Farley, S. Milanovich, E. Garrett-Mayer, B. D. Winters, H. R. Rubin, T. Dorman, and T. M. Perl. 2004. “Eliminating catheter- related bloodstream infections in the intensive care unit”. Crit. Care Med. 32(10): 2014–2020.
Berry Jaeker, J. A. and A. L. Tucker. 2016. “Past the point of speeding up: The negative effects of workload saturation on efficiency and patient severity”. Manage. Sci. (Forthcoming.).
Berwick, D. M. 1991. “Controlling variation in health care: A consulta- tion from Walter Shewhart”. Med Care. 29(12): 1212–1225.
Berwick, D. M. 1998. “Developing and testing changes in delivery of care”. Ann. Intern Med. 128(8): 651–656.
Berwick, D. M. 2003. “Disseminating innovations in health care”. JAMA. 289(15): 1969–1975.
Berwick, D. M., B. James, and M. J. Coye. 2003. “Connections between quality measurement and improvement”. Med Care. 41(1 Suppl): I30–I38.
Berwick, D. M., T. W. Nolan, and J. Whittington. 2008. “The triple aim: Care, health, and cost”. Health Aff. 27(3): 759–769.
Besiou, M., A. J. Pedraza-Martinez, and L. N. van Wassenhove. 2014. “Vehicle supply chains in humanitarian operations: Decentralization, operational mix, and earmarked funding”. Prod Oper. Manag. 23(11): 1950–1965.
Best, T. J., B. Sandikci, D. D. Eisenstein, and D. O. Meltzer. 2015. “Managing hospital inpatient bed capacity through partitioning care into focused wings”. Manuf. Serv. Oper. Manag. 17(2): 157–176.
Blumenthal, D. 1995. “Applying industrial quality management science to physicians’ clinical decisions”. In: Improving Clinical Practice: Total Quality Management and the Physician. Ed. by D. Blumenthal and A. Scheck. San Francisco, CA: Jossey–Bass. 25–49.
Blumenthal, D. 2010. “Launching HITECH”. N. Engl. J. Med. 362(5): 382–385.
The full text is available at http://dx.doi.org/10.1561/0200000039
128 References
Blumenthal, D. and A. B. Jena. 2013. “Hospital value-based purchasing”. J. Hosp Med. 8(5): 271–277.
Blumenthal, D. and M. Tavenner. 2010. “The “meaningful use” regu- lation for electronic health records”. N. Engl. J. Med. 363(6): 501– 504.
Boyer, K. K., J. W. Gardner, and S. Schweikhart. 2012. “Process quality improvement: An examination of general vs. outcome-specific climate and practices in hospitals”. J. Oper. Manag. 30(4): 325–339.
Boyer, K. K. and M. W. Lewis. 2002. “Competitive priorities: Investi- gating the need for trade-offs in operations strategy”. Prod Oper. Manag. 11(1): 9–20.
Bozic, K. J., J. Maselli, P. S. Pekow, P. K. Lindenauer, T. P. Vail, and A. D. Auerbach. 2010. “The influence of procedure volumes and standardization of care on quality and efficiency in total joint replacement surgery”. J. Bone Jt. Surg. 92(16): 2643–2652.
Bradley, E. H., L. A. Curry, T. R. Webster, J. A. Mattera, S. A. Rouma- nis, M. J. Radford, R. L. McNamara, B. A. Barton, D. N. Berg, and H. M. Krumholz. 2006. “Achieving rapid door-to-balloon times: How top hospitals improve complex clinical systems”. Circulation. 113(8): 1079–1085.
Bradley, E. H., E. S. Holmboe, J. A. Mattera, S. A. Roumanis, M. J. Radford, and H. M. Krumholz. 2001. “A qualitative study of in- creasing β-blocker use after myocardial infarction”. JAMA. 285(20): 2604–2611.
Bradley, E. H., E. S. Holmboe, J. A. Mattera, S. A. Roumanis, M. J. Radford, and H. M. Krumholz. 2003. “The roles of senior manage- ment in quality improvement efforts: What are the key components?” J. Healthc. Manag. 48(1): 15–28.
Bradley, E. H., J. Herrin, L. Curry, E. J. Cherlin, Y. Wang, T. R. Webster, E. E. Drye, S. L. Normand, and H. M. Krumholz. 2010a. “Variation in hospital mortality rates for patients with acute my- ocardial infarction”. Am. J. Cardiol. 106(8): 1108–1112.
The full text is available at http://dx.doi.org/10.1561/0200000039
References 129
Bradley, E. H., I. M. Nembhard, C. T. Yuan, A. F. Stern, J. P. Curtis, B. K. Nallamothu, J. E. Brush Jr., and H. M. Krumholz. 2010b. “What is the experience of national quality campaigns? Views from the field”. Health Serv. Res. 45(6(Pt 1)): 1651–1669.
Bretthauer, K. M. and M. J. Côté. 1998. “A model for planning resource requirements in health care organizations”. Decis. Sci. 29(1): 243– 270.
Buntin, M. B., M. F. Burke, M. C. Hoaglin, and D. Blumenthal. 2011. “The benefits of health information technology: A review of the recent literature shows predominantly positive results”. Health Aff. 30(3): 464–471.
Burns, L. R. and M. V. Pauly. 2012. “Accountable care organizations may have difficulty avoiding the failures of integrated delivery net- works of the 1990s”. Health Aff. 31(11): 2407–2416.
Butler, T. W., G. K. Leong, and L. N. Everett. 1996. “The operations management role in hospital strategic planning”. J. Oper. Manag. 14(2): 137–156.
Cabana, M. D. and S. H. Jee. 2004. “Does continuity of care improve patient outcomes?” J. Fam. Pract. 53(12): 974–980.
Cachon, G. P. and M. L. Fisher. 2000. “Supply chain inventory man- agement and the value of shared information”. Manage. Sci. 46(8): 1032–1048.
Cachon, G. P. and C. Terwiesch. 2012. Matching Supply with Demand: An Introduction to Operations Management. Boston, MA: McGraw- Hill Education.
Campbell, S. M., D. Reeves, E. Kontopantelis, B. Sibbald, and M. Roland. 2009. “Effects of pay for performance on the quality of primary care in England”. N. Engl. J. Med. 361(4): 368–378.
Cardoen, B., E. Demeulemeester, and J. Beliën. 2010. “Operating room planning and scheduling: A literature review”. Eur. J. Oper. Res. 201(3): 921–932.
Carey, K., J. F. Burgess, and G. J. Young. 2008. “Specialty and full- service hospitals: A comparative cost analysis”. Health Serv. Res. 43(5(Pt 2)): 186–187.
The full text is available at http://dx.doi.org/10.1561/0200000039
130 References
Carman, J. M., S. M. Shortell, R. W. Foster, E. F. Hughes, H. Boer- stler, J. L. O’Brien, and E. J. O’Conner. 1996. “Keys for successful implementation of total quality management in hospitals”. Health Care Manage. Rev. 21(1): 48–60.
Cayirli, T. and E. Veral. 2003. “Outpatient scheduling in healthcare: A review of the literature”. Prod. Oper. Manag. 12(4): 519–549.
Cayirli, T., E. Veral, and H. Rosen. 2008. “Assessment of patient classi- fication in appointment system design”. Prod. Oper. Manag. 17(3): 338–353.
Centers for Medicare & Medicaid Services. 2011. “Medicare Program: Hospital Inpatient Value-Based Purchasing Program.” Fed. Regist. 88: 26490.
Centers for Medicare & Medicaid Services. 2013. HCAHPS Fact Sheet. Baltimore, MD.
Chand, S., H. Moskowitz, J. B. Norris, S. Shade, and D. R. Willis. 2009. “Improving patient flow at an outpatient clinic: Study of sources of variability and improvement factors”. Health Care Manag. Sci. 12(3): 325–340.
Chandrasekaran, A., C. Senot, and K. K. Boyer. 2012. “Process manage- ment impact on clinical and experiential quality: Managing tensions between safe and patient-centered healthcare”. Manuf. Serv. Oper. Manag. 14(4): 548–566.
Chang, S. I., C. S. Ou, C. Y. Ku, and M. Yang. 2008. “A study of RFID application impacts on medical safety”. Int. J. Electron. Healthc. 4(1): 1–23.
Chassin, M. R. 1991. “Quality of care: Time to act”. JAMA. 266(24): 3472–3473.
Chassin, M. R. and R. W. Galvin. 1998. “The urgent need to improve health care quality. Institute of Medicine National Roundtable on Health Care Quality”. JAMA. 280(11): 1000–1005.
Chassin, M. R., J. M. Loeb, S. P. Schmaltz, and R. M. Wachter. 2010. “Accountability measures–using measurement to promote quality improvement”. N. Engl. J. Med. 363(7): 683–688.
The full text is available at http://dx.doi.org/10.1561/0200000039
References 131
Chaudhry, B., J. Wang, S. Wu, M. Maglione, W. Mojica, E. Roth, S. C. Morton, and P. G. Shekelle. 2006. “Systematic review: Impact of health information technology on quality, efficiency, and costs of medical care”. Ann. Intern. Med. 144(10): 742–752.
