Resource Sharing in the Healthcare Environment

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Resource Sharing in the Healthcare

Environment

An Operations Management Approach

at the Radiology Department of the Nij Smellinghe Hospital

I.A. van der Weide

(s1579436)

Groningen, October 2008

University of Groningen

Faculty of Economics and Business

Technology Management

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University of Groningen

Supervisor: Dr. J.T. van der Vaart

Co-Assessor: Drs.Ing. J. Drupsteen

Nij Smellinghe Hospital

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Preface

This Master Thesis finalizes my journey through the academic world at the University of Groningen. Three years ago, I could not have imagined which impact the decision to undertake the course of Technology Management could have, but I now know that it was worth it. I have met some inspiring people throughout this study programme, and I have participated in many challenging assignments in a variety of environments. This thesis was conducted in one of the most interesting environments I could have been in: the Healthcare environment. It is in this preface that I wish to express my gratitude to those who enabled me to complete this Master Thesis.

My first gratitude goes out to my supervisors who have continuesly supported me in conducting my thesis. My first supervisor Dr. Taco van der Vaart, associate professor, came with the initial idea to study the phenomena of shared resources at the Nij Smellinghe hospital and introduced me to my second supervisor and my co-assesor. His feedback has steered my thesis towards a more academic level, which can be easily lost when confronted with practical applications of theory. My co-assesor, Drs.Ing. Justin Drupsteen, phd-student, introduced me to the subject of shared resources, as he was already working on a PhD thesis within this context. My thesis was also ment to provide him a more practical insight into the actual usage of shared resources, so that he can start his case studies with better knowledge of the empirical details. Your enthusiasm about the subject and the practical implications, as well as, your feedback and discussions have helped me a lot and I hope my thesis supports you in completing your PhD-degree. My second supervisor Pieter Buwalda, head of Logistics, has introduced me to the Nij Smellinghe hospital of Drachten and the department of Radiology in which my cases were conducted. His knowledge of applied hospital logistics has guided me in many ways in optimizing my thesis, as did his tremendous amount of enthusiasm and positive feedback.

Further, I wish to thank the people of the Radiology department which I have seen a lot throughout this research. First and foremost I wish to thank Lenie Wilms, teamleader of the department of Radiology, for her great help in unraveling the different systems, medical jargon, technology, schematics and details I were confronted with at the Radiology department, as well as, the social time at the running track. Also, I wish to thank Mathilde Hommes, head of Radiology, for providing me the opportunity to conduct research at her department, and for the interviews and discussions we had. Further, this thesis would not have been completed if it wasn’t with the great help of all the technologists and receptionists, who allowed me to have a look at their daily work and ask questions whenever I wanted. This also concerns some people outside the department of Radiology, who were very helpful in providing answers for my questions. Special thanks go out to Eric Annema, IT-specialist, who has helped me a lot in accessing the Radiology data, which was far from straightforward.

Outside the hospital I could count on a group of fellow-students who were sharing the same enthusiasm about their master thesis as me. In this respect, my gratitude goes out to Herman, Ruurd, Nick, Joost, and, Laura; especially for the great Friday afternoon revivers we have had! I really feel that we have helped eachother a lot in finalizing our theses, and I surely hope that this is not the end of our great time.

Finally, my sincere gratitude goes out to my parents and my girlfriend who have always supported me in my choices, of which this journey is but one.

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Abstract

This master thesis approached the subject of shared resources within the healthcare environment. The research goal was stated as follows: “to determine how [a selection of] shared resources within

the department of Radiology influence the patient lead time performance”. Successively, this thesis

was intended to provide a better understanding about how hospitals manage their shared resources. The Nij Smellinghe hospital enabled this research by providing a real-world problem context, which concerned their department of Radiology. Obviously, this department and its modalities form a major shared resource, which influences the lead time performance of almost any patient within the hospital. As the Radiology department encountered lead time problems with their Magnetic Resonance Imaging (MRI) equipment, as well as, their Ultrasonographic (US) instruments, it was decided to use these as the main shared resources for conducting this thesis. Additionally, the Bucky modality was also approached, as its characteristics were different from the other resources involved. The counteraction concerned the provision of recommendations for the Radiology department, which should enable them to understand and manage their lead time problems.

In order to address the real-world context, an operations management approach was taken. The function of planning and control was taken as the main determinant for the performance of shared resources and its effect on the patient lead time. This led to a distinction into the characteristics of demand, the characteristics of supply, and the management objectives per shared resource. These elements were described for each modality, as well as, the means by which planning and control was conducted and its effect on the patient service level and the resource efficiency.

For each analyzed modality the author has made a number of recommendations which provides the department of Radiology with a sensible direction to improve their operations management. The main recommendations of this research are the implementation of aggregated demand and capacity plans, frequent sampling of current performance in terms of service levels and resource utilizations, the formulation of more detailed management objectives, and the introduction of an IT-enabler which is able to access the Radiology Information System (RIS) data automatically so that it can be used for management purposes.

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1. Introduction

1.1 Introduction

Dutch hospitals are facing an ever growing need for patient care, directed by a strong (national) emphasis on medical and organisational efficiency, as well as, higher patient expectations on the hospital’ service delivery. Therefore, they find themselves in a constant urge for care-focused and patient-centred reorganisations and refinements. The emerging paradigm shift away from the traditional clinicians-centred structuring of the hospital delivery processes has been widely discussed in literature1. As a consequence, these developments –among others– force the hospital’s management to re-asses the balance between patient service levels and the operational costs in order to satisfy patient needs against reasonable expenditure. Hence, healthcare managers find themselves in the midst of a struggle between service and efficiency, imposing considerable demands on the hospital resources and the underlying operations management processes incurred.

In many cases, different categories of patients make a combined use of certain hospital resources (e.g. diagnostic equipment, nursing staff, medical supplies, etcetera). These resources are labelled shared resources and impose considerable demands upon the operations management function. By that means, the question arises: how do hospitals manage their shared resources? This thesis will approach this subject at the Radiology department of the Nij Smellinghe hospital, by investigating the relation between the planning and control of shared resources and the patient lead-time performance.

1.2 Research Motivation

In order to finish the masters’ degree in Technology Management at the University of Groningen a graduation project has to be completed. The author’s interest went out to a subject within operations management in a health care environment. The initial idea to commence this research came from Dr. Taco van der Vaart and Drs.Ing Justin Drupsteen who perform research on the subject of shared resources in general and in health care applications. They are interested in the application of resource sharing within a real/world hospital environment and the effects on the patient lead-time performance. In order to access a real-world case Mr. Pieter Buwalda, head of logistics at the hospital of Nij Smellinghe, was approached to facilitate this research project. His interest went out to a focus on the Radiology department as difficulties are perceived concerning the patient lead times. Ultimately, this thesis should provide Nij Smellinghe with a better understanding of the consequences of certain planning and control decisions on the patient lead-time performance, which could support them in identifying a sensible way to proceed their operational refinements.

1.3 The Research Purpose

The research purpose is stated as follows:

“to determine how [a selection of] shared resources within the department of Radiology influence the patient lead time performance“

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2. Research Design

In order to logically construct a clearly defined and recoverable master thesis, this research design is ordered according to the epistemology used, being the set of ideas and the process by which they are used. Checkland (1985) defines these elements of research as (1) the area of concern, (2) the framework of ideas and (3) the methodology (see Figure 1).

Figure 1 - Elements of Research (Checkland, 1985)

The following sections will successively discuss these elements. Firstly, section 2.2 addresses the area of concern which is formed by current developments in the Dutch healthcare environment and the importance of operations management in relation with shared resources. Secondly, section 2.3 introduces a framework of ideas, which consists of background theory relevant to the area of concern, as well as, an outline of the research approach used. Finally, section 2.4 describes the methodology which is used to conduct the analysis and generate results.

2.2 Area of Concern

This section addresses the problem context in which the subject of this thesis is embedded. It is assumed that the care delivery processes of the Dutch hospitals are open systems and, as such, are influenced and shaped by their environment. This environment imposes pressure for changes upon the health care industry, of which the new reimbursement system (section 2.2.1) is but one. In order to manage the (changes in) health care processes, operations management provides a useful perspective which is introduced in section 2.2.2. Hereafter, the role of shared resources within the healthcare operations is portrayed in section 2.2.3. The final section will conclude with the focus and intensions of this thesis, as well as, its position within the area of concern.

2.2.1 Dynamics of the Dutch Health Care Industry: Implications of the New Reimbursement System Traditionally, Dutch hospitals are private institutions operating on a non-profit basis, being financed by the national government in which insurers, unions, and employers play an intermediate role. This health care system has been built2 in the early years of the 20th century and has seen little changes for years. However, starting from the early 1990s, the health care environment is becoming increasingly turbulent as a result of several factors, such as -among others- (1) encouragement of competition by the government, (2) the shifting balance of power from clinicians to managers, and (3) increased cost consciousness on the part of the government. In addition, according to Lega & DePietro (2005)

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changes are enacting on the clinical level (i.e. new developments and technologies, e.g. minimal invasive surgery and interventional radiology) as well as the professional level (e.g. an emphasis on competence rather than credentials; the transformation of the nursing profession, etcetera).