Chidester, T. R. and W. C. Grigsby. 1984. “A meta-analysis of the goal setting-performance literature”. Acad Manag. Proc. 1984(1): 202–206.
Choo, A. S. 2014. “Defining problems fast and slow: The U-shaped effect of problem definition time on project duration”. Prod Oper. Manag. 23(8): 1462–1479.
Chou, S. Y., M. E. Deily, S. Li, and Y. Lu. 2014. “Competition and the impact of online hospital report cards”. J. Health Econ. 34(1): 42–58.
Christakis, D. A., J. A. Wright, F. J. Zimmerman, A. L. Bassett, and F. A. Connell. 2003. “Continuity of care is associated with well- coordinated care”. Ambul. Pediatr. 3(2): 82–86.
Christensen, C. M. 1997. The Innovator’s Dilemma: When New Tech- nologies Cause Great Firms to Fail. Boston, MA: Harvard Business School Press.
Clancy, C. M. 2007. “Mistake-proofing in health care: Lessons for ongoing patient safety improvements”. Am. J. Med. Qual. 22(6): 463–465.
Clark, J. R. and R. S. Huckman. 2012. “Broadening focus: Spillovers, complementarities, and specialization in the hospital industry”. Man- age. Sci. 58(4): 708–722.
Clark, S., M. Belfort, G. Saade, G. Hankins, D. Miller, D. Frye, and J. Meyers. 2007. “Implementation of a conservative checklist-based pro- tocol for oxytocin administration: Maternal and newborn outcomes”. Am. J. Obstet. Gynecol. 197(5): 480.e1–e5.
Cohen, A. B., J. D. Restuccia, M. Shwartz, J. E. Drake, R. Kang, P. Kralovec, S. K. Holmes, F. Margolin, and D. Bohr. 2008. “A survey of hospital quality improvement activities”. Med. Care Res. Rev. 65(5): 571–595.
Corbett, C. J., M. J. Montes-Sancho, and D. A. Kirsch. 2005. “The financial impact of ISO 9000 certification in the United States: An empirical analysis”. Manage. Sci. 51(7): 1046–1059.
The full text is available at http://dx.doi.org/10.1561/0200000039
132 References
Côté, M. J. 1999. “Patient flow and resource utilization in an outpatient clinic”. Socioecon. Plann. Sci. 33(3): 231–245.
Cram, P., G. E. Rosenthal, and M. S. Vaughan-Sarrazin. 2005. “Cardiac revascularization in specialty and general hospitals”. N. Engl. J. Med. 352(14): 1454–1462.
Culyer, A. J. and J. P. Newhouse. 2000. Handbook of Health Economics. Oxford, UK: Elsevier.
Cunningham, P. J. and L. M. Nichols. 2005. “The effects of Medi- caid reimbursement on the access to care of Medicaid enrollees: A community perspective”. Med Care Res. Rev. 62(6): 676–696.
Curry, L. A., E. Spatz, E. Cherlin, J. W. Thompson, D. Berg, H. H. Ting, C. Decker, H. M. Krumholz, and E. H. Bradley. 2011. “What distinguishes top-performing hospitals in acute myocardial infarction mortality rates? A qualitative study”. Ann. Intern. Med. 154(6): 384–390.
Cutler, D. M. and R. J. Zeckhauser. 2000. “The Anatomy of Health Insurance”. In: Handbook of Health Economics. Ed. by A. J. Culyer and J. P. Newhouse. Oxford, UK: Elsevier.
Darr, E. D., L. Argote, and D. Epple. 1995. “The acquisition, transfer, and depreciation of knowledge in service organizations: Productivity in franchises”. Manage. Sci. 41(11): 1750–1762.
Dasu, S. and R. B. Chase. 2010. “Designing the soft side of customer service”. MIT Sloan Manag. Rev. 52(1): 33–39.
Deming, W. E. 1986. Out of the Crisis. Cambridge, MA: Massachusetts Institute of Technology, Center for Advanced Engineering Study.
Deo, S., S. Iravani, T. Jiang, K. Smilowitz, and S. Samuelson. 2013. “Improving health outcomes through better capacity allocation in a community-based chronic care model”. Oper. Res. 61(6): 1277–1294.
Deo, S., S. M. Topp, A. Garcia, M. Soldner, K. Y. Sokat, J. Chipukuma, C. S. Wamulume, S. E. Reid, and J. Swann. 2012. “Modeling the impact of integrating HIV and outpatient health services on patient waiting times in an urban health clinic in Zambia”. PLoS One. 7(4): e35479.
The full text is available at http://dx.doi.org/10.1561/0200000039
References 133
DesRoches, C. M., E. G. Campbell, S. R. Rao, K. Donelan, T. G. Ferris, A. Jha, R. Kaushal, D. E. Levy, S. Rosenbaum, A. E. Shields, and D. Blumenthal. 2008. “Electronic health records in ambulatory care: A national survey of physicians”. N. Engl. J. Med. 359(1): 50–60.
DesRoches, C. M., E. G. Campbell, C. Vogeli, J. Zheng, S. R. Rao, A. E. Shields, K. Donelan, S. Rosenbaum, S. J. Bristol, and A. K. Jha. 2010. “Electronic health records’ limited successes suggest more targeted uses”. Health Aff. 29(4): 639–646.
DesRoches, C. M., C. Worzala, M. S. Joshi, P. D. Kralovec, and A. K. Jha. 2012. “Small, nonteaching, and rural hospitals continue to be slow in adopting electronic health record systems”. Health Aff. 31(5): 1092–1099.
Devaraj, S., T. T. Ow, and R. Kohli. 2013. “Examining the impact of information technology and patient flow on healthcare performance: A Theory of Swift and Even Flow (TSEF) perspective”. J. Oper. Manag. 31(4): 181–192.
Dey, A., K. K. Sinha, and S. Thirumalai. 2013. “IT capability for health care delivery: Is more better?” J. Serv. Res. 16(3): 326–340.
Ding, D. X. 2014. “The effect of experience, ownership and focus on productive efficiency: A longitudinal study of U.S. hospitals”. J. Oper. Manag. 32(1–2): 1–14.
Dixon–Woods, M., S. McNicol, and G. Martin. 2012. “Ten challenges in improving quality in healthcare: Lessons from the Health Founda- tion’s programme evaluations and relevant literature”. BMJ Qual. Saf. 21(10): 876–884.
Donabedian, A. 1966. “Evaluating the quality of medical care”. Milbank Mem. Fund. Q. 44(3): 166–206.
Doty, M. M., A. K. Fryer, and A. M. Audet. 2012. “The role of care coor- dinators in improving care coordination: The patient’s perspective”. Intern. Med. 172(7): 587–588.
Douglas, T. J. and L. D. Fredendall. 2004. “Evaluating the Deming management model of total quality in services”. Decis. Sci. 35(3): 393–422.
Edmondson, A. C. 1999. “Psychological safety and learning behavior in work teams”. Adm. Sci. Q. 44(2): 350–383.
The full text is available at http://dx.doi.org/10.1561/0200000039
134 References
Edmondson, A. C. 2003. “Framing for learning: Lessons in successful technology implementation”. Calif. Manage. Rev. 45(2): 34–54.
Erdem, E., H. Zeng, J. Zhou, J. Shi, and D. L. Wells. 2009. “Investigation of RFID tag readability for pharmaceutical products at item level”. Drug Dev. Ind. Pharm. 35(11): 1312–1324.
Ethiraj, S. K. and D. Levinthal. 2009. “Hoping for A to Z while rewarding only A: Complex organizations and multiple goals”. Organ. Sci. 20(1): 4–21.
Evdokimov, S., B. Fabian, O. Günther, L. Ivantysynova, and H. Ziekow. 2010. “RFID and the internet of things: Technology, applications, and security challenges”. Found. Trends Technol. Inf Oper. Manag. 4(2): 105–185.
Faraj, S. and Y. Xiao. 2006. “Coordination in fast-response organiza- tions”. Manage. Sci. 52(8): 1155–1169.
Field, J. M., J. Heineke, J. R. Langabeer, and J. L. DelliFraine. 2014. “Building the case for quality improvement in the health care in- dustry: A focus on goals and training”. Qual. Manag. Health Care. 23(3): 138–154.
Field, R. I. 2007. Health Care Regulation in America: Complexity, Confrontation and Compromise. New York, NY: Oxford University Press.
Fieldston, E., C. Terwiesch, and S. Altschuler. 2013. “Application of business model innovation to enhance value in health care delivery”. JAMA Pediatr. 167(5): 409–411.
Fisher, E. S., M. B. McClellan, J. Bertko, S. M. Lieberman, J. J. Lee, J. L. Lewis, and J. S. Skinner. 2009. “Fostering accountable health care: moving forward in medicare”. Health Aff. 28(2): w219–231.
Fisher, E. S. and S. M. Shortell. 2010. “Accountable care organizations: Accountable for what, to whom, and how”. JAMA. 304(15): 1715– 1716.
Flynn, B. B., S. Sakakibara, R. G. Schroeder, K. A. Bates, and E. J. Flynn. 1990. “Empirical research methods in operations manage- ment”. J. Oper. Manag. 9(2): 250–284.
The full text is available at http://dx.doi.org/10.1561/0200000039
References 135
Flynn, B. B., R. G. Schroeder, and S. Sakakibara. 1995. “The impact of quality management practices on performance and competitive advantage”. Decis. Sci. 26(5): 659–691.
Frankel, A. S., M. W. Leonard, and C. R. Denham. 2006. “Fair and just culture, team behavior, and leadership engagement: The tools to achieve high reliability”. Health Serv. Res. 41(4 II): 1690–1709.
Fredendall, L. D., J. B. Craig, P. J. Fowler, and U. Damali. 2009. “Bar- riers to swift, even flow in the internal supply chain of perioperative surgical services department: A case study”. Decis. Sci. 40(2): 327– 349.
Furman, C. and R. Caplan. 2007. “Applying the Toyota Production System: Using a patient safety alert system to reduce error”. Jt. Comm. J. Qual. Patient Saf. 33(7): 376–386.
Gawande, A. 2007. Better: A Surgeon’s Notes on Performance. New York, NY: Picador.
Gawande, A. 2009a. The Checklist Manifesto: How to Get Things Right. New York, NY: Metropolitan Books.
Gawande, A. 2009b. “The cost conundrum”. New Yorker. 1: 36–44. Gawande, A. 2010. “Now what?” New Yorker. Ghosh, M. 2012. “A3 process: A pragmatic problem-solving technique
for process improvement in health care”. J. Health Manag. 14(1): 1–11.
Ghosh, M. and D. K. Sobek. 2014. “A problem-solving routine for improving hospital operations”. J. Health Organ. Manag. 29(2): 252–270.
Ginsburg, P. B. and D. M. Koretz. 1983. “Bed availability and hospital utilization: Estimates of the “Roemer effect””. Health Care Financ. Rev. 5(1): 87–92.
Girotra, K., C. Terwiesch, and K. T. Ulrich. 2010. “Idea generation and the quality of the best idea”. Manage. Sci. 56(4): 591–605.
Gittell, J. H. 2002. “Coordinating mechanisms in care provider groups: Relational coordination as a mediator and input uncertainty as a moderator of performance effects”. Manage. Sci. 48(11): 1408–1426.
The full text is available at http://dx.doi.org/10.1561/0200000039
136 References
Gittell, J. H., K. M. Fairfield, B. Bierbaum, W. Head, R. Jackson, M. Kelly, R. Laskin, S. Lipson, J. Siliski, T. Thornhill, and J. Zuckerman. 2000. “Impact of relational coordination on quality of care, postoperative pain and functioning, and length of stay: A nine-hospital study of surgical patients”. Med. Care. 38(2): 807–819.
Gittell, J. H., R. Seidner, and J. Wimbush. 2010. “A relational model of how high-performance work systems work”. Organ. Sci. 21(2): 490–506.
Goldstein, S. M. 2003. “Employee development: An examination of service strategy in a high-contact service environment”. Prod Oper. Manag. 12(2): 186–203.
Goldstein, S. M. and A. R. Iossifova. 2012. “Ten years after: Interference of hospital slack in process performance benefits of quality practices”. J. Oper. Manag. 30(1-2): 44–54.
Gowen, C. R., K. L. McFadden, J. M. Hoobler, and W. J. Tallon. 2006. “Exploring the efficacy of healthcare quality practices, employee commitment, and employee control”. J. Oper. Manag. 24(6): 765– 778.
Green, L. V. 2006. “Queueing analysis in healthcare”. In: Patient Flow: Reducing Delay in Healthcare Delivery. Ed. by R. W. Hall. Boston, MA: Springer US. 281–307.
Green, L. V. and V. Nguyen. 2001. “Strategies for cutting hospital beds: The impact on patient service”. Health Serv. Res. 36(2): 421–442.
Green, L. V. and S. Savin. 2008. “Reducing delays for medical appoint- ments: A queueing approach”. Oper. Res. 56(6): 1526–1538.
Greenhalgh, T., G. Robert, F. Macfarlane, P. Bate, and O. Kyriakidou. 2004. “Diffusion of innovations in service organizations: Systematic review and recommendations”. Milbank Q. 82(4): 581–629.
Greenwald, L., J. Cromwell, W. Adamache, S. L. Bernard, E. Drozd, E. Root, and K. J. Devers. 2006. “Specialty versus community hospitals: Referrals, quality, and community benefits”. Health Aff. 25(1): 106– 118.
Griffenhagen, G. B. and M. Bogard. 1999. History of Drug Containers and Their Labels. American Institute of the History of Pharmacy.
The full text is available at http://dx.doi.org/10.1561/0200000039
References 137
Griffin, J., P. Keskinocak, and J. Swann. 2013. “Allocating scarce healthcare resources in developing countries: A case for malaria prevention”. In: Handbook of Healthcare Operations Management: Methods and Applications. Ed. by B. T. Denton. New York, NY: Springer New York. 511–532.
Grout, J. R. 2006. “Mistake proofing: Changing designs to reduce error”. Qual. Saf. Health Care Suppl. 1(15): i44–i49.
Grout, J. R. 2007. Mistake-Proofing the Design of Health Care Processes. Washington, DC.
Gupta, D. and B. Denton. 2008. “Appointment scheduling in health care: Challenges and opportunities”. IIE Trans. 40(9): 800–819.
Gupta, D. and S. J. Potthoff. 2016. “Matching supply and demand for hospital services”. Found. Trends Technol. Inf Oper. Manag. 8(3-4): 131–274.
Hackman, J. R. and R. Wageman. 1995. “Total quality management: Empirical, conceptual, and practical issues”. Adm. Sci. Q. 19(3): 309–342.
Haggerty, J. L., R. J. Reid, G. K. Freeman, B. H. Starfield, C. E. Adair, and R. McKendry. 2003. “Continuity of care: A multidisciplinary review”. BMJ. 327(7425): 1219–1221.
Haggerty, J. L., D. Roberge, G. K. Freeman, and C. Beaulieu. 2013. “Experienced continuity of care when patients see multiple clinicians: A qualitative metasummary”. Ann. Fam. Med. 11(3): 262–271.
Han, Y. Y., J. A. Carcillo, S. T. Venkataraman, R. S. Clark, R. S. Watson, T. C. Nguyen, H. Bayir, and R. A. Orr. 2005. “Unexpected increased mortality after implementation of a commercially sold computerized physician order entry system”. Pediatrics. 116(6): 1506–1512.
Haraden, C. and R. Resar. 2004. “Patient flow in hospitals: Understand- ing and controlling it better”. Front. Health Serv. Manage. 20(4): 3–15.
Harman, J. S., K. M. Rost, C. A. Harle, and R. L. Cook. 2012. “Elec- tronic medical record availability and primary care depression treat- ment”. J. Gen. Intern. Med. 27(8): 962–967.
The full text is available at http://dx.doi.org/10.1561/0200000039
138 References
Harris, J. E. 1977. “The internal organization of hospitals: Some eco- nomic implications”. Bell J. Econ. 8(2): 467–482.
Harrison, M. I., K. Paez, K. L. Carman, J. Stephens, L. Smeeding, K. J. Devers, and S. Garfinkel. 2016. “Effects of organizational context on Lean implementation in five hospital systems”. Health Care Manage Rev. 41(2): 127–144.
Harry, M. J. and R. Schroeder. 2000. Six Sigma: The Breakthrough Management Strategy Revolutionizing the World’s Top Corporation. New York, NY: Currency.
Hart, E. M. and H. Owen. 2005. “Errors and omissions in anesthesia: A pilot study using a pilot’s checklist”. Anesth. Analg. 101(1): 246–250.
Hayes, R. H. and G. P. Pisano. 2009. “Manufacturing strategy: At the intersection of two paradigm shifts”. Prod Oper. Manag. 5(1): 25–41.
Henry J. Kaiser Family Foundation. 2015. “State Health Facts”. Avail- able at: pphttp://www.statehealthfacts.org. [Accessed September 12, 2015].
van Herck, P., D. de Smedt, L. Annemans, R. Remmen, M. B. Rosenthal, and W. Sermeus. 2010. “Systematic review: Effects, design choices, and context of pay-for-performance in health care”. Health Serv. Res. 10: 247.
Herzer, K. R. and P. J. Pronovost. 2013. “Motivating physicians to improve quality: Light the intrinsic fire”. Am. J. Med. Qual. 29(5): 451–453.
Heskett, J. L. 1983. Shouldice Hospital Limited. Harvard Bus. Sch. Case 9-683-68.
Heskett, J. L., S. Earl, and L. A. Schlesinger. 1997. The Service Profit Chain: How Leading Companies Link Profit Growth to Loyalty, Satisfaction, and Value. New York, NY: Free Press.
Heskett, J. L., T. O. Jones, G. W. Loveman, S. Earl, and L. A. Schlesinger. 1994. “Putting the service-profit chain to work”. Harv. Bus. Rev. 72(2): 164–170.
Hines, P., M. Holweg, and N. Rich. 2004. “Learning to evolve: A review of contemporary Lean thinking”. Int. J. Oper. Prod. Manag. 24(10): 994–1011.
The full text is available at http://dx.doi.org/10.1561/0200000039
References 139
Holden, R. J. 2011. “Lean Thinking in emergency departments: A critical review”. Ann. Emerg. Med. 57(3): 265–278.