One of the most important changes is the introduction of a new health reimbursement system by the national government, providing transparency of hospital and specialist care, forcing increased efficiency, and facilitating regulated competition between health care providers (Oostenbrink & Rutten, 2006). This new financing system is based on the diagnoses and treatment combinations (Dutch abbreviation: DBC), especially geared towards those treatment combinations found on waiting lists. A DBC includes all services and activities in a hospital associated with the patient’s demand for care, covering the diagnosis, treatment and nursing functions involved. This financing system introduces a market-oriented reform as hospitals and health insurers have to negotiate about the price, quality and volume of these services and activities. Although currently about 80% of the diagnosis and treatment combinations (segment A treatments) are still financed by a -traditional- closed tariff, a growing amount of DBCs (segment B currently holds app. 20%) has to be negotiated with the health insurers and comprise highly straightforward cases, such as hip and knee arthritis imposing stable, predictable prices.

The impact of the new reimbursement system on the health care quality in terms3 of hospital efficiency, the clinical effectiveness and the patient-centeredness has been widely discussed. Although the governmental forces towards cost containment do not necessarily lead to low cost strategies, it is evident that cost consciousness has its impact on the hospital management. Starting with the former, the hospital efficiency, Oostenbrink & Rutten (2006) state: “it is beyond doubt that the introduction of DBCs has increased awareness for the output and efficiency of hospital and medical specialist care”. Thus, providing a rationale for the introduction of various operational reengineering programs or interventions, such as -among others- changes in (1) process sequences, (2) organisation of processes, (3) physical structure, (4) staff organization and (5) capacity planning. Most often objectives in these efficiency related investments are aimed at the reduction of costs and/or the improvement of resource utilization. In addition, as the DBC system is related to the actual activities performed per patient case, efficiency related investment could also specifically be found in those activities not related to a certain case, such as (1) unnecessary tests, (2) reduction of length of stay, (3) reduction of overhead costs (e.g. central computer infrastructure) and the like. Secondly, the effects on the clinical effectiveness are found doubtful by Custers et al (2007) as they argue that the new reimbursement system is output-related (i.e. volume) instead of outcome-output-related (i.e. quality) implying an ambiguous impact on the clinical effectiveness, since “the incentive is less clear with regard to reducing medical errors and the associated costs … of complications”. Objectives within this dimension are probably aimed at the medical outcomes itself and the medical knowledge and technologies available. Thirdly, the aspect of patient centeredness, aimed at the identification of patient preferences, needs, and values and subsequent clinical decision-making based on these variables is potentially induced by the new reimbursement system, as hospitals could attract patients by providing premium services and build up a good reputation within this dimension. However, as health care insurers are the primary customers of hospital care, they need to provide financial incentives or introduce selective contracting in order to trigger these developments (Custers et al, 2007). In contrast, when patients increasingly support a certain hospital, as a result of an excellent image, it may well force insurance companies to abide by these requests and provide the financials needed. Objectives within this dimension are probably aimed at the identification of patient satisfaction, as this is dubbed an important factor of the patient service

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level or patient centeredness. It provides a rationale for hospitals to obtain information regarding patient’ perceptions of (1) nursing care, (2) physician’s care, (3) performance of service, and (4) complaint management (Dufrene, 1999).

In general, it is evident that the changes in the hospital environment are affecting the hospitals behaviour towards the quality of health care in terms of the hospital efficiency, the clinical effectiveness and the patient-centeredness. Hence, there is a compelling need for health care managers to focus on efficiency, effectiveness and patient-centeredness in order to satisfy the numerous stakeholders, of which the patient is only one.

2.2.2 Complexity and Decomposition of Health Care Processes

While hospital managers are reconsidering their strategy, structures and processes, logistical concepts from other industries are held potentially successful in the hospital setting. This apparent match can be easily explained as these logistical principles are widely known for their successful applications in many world-class companies, operating in turbulent environments against fierce competition. Consequently, it becomes tempting to approach the health delivery process in terms of logistical concepts, of which MRP, BRP and JIT are just a few. However, a closer examination of the principles underlying these logistical principles show that they all hold specific assumptions of reality; two examples of the latter are MRP-I implicitly assuming infinite capacity and JIT assuming a steady rate and mix of production. Hence, there cannot be a simple selection, as Hopp & Spearman (2000, pp 182) note: “each firm is on its own to develop an effective manufacturing strategy, support it with appropriate policies and procedures, and continue to improve these over time”. In order to get some basic insight in the complexity of the hospital system, the next paragraphs will approach this system from a logistical perspective.

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Figure 2 - Logistical approach of hospital complexity (derived from Vissers & de Vries, 2005)

According to Bertrand, Wortmann & Wijngaard (1998), the usage of decomposition leads to a new form of complexity, since the interdependencies between the decomposed units and systems still need to be coordinated. An example is the coordination of sequentional operations between different functional units (e.g. transportation of patients from the ward to the operating room). This form of complexity also arises when demand is decomposed into several specialties and certain groups of patients. Interdependencies still exists among these decomposed groups, as they share functional units (and the underlying resources) within the hospital sub-functions. Hence, decisions have to be made regarding the allocation of resources towards the different medical specialties and the patient groups defined.

From the perspective of a focused factory4 (Skinner, 1974), the choice on how to allocate the hospital resources to the different patient groups would be rather straightforward, as every patient group gets its own dedicated set of resources. In its most extreme form, this would result in separated, focused ‘hospital’ systems, of which specialized eye-laser clinics are familiar examples. These specialty hospitals are perceived to have a relative advantage in terms of lower costs, scheduling efficiencies, and shorter waiting times (Yang et al, 1992). The apparent advantages of this approach can be easily explained, as interdependencies with other patient groups are effectively removed.

However, many rural hospitals are not able to provide the number of patients needed for a focused setting, which would result in under-utilized hospital resources. Therefore, sharing of functional units (and the resources) by different patient groups is needed to level overcapacity/undercapacity. Additionally, combining demand towards certain functional units may yield scale advantages, as greater patient volumes could lead to advantageous in terms of efficiency and synergy effects (e.g. specialisation of staff). Concluding, hospital systems often have to abide by the sharing of functional units and the underlying resources as a result of the insufficient patient volumes available for a dedicated configuration.

2.2.3 Uncertainty, Shared Resources and Performance

Apart from the considerable amount of complexities found in the health care processes, the hospital system does also hold a great amount of uncertainty. Here, uncertainty refers to the state of an individual (manager) who finds him/her to be lacking information about the environment. Within operations management, one often refers to variability as the numeretical quantity of uncertainty. The hospital system is affected by different forms of variability. Firstly, clinical variability is caused by the uncertainties found in the clinical trajectories of the patients, as well as, in the length of stay or the

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duration of examinations within these trajectories. Secondly, as patients most often arrive in a stochastic fashion rather than deterministic, this results in flow variability. Thirdly, not every hospital facility would provide care in the same, uniform manner comprising professional variability. Finally, as hospital managers and clinicians try to confine all these forms of variability by decomposition into patient groups, predictable treatment paths, and control mechanisms; a fourth form of variability could arise, coined artificial variability by Litvak & Long (2000), resulting from “dysfunctional operations management“. This artificial variability is a direct result of managerial decisions and therefore controllable form of variation. In contrast, the other forms of variability are caused by chance or randomness and follows from events beyond our immediate control. According to Bertrand, Wortmann & Wijngaard (1998), these uncontrollable forms of variability can only be dampened by providing flexibility of some sort (e.g. cross-functional teams, overcapacity, etc).

One important decision underlying the healthcare operations management concerns the application of shared resources within the hospital system. This sharing decision may hold forms of artificial variability, as it could affect the overall performance of the hospital system. As Broekhuis & Van der Vaart (2005) note: “shared resources seriously complicate the effective control of the flows of patients and hamper the achievement of high service levels”. From an operations management perspective, the rule is that shared resources should be avoided unless the advantages like economics of scale and the possibility to smooth overcapacity/undercapacity outweigh significant adverse aspects like complexity of control, creation of stocks, longer lead times, reduction of flexibility, the efficiency of the shared resource, and the integral effect on the overall service delivery (Hoekstra & Romme, 1992; Van der Vaart & Van Donk, 2006). However, as hospital functions are typically decomposed into functional units (e.g. wards, radiology departments, intensive care), the sharing of the underlying resources is very common for hospital operations. Additionally, rural hospitals often do not possess the volumes needed for dedicating resources to certain groups of patients. Therefore, the management of shared resources plays an important role within the overall health care operations, as its adverse aspects could seriously hamper the overall performance of the hospital system. As Kusters & Groot (1996) note: “the many factors involved in controlling a speedy throughput of patients on the one hand and the optimal use of scarce resources on the other makes this a ‘wicked’ problem”.

2.2.4 Focus of this Master Thesis

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2.3 Framework of Ideas

Now that the problem domain has been portrayed, it is necessary to outline this thesis in a more precise setting. This section introduces the theoretical background relevant to the subject at hand, and thereafter provides the set of variables which are used during the case study approach.