Houle, S. K. D., F. A. McAlister, C. A. Jackevicius, A. W. Chuck, and R. T. Tsuyuki. 2012. “Does performance-based remuneration for individual health care practitioners affect patient care? A systematic review”. Ann. Intern. Med. 157(12): 889–899.
Hsiao, C. J., S. L. Decker, E. Hing, and J. E. Sisk. 2012. “Most physicians were eligible for federal incentives in 2011, but few had EHR systems that met meaningful-use criteria”. Health Aff. 31(5): 1100–1107.
Huckman, R. S. and D. E. Zinner. 2008. “Does focus improve opera- tional performance? Lessons from the management of clinical trials”. Strateg. Manag. J. 29(2): 173–193.
Hyer, N. L., U. Wemmerlöv, and A. Morris. 2009. “Performance analysis of a focused hospital unit: The case of an integrated trauma center”. J. Oper. Manag. 27(3): 203–219.
Iglehart, J. K. 1996. “The national committee for quality assurance”. N. Engl. J. Med. 335(13): 995–999.
Iglehart, J. K. 2005. “The uncertain future of specialty hospitals”. N. Engl. J. Med. 352(14): 1405–1407.
Institute for Healthcare Improvement. 2016. Available at: http://www. ihi.org/about/Pages/ScienceofImprovement.aspx. [Accessed June 24, 2016].
Institute of Medicine. 2000. To Err Is Human: Building a Safer Health System. Ed. by T. L. T. Kohn, J. M. Corrigan, and M. S. Donaldson. Washington, D.C.: National Academies Press.
Institute of Medicine. 2001. Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC: National Academies Press.
Ivancevich, J. M. 1977. “Different goal setting treatment and their effects on performance and job satisfaction”. Acad Manag. J. 20(3): 406–419.
Jack, E. P. and T. L. Powers. 2004. “Volume flexible strategies in health services: A research framework”. Prod Oper. Manag. 13(3): 230–244.
The full text is available at http://dx.doi.org/10.1561/0200000039
140 References
Jack, E. P. and T. L. Powers. 2009. “A review and synthesis of demand management, capacity management and performance in health-care services”. Int. J. Manag. Rev. 11(2): 149–174.
Janakiraman, R., J. Parish, and L. Berry. 2011. “The effect of the work and physical environment on hospital nurses’ perceptions and attitudes: Service quality and commitment”. Qual. Manag. J. 18(4): 36–49.
Jha, A. K., M. F. Burke, C. DesRoches, M. S. Joshi, P. D. Kralovec, E. G. Campbell, and M. B. Buntin. 2011. “Progress toward meaningful use: Hospitals’ adoption of electronic health records”. Am. J. Manag. Care. 17(12 Spec No.): SP117–SP124.
Jha, A. K., C. M. DesRoches, E. G. Campbell, K. D. ans S. R. Rao, T. G. Ferris, A. Shields, S. Rosenbaum, and D. Blumenthal. 2009. “Use of electronic health records in U.S. hospitals”. N. Engl. J. Med. 360(16): 1628–1638.
Jha, A. K., C. M. DesRoches, P. D. Kralovec, and M. S. Joshi. 2010. “A progress report on electronic health records in U.S.” Health Aff. 29(10): 1951–1957.
Jha, A. K., K. E. Joynt, E. J. Orav, and A. M. Epstein. 2012. “The long- term effect of premier pay for performance on patient outcomes”. N. Engl. J. Med. 366(17): 1606–1615.
Jimmerson, C. 2007. A3 Problem Solving for Health Care: A Practical Method for Eliminating Waste. New York, NY: Productivity Press.
Jimmerson, C., D. Weber, and D. K. Sobek. 2005. “Reducing waste and errors: Piloting Lean principles at Intermountain Healthcare”. Jt Comm. J. Qual. Patient Saf. 31(5): 249–257.
Jones, S. S., R. S. Rudin, T. Perry, and P. G. Shekelle. 2014. “Health information technology: An updated systematic review with a focus on meaningful use”. Ann. Intern. Med. 160(1): 48–54.
Kaplan, H. C., P. W. Brady, M. C. Dritz, D. K. Hooper, W. M. Linam, C. M. Froehle, and P. Margolis. 2010. “The influence of context on quality improvement success in health care: A systematic review of the literature”. Milbank Q. 88(4): 500–559.
The full text is available at http://dx.doi.org/10.1561/0200000039
References 141
Kaplan, H. C., L. P. Provost, C. M. Froehle, and P. A. Margolis. 2012. “The model for understanding success in quality (MUSIQ): Building a theory of context in healthcare quality improvement”. BMJ Qual. Saf. 21(1): 13–20.
Kaplan, R. S. and D. P. Norton. 1992. “The balanced scorecard - measures that drive performance”. Harv. Bus. Rev. 70(1): 71–79.
Karsh, B. T., R. J. Holden, S. J. Alper, and C. K. L. Or. 2006. “A human factors engineering paradigm for patient safety: Designing to support the performance of the healthcare professional”. Qual. Saf. Health Care. 15 Suppl 1: i59–i65.
Katz-Navon, T., E. Naveh, and Z. Stern. 2005. “Safety climate in health care organizations: A multidimensional approach”. Acad Manag. J. 48(6): 1075–1089.
Kaynak, H. 2003. “The relationship between total quality management practices and their effects on firm performance”. J. Oper. Manag. 21(4): 405–435.
KC, D. S. and B. R. Staats. 2012. “Accumulating a portfolio of ex- perience: The effect of focal and related experience on surgeon performance”. Manuf. Serv. Oper. Manag. 14(4): 618–633.
KC, D. S. and C. Terwiesch. 2011. “The effects of focus on performance: Evidence from California hospitals”. Manage. Sci. 57(11): 1897– 1912.
KC, D. S. and C. Terwiesch. 2012. “An econometric analysis of patient flows in the cardiac intensive care unit”. Manuf. Serv. Oper. Manag. 14(1): 50–65.
Kilo, C. M. 1999. “Improving care through collaboration”. Pediatrics. 103(1 Suppl E): 384–393.
Kim, S. H., C. W. Chan, M. Olivares, and G. Escobar. 2015. “ICU admission control: An empirical study of capacity allocation and its implication for patient outcomes”. Manage. Sci. 61(1): 19–38.
Klassen, K. J. and T. R. Rohleder. 2004. “Outpatient appointment scheduling with urgent clients in a dynamic, multi-period environ- ment”. Int. J. Serv. Ind. Manag. 15(2): 167–186.
The full text is available at http://dx.doi.org/10.1561/0200000039
142 References
Klassen, K. J. and R. Yoogalingam. 2008. “An assessment of the in- terruption level of doctors in outpatient appointment scheduling”. Oper. Manag. Res. 1(2): 95–102.
Klassen, K. J. and R. Yoogalingam. 2009. “Improving performance in outpatient appointment services with a simulation optimization approach”. Prod. Oper. Manag. 18(4): 447–458.
Klassen, K. J. and R. Yoogalingam. 2013. “Appointment system de- sign with interruptions and physician lateness”. Int. J. Oper. Prod. Manag. 33(4): 394–414.
Klein, K. J. and A. P. Knight. 2005. “Innovation implementation. Over- coming the challenge”. Curr. Dir. Psychol. Sci. 14(5): 243–246.
Kocher, R. P. and E. Y. Adashi. 2011. “Hospital readmissions and the affordable care act: Paying for coordinated quality care”. JAMA. 306(16): 1794–1795.
Koppel, R., J. P. Metlay, A. Cohen, B. Abaluck, A. R. Localio, S. E. Kimmel, and B. L. Strom. 2005. “Role of computerized physician or- der entry systems in facilitating medication errors”. JAMA. 293(10): 1197–1203.
Koppel, R., T. Wetterneck, J. L. Telles, and B. T. Karsh. 2008. “Work- arounds to barcode medication administration systems: Their occur- rences, causes, and threats to patient safety”. J. Am. Med. Inform. Assoc. 15(4): 408–423.
Kornfeld, B. J. and S. Kara. 2011. “Project portfolio selection in con- tinuous improvement”. Int. J. Oper. Prod. Manag. 31(10): 1071– 1088.
Kotter, J. P. 1995. “Leading change: Why transformation efforts fail”. Harv. Bus. Rev. 73(2): 59–67.
Kotter, J. P. 2007. “Leading change”. Harv. Bus. Rev. 85(1): 96–103. Kovach, J. V. 2013. “The influence of continuous improvement practices
on learning: An empirical study”. Qual. Manag. J. 20(4): 6–20. Kovner, A. R. and J. R. Knickman. 2008. Jonas and Kovner’s Health
Care Delivery in the United States, 9th Edition. New York, NY: Springer Publishing Company.
The full text is available at http://dx.doi.org/10.1561/0200000039
References 143
Kraiselburd, S. and P. Yadav. 2013. “Supply chains and global health: An imperative for bringing operations management scholarship into action”. Prod. Oper. Manag. 22(2): 377–381.
Kumar, S., G. Livermont, and G. McKewan. 2010. “Stage implementa- tion of RFID in hospitals”. Technol. Health Care. 18(1): 31–46.