2.3.1 Theory of Shared Resources

The first definition of the concept of shared resources within a logistical context was provided by Hoekstra & Romme (1992) who defined the concept as “a common-capacity source in the chain of two or more different product-market combinations”. This concept was explained as a functionally organized link in a (process oriented) manufacturing process. In 2004, Van der Vaart & Van Donk extended this concept with an external outlook, as they approached the concept from the perspective of Supply Chain Management (SCM). They refined the definition as follows: “a common-capacity source in two or more supply chains or networks”. In a series of papers Van der Vaart & Van Donk (2004a, 2004b, 2005) developed a theory for understanding the influence of shared resources on integration practises within SCM. Their major assumption is that shared resources will be a barrier for integration, which especially poses a problem in the case of highly uncertain business conditions. Within these uncertain conditions it is proposed to apply the concept of buyer focus (Griffiths, James & Kempson, 2000), which basically means that resources are allocated to a specific buyer along the whole range of his products. Figure 3 gives an overview of the suggested relationships between the type of allocation, the level of uncertainty and the characteristics of the network. What follows are basically two extreme configurations of the network characteristics.

Figure 3 - Characteristics of the network and the allocation of resources (derived from Van der Vaart & Van Donk, 2004)

On one extreme, low levels of environmental uncertainty result in a focus towards cost-containment, in which Make-To-Stock (MTS) production should lead to highly utilized resources. Within these networks it is expected that the manufacturing technology is characterised by mass production, and that high levels of integration are not required given the focus on cost-containment. Consequently, it is argued that shared resources are not necessarily a problem, as integration towards the buyer is not required. Further, inventories are used to maintain speed of delivery when demanded.

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the required capacity and flexibility, the concept of buyer focus is suggested as it reserves necessary capacity for the right buyer. Obviously, this configuration corresponds with a high level of integration.

In a series of empirical studies, evidence was found that shared resources limit the level of integration. In addition, some uncertain networks did consist of shared resources, which were expected to use some form of time- or capacity-buffers in order to meet flexibility. Especially in these circumstances, the sharing of information seemed crucial. Finally, while discussing this model, Van der Vaart & Van Donk (2004b) suggest that other configurations probably exist as well, between the extreme configurations outlined.

The theory presented gives an interesting perspective on the role of shared resources within a network of parties, as well as, the apparent inability to cope with environmental uncertainty. However, a major difference between manufacturing- and hospital-systems comprises the fact that patients are to be served, instead of products delivered. Therefore, inventories cannot be used as a buffer against uncertainty. The other factors concerned (e.g. order-winners, technology) may prove useful to this research, and will be explored. The logic behind this theory will be used for discussing the outcome of this thesis.

2.3.2 The Function of Planning and Control

The goal of this thesis refers to the impact of shared resources on the lead-time performance of the patient. For this matter, the function of planning and control is concerned, as this function basically determines how resources are managed, and -consequently- the successive outcome in terms of performance (e.g. time, efficiency, etc.). Planning and control can be defined as “the reconciliation of the potential of the operation to supply products and services, and the demands of its customers on the operation” (Slack et al, 1998). The purpose of planning and control as defined by Slack et al (1998) is to ensure that the operation runs effectively and efficiently and produces products and services as required by customers. In order to do this, as stated by Slack et al, the resources of the operation should be available (1) in the appropriate quantity, (2) at the appropriate time, and (3) at the appropriate level of quality.

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General Distinctions Slack et al (1998) Framework Vissers et al (2001) Long-term Planning and Control

• Uses aggregated demand forecasts

• Determines resources in aggregated form

• Objectives set in largely financial terms

Strategic Planning (2-5 yrs)

• Contracted annual patient volumes

• Target service levels

Patient Volumes Planning and Control (1-2 yrs)

• Amount of resources available at annual level

• Regulations regarding resource-use

Medium-term Planning and Control

• Uses partially disaggregated demand forecasts

• Determines resources and contingencies

• Objectives set both financial and operations terms

Resources Planning and Control (3mth-1yr)

• Time-Phased allocation of resources

• Detailed number of patients per period

Patient Group Planning and Control (wks-3mth)

• Urgency and Service Requirements

• Planning guidelines per patient group

Short-term Planning and Control

• Uses totally disaggregated forecasts or actual

demand

• Makes interventions to resources to resources to

correct deviations from plans

• Ad hoc considerations of operations objectives

Patient Planning and Control (dys-wks)

• Scheduling of individual patients

Table 1 - Comparison general p&c decision levels with framework Vissers (2001)

In general, the distinctions of Visser’s framework provides useful time-boundaries regarding the decisions focus of planning and control within health care organizations and also emphasizes the urge for constant feedback and control mechanisms in order to balance the different levels and the underlying decisions, as well as, to match patient flows with resources. However, as these endeavours may seem theoretically sound, they do not provide much practical information on how to disaggregate towards the different decision levels and how to schedule patients for the short term.

Given the scope of this thesis, i.e. shared resources at the radiology department, planning and control on the long-term level of strategic planning and patient volumes will not be considered. Rather, this thesis will focus on the medium- and short-term planning and control functions of which the time-phased allocation of resources and the planning guidelines per patientgroup are important elements.