Kumar, S. and M. Steinebach. 2008. “Eliminating US hospital medical errors”. Int. J. Health Care Qual. Assur. 21(5): 444–471.
Kumar, S., E. Swanson, and T. Tran. 2009. “RFID in the healthcare supply chain: Usage and application”. Int. J. Health Care Qual. Assur. 22(1): 67–81.
Kuntz, L., R. Mennicken, and S. Scholtes. 2015. “Stress on the ward: Evidence of safety tipping points in hospitals”. Manage. Sci. 61(4): 754–771.
LaGanga, L. R. 2011. “Lean service operations: Reflections and new directions for capacity expansion in outpatient clinics”. J. Oper. Manag. 29(5): 422–433.
LaGanga, L. R. and S. R. Lawrence. 2007. “Clinic overbooking to improve patient access and increase provider productivity”. Decis. Sci. 38(2): 251–276.
Lakkam, M., S. Wager, P. H. Wise, and L. M. Wein. 2014. “Quantifying and exploiting the age dependence in the effect of supplementary food for child undernutrition”. PLoS One. 9(6): e99632.
Lam, M. and D. Robertson. 2012. “Organizational culture, tenure, and willingness to participate in continuous improvement projects in healthcare”. Qual. Manag. J. 19(3): 7–15.
Langabeer, J. R., J. L. DelliFraine, J. Heineke, and I. Abbass. 2009. “Implementation of lean and Six Sigma quality initiatives in hospitals: A goal theoretic perspective”. Oper. Manag. Res. 2(1-4): 13–27.
Langley, G. J., R. Moen, K. M. Nolan, T. W. Nolan, C. L. Norman, and L. P. Provost. 2009. The Improvement Guide: A Practical Approach to Enhancing Organizational Performance, 2nd ed. San Francisco, CA: Jossey–Bass Publishers.
Lapierre, S. D., C. Batson, and S. McCaskey. 1999. “Improving on-time performance in health care organizations: A case study”. Health Care Manag. Sci. 2(1): 27–34.
The full text is available at http://dx.doi.org/10.1561/0200000039
144 References
Lapré, M. A. and I. M. Nembhard. 2010. “Inside the organizational learning curve: Understanding the organizational learning process”. Found. Trends Technol. Inf. Oper. Manag. 4(1): 1–103.
Lapré, M. A. and L. N. van Wassenhove. 2001. “Creating and transfer- ring knowledge for productivity improvement in factories”. Manage. Sci. 47(10): 1311–1325.
Latha, N. A., B. R. Murthy, and U. Sunitha. 2012. “Electronic health record”. Int. J. Eng. Res. Technol. 1(10): 1–8.
Leape, L. L. 1994. “Error in Medicine”. JAMA. 272(23): 1851–1857. Lee, H. L. 2004. “The Triple-A Supply Chain”. Harv. Bus. Rev. 82(10):
102–112. Lindenauer, P. K., D. Remus, S. Roman, M. B. Rothberg, E. M. Ben-
jamin, A. Ma, and D. W. Bratzler. 2007. “Public reporting and pay for performance in hospital quality improvement”. N. Engl. J. Med. 356(5): 486–496.
Linderman, K., R. G. Schroeder, and A. S. Choo. 2006. “Six Sigma: The role of goals in improvement teams”. J. Oper. Manag. 24(6): 779–790.
Linderman, K., R. G. Schroeder, S. Zaheer, and A. S. Choo. 2003. “Six Sigma: A goal-theoretic perspective”. J. Oper. Manag. 21(2): 193–203.
Liu, N., S. Ziya, and V. G. Kulkarni. 2010. “Dynamic scheduling of outpatient appointments under patient no-shows and cancellations”. Manuf. Serv. Oper. Manag. 12(2): 347–364.
Loch, C. H. and C. Terwiesch. 2009. “Rush and be wrong or wait and be late? A model of information in collaborative processes”. Prod. Oper. Manag. 14(3): 331–343.
Locke, E. A. 1968. “Toward a theory of task motivation and incentives”. Organ. Behav. Hum. Perform. 3(2): 157–189.
Locke, E. A., D. O. Chah, S. Harrison, and N. Lustgarten. 1989. “Sepa- rating the effects of goal specificity from goal level”. Organ. Behav. Hum. Decis. Process. 43(2): 270–287.
Locke, E. A. and G. P. Latham. 1990. A Theory of Goal Setting & Task Performance. Englewood Cliffs, NJ: Prentice-Hall.
The full text is available at http://dx.doi.org/10.1561/0200000039
References 145
Lukas, C. V., S. K. Holmes, A. B. Cohen, J. Restuccia, I. E. Cramer, M. Shwartz, and M. P. Charns. 2007. “Transformational change in health care systems”. Health Care Manage Rev. 32(4): 309–320.
Marcon, E. and F. Dexter. 2006. “Impact of surgical sequencing on post anesthesia care unit staffing”. Health Care Manag. Sci. 9(1): 87–98.
Marcus, A. and E. Naveh. 2005. “How a new rule is adjusted to context: Knowledge creation following the implementation of the ISO 9000 quality standard”. Int. J. Organ. Anal. 13(2): 106–126.
Marley, K. A., D. A. Collier, and S. M. Goldstein. 2004. “The role of clinical and process quality in achieving patient satisfaction in hospitals”. Decis. Sci. 35(3): 349–369.
Marshall, A., C. Vasilakis, and E. El–Darzi. 2005. “Length of stay-based patient flow models: Recent developments and future directions”. Health Care Manag. Sci. 8(3): 213–220.
Marshall, M., P. Pronovost, and M. Dixon-Woods. 2013. “Promotion of improvement as a science”. Lancet. 381(9864): 419–421.
Mazzocato, P., C. Savage, M. Brommels, H. Aronsson, and J. Thor. 2010. “Lean thinking in healthcare: A realist review of the literature”. Qual. Saf. Health Care. 19(5): 376–382.
McCarthy, M. L., R. Ding, J. M. Pines, C. Terwiesch, M. Sattarian, J. A. Hilton, J. Lee, and S. L. Zeger. 2012. “Provider variation in fast track treatment time”. Med. Care. 50(1): 43–49.
McClellan, M. 1997. “Hospital reimbursement incentives: An empirical analysis”. J. Econ. Manag. Strateg. 6(1): 91–128.
McCoy, J. H. 2013. “Overcoming the Challenges of the Last Mile: A Model of Riders for Health”. In: Handbook of Healthcare Operations Management: Methods and Applications. Ed. by B. T. Denton. New York, NY: Springer. 483–509.
McDermott, C. M. and G. N. Stock. 2011. “Focus as emphasis: Concep- tual and performance implications for hospitals”. J. Oper. Manag. 29(6): 616–626.
McFadden, K. L., S. C. Henagan, and C. R. Gowen III. 2009. “The patient safety chain: Transformational leadership’s effect on patient safety culture, initiatives, and outcomes”. J. Oper. Manag. 27(5): 390–404.
The full text is available at http://dx.doi.org/10.1561/0200000039
146 References
McFadden, K. L., G. N. Stock, and C. R. Gowen III. 2006. “Implemen- tation of patient safety initiatives in US hospitals”. Int. J. Oper. Prod. Manag. 26(3): 326–347.
McGlynn, E. A. and S. M. Asch. 1998. “Developing a clinical perfor- mance measure”. Am. J. Prev. Med. Suppl. 14(3): 14–21.
McGlynn, E. A., S. M. Asch, J. Adams, J. Keesey, J. Hicks, A. DeCristo- faro, and E. A. Kerr. 2003. “The quality of health care delivered to adults in the United States”. N. Engl. J. Med. 348(26): 2635–2645.
McLeod, P. J., R. M. Tamblyn, D. Gayton, R. Grad, L. Snell, L. Berk- son, and M. Abrahamowicz. 1997. “Use of standardized patients to assess between-physician variations in resource utilization”. JAMA. 278(14): 1164–1168.
McManus, M. L., M. C. Long, A. Cooper, J. Mandell, D. M. Berwick, M. Pagano, and E. Litvak. 2003. “Variability in surgical caseload and access to intensive care services”. Anesthesiology. 98(6): 1491–1496.
MedPAC. 2009. Accountable Care Organizations. Merlino, J. I. and A. Raman. 2013. “Health care’s service fanatics:
How the Cleveland Clinic leaped to the top of patient-satisfaction surveys”. Harv. Bus. Rev. 91(5): 108–116.
Meyer, S. M. and D. A. Collier. 1998. “Contrasting the original Malcolm Baldrige national quality award and the health care pilot award”. Qual. Manag. Health Care. 6(3): 12–21.
Meyer, S. M. and D. A. Collier. 2001. “An empirical test of the causal relationships in the Baldrige health care pilot criteria”. J. Oper. Manag. 19(4): 403–426.
van Mieghem, J. A. 2003. “Commissioned paper: Capacity management, investment, and hedging: Review and recent developments”. Manuf. Serv. Oper. Manag. 5(4): 269–302.
Moody, K. 2014. “Competition and conflict: Union growth in the US hospital industry”. Econ. Ind. Democr. 35(1): 5–25.
Moore, M. H. 1995. Creating Public Value: Strategic Management in Government. Harvard University Press.