2.3.3 Defining the Research Goal and Questions

Now that the area of concern is portrayed, and an introduction is given to the planning and control function, the research goal and questions should provide structure for the successive thesis. The research goal was initially stated as follows: “to identify the main shared resources within a hospital and to determine how these shared resources influence the patient lead time performance”. However, as the Nij Smellinghe hospital was specifically interested in a focus on the radiology department, and as this thesis had a timeframe of six months, the research goal had to be scoped. Therefore, the research goal is stated as:

“to determine how [a selection of] shared resources within the department of Radiology influence

the patient lead time performance”

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an input-transformation-output-outcome model, where the output (and purpose) comprises the delivery of effectively and efficiently managed operations.

Figure 4 - Planning and Control Function

Although the goal of this thesis is primarily aimed at the effect of shared resources on the patient lead time, also the performance criteria of resource utilization are addressed. This enables an insight into the performance (i.e. efficiency) of the resources themselves. Consequently the main research question is stated as follows:

“How is the planning and control function underlying the shared resources managed and what is

the effect of this operations management on the performance of the shared resources?”

In order to answer the research question several sub-questions have been defined. The sub-questions are derived from the different elements in Figure 4 and ultimately lead to the answer of the main research question.

The first question relates to the characteristics of demand which gives insight into the complex of incoming requests.

1. What are the characteristics of demand?

Further, the characteristic of supply provides an understanding of both the services delivered and the properties of the resources used.

2. What are the characteristics of the resources and the delivered services?

The management objectives set by the long- and medium-terms levels of planning and control enable the interpretation of the actual efficiency and effectiveness of the operations.

3. What are the objectives set for the shared resources?

The way in which planning and control is conducted basically determines how supply and demand are reconciled. Insights in the choices made indicate how shared resources are managed.

4. a. How is the resource capacity determined? b. How is the capacity allocated?

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Finally, the influence on the patient lead time and resource utilization is explored. 5. a. What is the performance in terms of patient lead time?

b. What is the performance in terms of resource utilization?

These Sub-Questions will be researched at the department of radiology for a selection of resources. The consequent paragraphs will discuss these different questions, as well as, the underlying factors introduced. Notably, the outcome of the planning and control function is not addressed, as satisfaction of staff and patients is not a direct subject of this thesis.

2.3.4 Characteristics of Demand

In order to categorize demand, the DWV3 classification approach (based on Christopher & Towill, 2000) is adopted, which has also been used in the shared resource context by Van der Vaart & Van Donk (2005). This approach assumes five different characteristics that influence decision-making in the context of demand chain strategies. These attributes are (1) duration of life-cycle, (2) time-window for delivery, (3) volume, (4) variety, and (5) variability. Although this approach was initially used in the context of supply chain management for segmenting products based on market demands, it is expected that the hospital system does also hold different demands for different services and/or patient groups. Therefore, a distinction into these variables seems sensible.

The first attribute, i.e. duration of life-cycle, is in itself less important, as this research focuses on generic radiologic services, and does not include the strategic considerations underlying new sorts of services and/or temporary activities.

The second attribute, i.e. time-window for delivery, reflects the responsiveness requirements for the different services and/or patient groups. This attribute is part of the management objective element, and will be addressed in section 2.3.5.

Volume and variety are the third and fourth attribute, which are often related to each other. According to Slack et al (1998): “operations which produce a high variety of products or services in relatively low volume will clearly have customers who require a different set of factors and use processes which have a different set of needs to those operations which creates standardized products or services in high volume”. Both the volume and variety of the requested services (mix demand) and of the requesting specialties (volume demand) are considered.

The final classification variable concerns the variability, which is the numeretical quantity for uncertainty. Here, the fluctuations of demand in terms of volume (volume uncertainty) and service mix (mix uncertainty) are considered. As such, unpredictability affects capacity utilisation and the resultant production techniques (Christopher & Towill, 2000). It is expected that uncertainties are buffered with time, and production flexibility. The level of uncertainty will be expressed in terms of Relative Standard Deviation (RSD), which relates the standard deviation with the mean. RSD is regarded as low for values 0 – 30%, medium for values 30 – 60%, and high for values above 60%.

2.3.5 Characteristics of Supply

The characteristics of the supplied resources which are held relevant to this research are: technology, the characteristics of the services conducted, and the process uncertainty.

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The resources researched may provide a wide range of different services, which pose different demands on the resource capacity. Here, an overview will be given of the different groups of examinations, as well as, the capacity (staffing, planned time) and setups required per examination.

Process uncertainty refers to the fluctuations in the services delivered. This uncertainty can be caused by (1) differences in processing times for different services, (2) differences in activities within equal services, and (3) variations in the physical coordination and effort of the operator performing the task. High process uncertainties may pose difficulties for effective planning and control and may lead to inefficiencies (idle time) or waiting times for queued patients.

2.3.6 Management Objectives

Slack et al. (1998) have defined an array of performance objectives relevant to operations management, consisting of (1) quality, (2) dependability, (3) flexibility, (4) speed and (5) cost (see Table 2 for examples). Performance measures defined and audited within these indicators can ultimately say whether planning and control has been conducted efficiently and effectively.

Performance Measures: Hospital Examples:

Quality,

i.e. to provide error-free services

Treatment is carried out in the correct manner Patients are kept informed

Dependability,

i.e. to deliver exactly on time

Keeping to appointment times

Number of cancellations are kept to a minimum Flexibility,

i.e. to change fast and far enough

The ability to introduce new types of treatments The ability to adjust the number of patients treated Speed,

i.e. to minimize the time a customer has to wait

The time for test-result

The time between diagnosis and actual treatment Cost

i.e. to do things cheaply

Staff Cost Material Cost

Table 2 – Examples of performance objectives (derived from Slack et al. (1998))

As this thesis approaches the medical operations from a logistical perspective, the performance measure of quality is not included in the diagnosis. The measures of dependability, flexibility, and speed all refer to the patient service level (or availability). In contrast, the performance measure of cost has a strong emphasis towards resource efficiency (or utilization). The impact on the planning and control decisions is expected to differ greatly between these two “order-winners” (patient service level versus resource efficiency) under highly uncertain circumstances. This is caused by the fact that highly resource-efficient operations would require the buffering of time (implying low service levels), while high service levels requires buffering of capacity (implying low utilization). Hence, the management objectives are expected to be of great effect to the planning and control approach taken.

2.3.7 Planning and Control Decisions

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2.3.7.1 Resource Capacity

The definition of the capacity of an operation is “the maximum level of value-added activity over a period of time” that the process can achieve under normal operating conditions (Slack et al., 1998). This level or volume of activity can be expressed in terms of the amount of resources (e.g. number of beds available) or the level of productivity (e.g. number of patients treated). Hospitals often measure the capacity in terms of the amount of resources, because the changing mix of activities causes the productivity to fluctuate (and is therefore difficult to predict).

The design capacity of an operation is often determined by the availability of staff within the hospital environment. This theoretical capacity is normally used to schedule patients for the services delivered. However, in practise the actual usable capacity is somewhat less than the design capacity. This is caused by down-time due to for example: holidays, vacations, preventive maintenance, employee meetings, and etcetera. This actual usable capacity is also called the effective capacity.

2.3.7.2 Capacity Allocation

Now that capacity is known, one has to determine how to share it among the demanding specialties. As the definition stated, a shared resource concerns a “common capacity source” (Hoekstra & Romme, 1992) which has to be shared. The simplest form of sharing would be to divide capacity according to the sequence of request-arrivals. Additionally, Vissers et al. (2001) defines time-shared resources, which are resources that are allocated to a user, i.e. a specialist, for specific time-phased periods. Further, Vissers et al. also approaches specialist time as a shared resource, which is sometimes shared among different patients groups or multidisciplinary teams. However, as this thesis only approaches physical resources, the specialist time is not regarded.

The concept of time-shared resources shows some similarities with the concept of buyer focus (i.e. a type of focus in which resources are allocated to a single buyer), which was introduced in the theoretical background section. Here one could regard certain patientgroups of a specific specialist as the focused group for whom resourcew are exclusively allocated for a certain period of time. According to the theoretical background it is expected that this form of sharing will most probably happen in cases characterized by high uncertainty.

Further, as some functions may be delivered by multiple similar resources, one must also make a decision whether these multiple resources are considered pooled capacity or separate capacity. For example, when considering a patient ward it is evident that this is a case of resource pooling (e.g. nurses, beds), while the ward itself can be either dedicated or shared. In addition, a hybrid form of sharing may occur when hospital beds within a certain ward are dedicated to a certain speciality, and simultaneously are available for other specialities in order to level peaks in demand. Consequently, pooled resources introduce similar advantages as shared resources (e.g. synergies, specialisation), and -in addition- they bring flexibility as well. The uncertainty in e.g. the operations length can be spread over the pooled resources, so that potential waiting times can be absorbed before they occur. Beds are confronted with the uncertainty of the length of stay of patients and can therefore better be pooled such that new requests can be divided over other free beds when available. However, one cannot always pool similar resources; for example: the combination of gynaecology patients and pregnant patients is not considered ethical.

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2000). Figure 5 gives an overview of the distinction between pooled and shared resources. Here, the ‘focused’ dimension can also be regarded as time-shared.