Mukherjee, A. S., M. A. Lapré, and L. N. van Wassenhove. 1998. “Knowledge driven quality improvement”. Manage. Sci. 44(11–12): S35–S49.
The full text is available at http://dx.doi.org/10.1561/0200000039
References 147
Murray, M. and D. M. Berwick. 2003. “Advanced access: Reducing waiting and delays in primary care”. JAMA. 289(8): 1035–1040.
Murray, M. and C. Tantau. 1999. “Redefining open access to primary care”. Manag. Care Q. 7(3): 45–55.
Murray, M. and C. Tantau. 2000. “Same-day appointments: Exploding the access paradigm”. Fam. Pract. Manag. 7(8): 45–50.
Nair, A., M. Nicolae, and R. Narasimhan. 2013. “Examining the im- pact of clinical quality and clinical flexibility on cardiology unit performance-Does experiential quality act as a specialized comple- mentary asset?” J. Oper. Manag. 31(7-8): 505–522.
Nanji, K. C., T. G. Ferris, D. F. Torchiana, and G. S. Meyer. 2013. “Overarching goals: A strategy for improving healthcare quality and safety?” BMJ Qual. Saf. 22(3): 187–193.
Natarajan, K. V. and J. M. Swaminathan. 2014. “Inventory manage- ment in humanitarian operations: Impact of amount, schedule, and uncertainty in funding”. Manuf. Serv. Oper. Manag. 16(4): 595–603.
National Center for Health Statistics. 2016. Health, United States, 2015: With Special Feature on Adults Aged 55-64. Hyattsville, MD.
Neely, A., M. Gregory, and K. Platts. 1995. “Performance measurement system design”. Int. J. Oper. Prod. Manag. 15(4): 80–116.
Nelson-Peterson, D. L. and C. J. Leppa. 2007. “Creating an environment for caring using Lean principles of the Virginia Mason production system”. J. Nurs. Adm. 37(6): 287–294.
Nembhard, I. M., C. T. Yuan, V. Shabanova, and P. D. Cleary. 2015. “The relationship between voice climate and patients’ experience of timely care in primary care clinics”. Health Care Manage. Rev. 40(2): 104–115.
NHS Institute for Innovation and Improvement Matrix Research and Consultancy. 2006. What is Transformational Change? [literature review]. Coventry, UK: University of Warwick.
Obermeyer, Z., M. Makar, S. Abujaber, F. Dominici, S. Block, and D. M. Cutler. 2014. “Association between the medicare hospice benefit and health care utilization and costs for patients with poor-prognosis cancer”. JAMA. 312(18): 1888–1896.
The full text is available at http://dx.doi.org/10.1561/0200000039
148 References
Ohashi, K., S. Ota, L. Ohno-Machado, and H. Tanaka. 2008. “Com- parison of RFID systems for tracking clinical interventions at the bedside”. In: AMIA Annu. Symp. Proc. 525–529.
Okhuysen, G. A. and B. A. Bechky. 2009. “Coordination in organiza- tions: An integrative perspective”. Acad. Manag. Ann. 3(1): 463– 502.
Olivares, M., C. Terwiesch, and L. Cassorla. 2008. “Structural estimation of the newsvendor model: An application to reserving operating room time”. Manage. Sci. 54(1): 41–55.
O’Malley, A. S., J. M. Grossman, G. R. Cohen, N. M. Kemper, and H. H. Pham. 2010. “Are electronic medical records helpful for care coordination? Experiences of physician practices”. J. Gen. Intern. Med. 25(3): 177–185.
O’Neill, L. 2015. “If more competition is the answer, why hasn’t it worked?” Anesth. Analg. 120(1): 3–4.
Ozen, A. and H. Balasubramanian. 2013. “The impact of case mix on timely access to appointments in a primary care group practice”. Health Care Manag. Sci. 16(2): 101–118.
Parker, V. A., W. H. Wubbenhorst, G. J. Young, K. R. Desai, and M. P. Charns. 1999. “Implementing quality improvement in hospitals: The role of leadership and culture”. Am. J. Med. Qual. 14(1): 64–69.
Pavlov, A. and M. Bourne. 2011. “Explaining the effects of perfor- mance measurement on performance: An organizational routines perspective”. Int. J. Oper. Prod. Manag. 31(1): 101–122.
Pfeffer, J. and R. I. Sutton. 1999. “Knowing “what” to do is not enough: Turning knowledge into action”. Calif. Manage Rev. 42(1): 83–108.
Pham, H. H., M. Cohen, and P. H. Conway. 2014. “The pioneer account- able care organization model”. JAMA. 312(16): 1635–1636.
Pisano, G. P., R. M. J. Bohmer, and A. C. Edmondson. 2001. “Organi- zational differences in rates of learning: Evidence from the adoption of minimally invasive cardiac surgery”. Manage. Sci. 47(6): 752–768.
Plsek, P. E. 1999. “Quality improvement methods in clinical medicine”. Pediatrics. 103(1): 203–214.
The full text is available at http://dx.doi.org/10.1561/0200000039
References 149
Poon, E. G., D. Blumenthal, T. Jaggi, M. M. Honour, D. W. Bates, and R. Kaushal. 2004. “Overcoming barriers to adopting and implement- ing computerized physician order entry systems in U.S. Hospitals”. Health Aff. 23(4): 184–190.
Poon, E. G., J. L. Cina, and W. Churchill. 2006. “Medication dispensing errors and potential adverse drug events before and after implement- ing bar code technology in the pharmacy”. Ann. Intern. Med. 145(6): 426–434.
Poon, E. G., C. Keoane, and C. S. Yoon. 2010. “Effect of bar-code technology on the safety of medication administration”. N. Engl. J. Med. 362(18): 1698–1707.
Pronovost, P. J., D. Needham, S. M. Berenholtz, D. Sinopoli, H. Chu, S. Cosgrove, B. Sexton, R. Hyzy, R. Welsh, G. Roth, J. Bander, J. Kepros, and C. Goeschel. 2006. “An intervention to decrease catheter-related bloodstream infections in the ICU”. N. Engl. J. Med. 355(26): 2725–2732.
Radnor, Z. J., M. Holweg, and J. Waring. 2012. “Lean in healthcare: The unfulfilled promise?” Soc. Sci. Med. 74(3): 364–371.
Ratcliffe, A., W. Gilland, and A. Marucheck. 2011. “Revenue man- agement for outpatient appointments: Joint capacity control and overbooking with class-dependent no-shows”. Flex Serv. Manuf. J. 24(4): 516–548.
Rau, J. 2015. “Feds fine eight Maine hospitals over avoidable patient complications”. Available at: http://bangordailynews.com/2015/12/ 17/health/feds-fine-eight-maine-hospitals-over-avoidable-patient- complications/. [Accessed March 25, 2016].
Rawson, R. A., R. Gonzales, L. Greenwell, and M. Chalk. 2012. “Process- of-care measures as predictors of client outcome among a metham- phetamine-dependent sample at 12- and 36-month follow-ups”. J. Psychoactive Drugs. 44(4): 342–349.
Reiling, J. 2006. “Safe design of healthcare facilities”. Qual. Saf. Health Care. 15(Suppl 1): i34–i40.
Repenning, N. P. and J. D. Sterman. 2002. “Capability traps and self-confirming attribution errors in the dynamics of process im- provement”. Adm. Sci. Q. 47(2): 265–295.
The full text is available at http://dx.doi.org/10.1561/0200000039
150 References
Resar, R., P. J. Pronovost, C. Haraden, T. Simmonds, T. Rainey, and T. Nolan. 2005. “Using a bundle approach to improve ventilator care processes and reduce ventilator-associated pneumonia”. Jt. Comm. J. Qual. Patient Saf. 31(5): 243–248.
Rivard, P. E., V. A. Parker, and A. K. Rosen. 2013. “Quality improve- ment for patient safety: Project-level versus program-level learning”. Health Care Manage. Rev. 38(1): 40–50.
Robinson, L. W. and R. R. Chen. 2010. “A comparison of traditional and open-access policies for appointment scheduling”. Manuf. Serv. Oper. Manag. 12(2): 330–346.
Rosenthal, M. B. and R. A. Dudley. 2007. “Pay-for-performance: Will the latest payment trend improve care?” JAMA. 297(7): 740–744.
Rosenthal, M. B., R. Fernandopulle, H. R. Song, and B. E. Landon. 2004. “Paying for quality: Providers’ incentives for quality improvement”. Health Aff. 23(2): 127–141.
Rosenthal, M. B., R. G. Frank, Z. Li, and A. M. Epstein. 2005. “Early experience with pay-for-performance: From concept to practice”. JAMA. 294(14): 1788–1793.
Rozich, J. D., R. J. Howard, J. M. Justeson, P. D. Macken, M. E. Lindsay, and R. K. Resar. 2004. “Standardization as a mechanism to improve safety in health care”. Jt. Comm. J. Qual. Saf. 30(1): 5–14.
Rubin, H. R., P. Pronovost, and G. B. Diette. 2001. “The advantages and disadvantages of process-based measures of health care quality”. Int. J. Qual. Heal. Care. 13(6): 469–474.
Rubineau, B. and Y. Kang. 2012. “Bias in white: A longitudinal natural experiment measuring changes in discrimination”. Manage. Sci. 58(4): 660–677.
Ryckman, F. C., P. A. Yelton, A. M. Anneken, P. E. Kiessling, P. J. Schoettker, and U. R. Kotagal. 2009. “Redesigning intensive care unit flow using variability management to improve access and safety”. Jt. Comm. J. Qual. Patient Saf. 35(11): 535–543.
The full text is available at http://dx.doi.org/10.1561/0200000039
References 151
Saghafian, S., W. J. Hopp, M. P. van Oyen, J. S. Desmond, and S. L. Kronick. 2012. “Patient streaming as a mechanism for improving responsiveness in emergency departments”. Oper. Res. 60(5): 1080– 1097.
Samson, D. and M. Terziovski. 1999. “The relationship between total quality management practices and operational performance”. J. Oper. Manag. 17(4): 393–409.
Schmenner, R. W. and M. L. Swink. 1998. “On theory in operations management”. J. Oper. Manag. 17(1): 97–113.
Sehgal, A. R. 2010. “The role of reputation in U.S. News & World Report’s rankings of the top 50 American hospitals”. Ann. Intern. Med. 152(8): 521–525.
Senge, P. M. 1994. The Fifth Discipline?: The Art and Practice of the Learning Organization. New York, NY: Currency Doubleday.
Senot, C., A. Chandrasekaran, P. T. Ward, A. L. Tucker, and S. D. Moffatt-Bruce. 2016. “The impact of combining conformance and experiential quality on hospitals’ readmissions and cost performance”. Manage. Sci. 62(3): 829–848.
Sequist, T. D., A. M. Zaslavsky, R. Marshall, R. H. Fletcher, and J. Z. Ayanian. 2009. “Patient and physician reminders to promote colorectal cancer screening: A randomized controlled trial”. Arch. Intern. Med. 169(4): 364–371.
Shah, R., S. M. Goldstein, B. T. Unger, and T. D. Henry. 2008. “Ex- plaining anomalous high performance in a health care supply chain”. Decis. Sci. 39(4): 759–789.
Shah, R. and P. T. Ward. 2003. “Lean manufacturing: Context, practice bundles, and performance”. J. Oper. Manag. 21(2): 129–149.
Shannon, R. P., D. Frndak, N. Grunden, J. C. Lloyd, B. Patel, D. Cummins, A. H. Shannon, P. H. O’Neill, and S. J. Spear. 2006. “Using real-time problem solving to eliminate central line infections”. Jt. Comm. J. Qual. Patient Saf. 32(9): 479–487.
Shortell, S. M., J. L. O’Brien, J. M. Carman, R. W. Foster, E. F. Hughes, H. Boerstler, and E. J. O’Connor. 1995. “Assessing the impact of continuous quality improvement/total quality management: Concept versus implementation”. Health Serv. Res. 30(2): 377–401.
The full text is available at http://dx.doi.org/10.1561/0200000039
152 References
Shwartz, M., A. B. Cohen, J. D. Restuccia, Z. J. Ren, A. Labonte, C. Theokary, R. Kang, and J. Horwitt. 2011. “How well can we identify the high-performing hospital?” Med. Care Res. Rev. 68(3): 290–310.
Sinha, K. K. and E. J. Kohnke. 2009. “Health care supply chain design: Toward linking the development and delivery of care globally”. Decis. Sci. 40(2): 197–212.
Skinner, W. 1974. “The focused factory”. Harv. Bus. Rev. 52(3): 113– 122.
Skinner, W. 1986. “The productivity paradox”. Manage. Rev. 75(9): 41–45.
Smith, A. 1776. An Inquiry into the Nature and Causes of the Wealth of Nations. London, UK: George Routledge and Sons.
Smith-Daniels, V. L., S. B. Schweikhart, and D. E. Smith-Daniels. 1988. “Capacity management in health care services: Review and future research directions”. Decis. Sci. 19(4): 889–919.
Sodhi, M. S. and C. S. Tang. 2014. “Supply-chain research opportunities with the poor as suppliers or distributors in developing countries”. Prod. Oper. Manag. 23(9): 1483–1494.
Song, H., A. L. Tucker, and K. L. Murrell. 2015. “The diseconomies of queue pooling: An empirical investigation of emergency department length of stay”. Manage. Sci. 61(12): 3032–3053.
Song, H., A. L. Tucker, K. L. Murrell, and D. R. Vinson. 2016. “Pub- lic relative performance feedback: Improving worker productivity through adoption of coworkers’ best practices”. Working paper.
Soorapanth, S. and S. E. Chick. 2013. “Assessing prevention for positives: Cost-utility assessment of behavioral interventions for reducing HIV transmission”. In: Operation Research and Health Care Policy. Ed. by G. S. Zaric. New York, NY: Springer New York. 157–178.
Soremekun, O. A., C. Terwiesch, and J. M. Pines. 2011. “Emergency medicine: An operations management view”. Acad. Emerg. Med. 18(12): 1262–1268.
Sousa, R. and C. A. Voss. 2002. “Quality management re-visited: A reflective review and agenda for future research”. J. Oper. Manag. 20(1): 91–109.
The full text is available at http://dx.doi.org/10.1561/0200000039
References 153
Spath, P. L. 2011. “Reducing errors through work system improve- ments”. In: Error Reduction in Health Care: A Systems Approach to Improving Patient Safety, 2nd edition. Ed. by P. L. Spath. San Francisco, CA: Jossey–Bass. 199–234.
Spear, S. J. 2005. “Fixing health care from the inside, today”. Harv. Bus. Rev. 83: 78–91.
Spear, S. J. and H. K. Bowen. 1999. “Decoding the DNA of the Toyota production system”. Harv. Bus. Rev. 77(5): 96–106.
Strandberg–Larsen, M. and A. Krasnik. 2009. “Measurement of inte- grated healthcare delivery: A systematic review of methods and future research directions”. Int. J. Integr. Care. 9: e01.
Sun, P. R., B. H. Wang, and F. Wu. 2008. “A new method to guard inpatient medication safety by the implementation of RFID”. J. Med. Syst. 32(4): 327–332.
Szulanski, G. 1996. “Exploring internal stickiness: Impediments to the transfer of best practice within the firm”. Strateg. Manag. J. 17: 27–43.
Taylor, M. J., C. McNicholas, C. Nicolay, A. Darzi, D. Bell, and J. E. Reed. 2014. “Systematic review of the application of the plan-do- study-act method to improve quality in healthcare”. BMJ Qual. Saf. 23(4): 290–298.
Teno, J. M., V. Mor, N. Ward, J. Roy, B. Clarridge, J. E. Wennberg, and E. S. Fisher. 2005. “Bereaved family member perceptions of quality of end-of-life care in US regions with high and low usage of intensive care unit care”. J. Am. Geriatr. Soc. 53(11): 1905–1911.
The Advisory Board Company. 2014. “Moody’s: Not-for-profit Hospital Margins Fall to 2.2. Dly. Brief.” Available at: http://www.advisory. com/daily-briefing/2014/04/25/moodys-not-for-profit-hospital- margins-fall.
Theokary, C. and Z. J. Ren. 2011. “An empirical study of the relations between hospital volume, teaching status, and service quality”. Prod. Oper. Manag. 20(3): 303–318.
Thompson, D. N., G. A. Wolf, and S. J. Spear. 2003. “Driving improve- ment in patient care”. J. Nurs. Adm. 33(11): 585–595.
The full text is available at http://dx.doi.org/10.1561/0200000039
154 References
Thompson, J. D. 1967. Organizations in Action: Social Science Bases of Administrative Theory. New York, NY: McGraw-Hill.
Toussaint, J., R. A. Gerard, and E. Adams. 2010. On the Mend: Rev- olutionizing Healthcare to Save Lives and Transform the Industry. Cambridge, MA: Lean Enterprise Institute.
Tubbs, M. E. 1986. “Goal setting: A meta-analytic examination of the empirical evidence”. J. Appl. Psychol. 71(3): 474–483.
Tucker, A. L. 2013. “Learning about reducing hospital mortality at Kaiser Permanente”. Harvard Bus. Sch. Case: 612–93.
Tucker, A. L. and J. A. Berry. 2010. “Patient flow at Brigham and Women’s Hospital (A)”. Harvard Bus. Sch. Case: 9–608–171.
Tucker, A. L. and A. C. Edmondson. 2009. “Cincinnati Children’s Hospital Medical Center”. Harvard Bus. Sch. Case: 9–609–109.
Tucker, A. L., A. C. Edmondson, and S. J. Spear. 2002. “When problem solving prevents organizational learning”. J. Organ. Chang. Manag. 15(2): 122–137.
Tucker, A. L., I. M. Nembhard, and A. C. Edmondson. 2007. “Imple- menting new practices: An empirical study of organizational learning in hospital intensive care units”. Manage. Sci. 53(6): 894–907.
U. S. Senate. 2010. “Patient Protection and Affordable Care Act”. In: H.R. 3590 – 111th Congress.
Uhlig, P. and W. E. Raboin. 2015. Field Guide to Collaborative Care: Implementing the Future of Health Care. Overland Park, KS: Oak Prairie Health Press.
United Nations. 2014. The Millennium Development Goals Report 2014. Valentijn, P. P., S. M. Schepman, W. Opheij, and M. A. Bruijnzeels.
2013. “Understanding integrated care: A comprehensive conceptual framework based on the integrative functions of primary care”. Int. J. Integr. Care. 13(Mar.): e010.
Verma, D. and K. K. Sinha. 2002. “Toward a theory of project inter- dependencies in high tech R&D environments”. J. Oper. Manag. 20(5): 451–468.
The full text is available at http://dx.doi.org/10.1561/0200000039
References 155
Vest, J. R. and L. D. Gamm. 2009. “A critical review of the research literature on Six Sigma, lean and studergroup’s hardwiring excellence in the United States: The need to demonstrate and communicate the effectiveness of transformation strategies in healthcare”. Implement. Sci. 4: 35.
Vogus, T. J., K. M. Sutcliffe, and K. E. Weick. 2010. “Doing no harm: Enabling, enacting, and elaborating a culture of safety in health care”. Acad. Manag. Persp. 24(4): 60–77.
Vroom, V. H. 1964. Work and Motivation. New York, NY: Wiley. Walshe, K. 2009. “Pseudoinnovation: The development and spread of
healthcare quality improvement methodologies”. Int. J. Qual. Heal. Care. 21(3): 153–159.
Wang, F. K., C. H. Hsu, and G. H. Tzeng. 2014. “Applying a hybrid MCDM model for Six Sigma Project selection”. Math. Probl. Eng. 2014: 1–13.
Weber, E. J., S. Mason, A. Carter, and R. L. Hew. 2011. “Emptying the corridors of shame: Organizational lessons from England’s 4-hour emergency throughput target”. Ann. Emerg. Med. 57(2): 79–88.
Weiser, T. G., A. B. Haynes, A. Lashoher, G. Dziekan, D. J. Boorman, W. R. Berry, and A. Gawande. 2010. “Perspectives in quality: De- signing the WHO surgical safety checklist”. Int. J. Qual. Heal. Care. 22(5): 365–370.
Whippy, A., M. Skeath, B. Crawford, C. Adams, G. Marelich, M. Alamshahi, and J. Borbon. 2011. “Kaiser Permanente’s performance improvement system, part 3: Multisite improvements in care for patients with sepsis”. Jt. Comm. J. Qual. Patient. Saf. 37(11): 483– 493.
White, D. L., C. M. Froehle, and K. J. Klassen. 2011. “The effect of integrated scheduling and capacity policies on clinical efficiency”. Prod. Oper. Manag. 20(3): 442–455.
White, F. M. and E. A. Locke. 1981. “Perceived determinants of high and low productivity in three occupational groups: A critical incident study”. J. Manag. Stud. 18(4): 375–388.
The full text is available at http://dx.doi.org/10.1561/0200000039
156 References
Wohlauer, M. V., V. M. Arora, L. I. Horwitz, E. J. Bass, S. E. Mahar, and I. Philibert. 2012. “The patient handoff: A comprehensive curricular blueprint for resident education to improve continuity of care”. Acad. Med. 87(4): 411–418.
Wolff, A. M., S. A. Taylor, and J. F. McCabe. 2004. “Using checklists and reminders in clinical pathways to improve hospital inpatient care”. Med. J. Aust. 181(8): 428–431.
Womack, J. P. and D. T. Jones. 1996. Lean Thinking: Banish Waste and Create Wealth in your Corporation. New York, NY: Simon and Schuster.
Wright, P. D., K. M. Bretthauer, and M. J. Côté. 2006. “Reexamining the nurse scheduling problem: Staffing ratios and nursing shortages”. Decis. Sci. 37(1): 39–70.
Wu, R. C., V. Lo, D. Morra, B. M. Wong, R. Sargeant, K. Locke, R. Cavalcanti, S. D. Quan, P. Rossos, K. Tran, and M. Cheung. 2013. “The intended and unintended consequences of communication systems on general internal medicine inpatient care delivery: A prospective observational case study of five teaching hospitals”. J. Am. Med. Inform. Assoc. 20(4): 766–777.
Wullink, G., M. van Houdenhoven, E. W. Hans, J. M. van Oostrum, M. van der Lans, and G. Kazemier. 2007. “Closing emergency operating rooms improves efficiency”. J. Med. Syst. 31(6): 543–546.
Xiao, Y., S. Schenkel, S. Faraj, C. F. Mackenzie, and J. Moss. 2007. “What whiteboards in a trauma center operating suite can teach us about emergency department communication”. Ann. Emerg. Med. 50(4): 387–395.
Yang, Y., J. van den Broeck, and L. M. Wein. 2013. “Ready-to-use food- allocation policy to reduce the effects of childhood undernutrition in developing countries”. Proc. Natl. Acad. Sci. U.S.A. 110(12): 4545–4550.
Yao, W., C. H. Chu, and Z. Li. 2012. “The adoption and implementation of RFID technologies in healthcare: A literature review”. J. Med. Syst. 36(6): 3507–3525.
The full text is available at http://dx.doi.org/10.1561/0200000039
References 157
Ye, C., G. Browne, V. S. Grdisa, J. Beyene, and L. Thabane. 2012. “Mea- suring the degree of integration for an integrated service network”. Int. J. Integr. Care. 12(Sept.): e137.
Young, T. P. and S. I. McClean. 2008. “A critical look at lean thinking in healthcare”. Qual. Saf. Health Care. 17(5): 382–386.
Yu, W. D., P. Ray, and T. Motoc. 2008. “WISH: A wireless mobile multimedia information system in healthcare using RFID”. Telemed. J. E. Health. 14(4): 362–370.
Zacharias, C. and M. Pinedo. 2014. “Appointment scheduling with no-shows and overbooking”. Prod. Oper. Manag. 23(5): 788–801.
Zander, U. and B. Kogut. 1995. “Knowledge and the speed of the transfer and imitation of organizational capabilities: An empirical test”. Organ. Sci. 6(1): 76–92.
Zarbo, R. J., J. M. Tuthill, R. D’Angelo, R. Varney, B. Mahar, C. Neuman, and A. Ormsby. 2009. “The Henry Ford production system: Reduction of surgical pathology in-process misidentification defects by bar code-specified work process standardization”. Am. J. Clin. Pathol. 131(4): 468–477.
Zepeda, E. D. and K. K. Sinha. 2016. “Toward an effective design of behavioral health care delivery: An empirical analysis of care for depression”. Prod. Oper. Manag. 25(5): 952–967.
Zhang, B., A. A. Wright, H. A. Huskamp, M. E. Nilsson, M. L. Maciejew- ski, C. C. Earle, S. D. Block, P. K. Maciejewski, and H. G. Prigerson. 2009. “Health care costs in the last week of life: Associations with end-of-life conversations”. Arch. Intern. Med. 169(5): 480–488.
Zhang, W., A. V. Hill, R. G. Schroeder, and K. W. Linderman. 2008. “Project management infrastructure: The key to operational perfor- mance improvement”. Oper. Manag. Res. 1(1): 40–52.
Zu, X., L. D. Fredendall, and T. J. Douglas. 2008. “The evolving theory of quality management: The role of Six Sigma”. J. Oper. Manag. 26(5): 630–650.
The full text is available at http://dx.doi.org/10.1561/0200000039
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- Introduction
- Framework for Performance Improvement in Health Care Organizations
- An Overview of the U.S. Health Care System
- The Need for a Health Care-Specific Framework
- Introduction to Key Operations Management Concepts in Performance Improvement
- Summary
- Model of Transformational Performance Improvement
- Overview of the Model
- Other Models of Improvement in Health Care
- Summary
- Determining and Communicating a System-Level Goal
- Developing System-Level Goals
- Operations Management Literature Related to System-Level Goals: Operational Focus
- Summary
- Developing and Using System-Level Measures of Performance
- Considerations in Developing Performance Measures
- Operations Management Literature Related to Performance Measures: Health Information Technology
- Summary
- Understanding and Managing Interdependencies
- Considerations in Understanding and Managing Interdependencies
- Operations Management Literature Related to Interdependence: Patient Flow
- Summary
- Selecting a Portfolio of Projects Aligned with System-Level Goals
- Aligning Projects with Objectives in Health Care Organizations
- Operations Management Literature Related to a Portfolio of Improvement Projects: Appointment Scheduling
- Summary
- Creating an Engine for Improvement
- Four Aspects of Creating an Improvement Engine
- Operations Management Literature Related to Total Quality Management, Lean, and Six Sigma
- Summary
- Implementing, Spreading, and Sustaining Improvements
- Facilitating the Spread of Best Practices
- Operations Management Literature Related to Spread and Sustainability
- Summary
- Common Barriers to Successful Performance Improvement
- Barriers Related to the External Context
- Barriers Within the Organization
- Barriers Related to the Implementation Process
- Barriers Related to the Improvement Project
- Summary
- Future Directions in Research on Performance Improvement in Health Care Organizations
- Opportunities for Research Related to the Impact of External Environment On Performance Improvement
- Opportunities for Research Related to Performance Improvement Within Organizations
- Summary
- Conclusion
- Acknowledgements
- References