Shared

Pooled

Focused Single

Figure 5 – Pooled versus shared resources

In the case of pooled resources, it is expected that the complexity of control increases. This is due to the fact that overall volumes of requests are increasing (and probably the variety of request as well). Further, flexibility can only be gained when information is shared regarding the activities and status of the grouped resources; e.g. information about which resource is (un)available on a specific time. This also may impose considerable complexity of control.

2.3.7.3 Loading, Sequencing and Scheduling

The final aspects of planning and control concern three different, but integrated activities: loading, sequencing, and scheduling. These activities deal with the volume and timing of activities.

The task of loading basically determines the volume an operation can cope with. Thus, once it is decided which requests may be loaded during a certain time, one has to determine whether the available capacity is loaded finitely or infinitely. This decision is usually based on the criteria whether it is possible and/or necessary to limit the load. For example, an emergency department may not turn away the incoming requests. Obviously, infinite loading may seriously affect the service levels, as well as, the resource utilization levels.

The task of sequencing determines the priority of tasks to be performed. The most well known sequence is First-In-First-Out which serves requests in exactly the same way as they arrive. However, sometimes physical constraints may affect the sequences, as for example some operations have to be conducted before the other, or some operations may be dependent upon specific preparations. Further, customer priority may also impose a specific sequence, which basically coincides with the (time) focused allocation decision discussed in the previous section. As soon as a request arrives of the specialist concerned, he will immediately get priority within the specific time-phase defined.

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2.3.8 Performance (E&E Managed Resources)

As the main focus of this thesis concerns the influence of shared resources in lead-time performance, it is interesting to approach both the waiting times and access times of the different groups of patients. Here it is assumed that the influence on the overall patient lead-time performance equals the access time of the radiologic modality, as the diagnostic services conducted generally form a bottleneck for the overall care trajectory (i.e. no other services can be performed beforehand).

Additionally, as was stated in the section regarding management objectives, two contrasting approaches to performance exist. One focuses on the patient service levels (or availability) and explicitly aims at reliability, speed, and flexibility. The other focuses on resource efficiency (or utilization) and thereby explicitly aims at costs. Therefore, the resource utilization is also included as a variable of the diagnosis.

High utilization can adversely affect the patient as it may reduce the speed, reliability and volume flexibility of the overall operation. In contrast, high service levels in the form of maximum availability can adversely affect utilization.

2.3.9 Constraints

This thesis abides by certain constraints inherent to the case at hand, the time available, and the knowledge present. The Nij Smellinghe hospital has asked for recommendations which aid them in their lead time problems found at the radiology department. Although these problems are not leading for the thesis written, they were found to have considerable overlap with the data used for this research design. Therefore, it was possible to define a certain number of recommendations based on the data at hand. Additionally, some research areas were explored more thoroughly than actually needed in order to make the recommendations more sensible. This being said, the research took a considerable amount of time to focus on the radiology department and could therefore not include an exploration of other departments involved. Therefore, the overall patient trajectory could not be included as a part of this investigation. Further, the recommendations posed were by no means meant to be final and have to be placed in a broader perspective and followed by additional actions and research. Also, this thesis does not enclose the actual implementation.

2.3.10 Summary

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2.4 Methodology

2.4.1 Case Study Research

The final element of the research design comprises the methodology. According to Jackson (2000): “the methodology marshalls various methods, tools, and techniques in a manner appropriate to the framework of ideas, and use them to investigate the situation of interest”. The strategy chosen is case study research, which is especially useful “when ‘how’ or ‘why’ questions are being posed, when the investigator has little control over events, and when the focus is on a contemporary phenomenon within some real-life context” (Yin, 2003). Within this research design the real-life context plays an important role, as this research tries to understand how shared resources are managed within a real-world hospital. As such, one tries to “ground theoretical concepts with reality” (Stuart et al., 2002). Also the notion that the investigator has little control over the events encountered is true, as the research is not focused on changing variables in the real-life context. For this matter, only recommendations are made from the perspective of the researcher.

An overview of the case research process has been given by Stuart et al. (2002) and consists of five critical stages as illustrated in Figure 7.

Figure 7 - The Five Stage Research Model (Derived from Stuart et al. (2002))

The first two stages have already been defined at this point. It was assumed that the influence of shared resources on patient lead time originates from the underlying planning and control function, of which several relevant variables have been operationalized. Additionally, the background theory provides a focus towards the distinction between sharing and focusing in combination with the influence of uncertainty. The third stage consists of the gathering of real-life data. For this matter, three cases are investigated. The selection of these cases is done in the next paragraph. During the fourth stage, the gathered data has to be analyzed. This does not only concern the patterns found and observations made within each case, but also the analysis of cross-case patterns. Finally, the results are disseminated by means of this thesis.

2.4.2 Selection of Cases

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walk-in mechanism (i.e. no scheduling). With these apparent differences, the author created as much diversity as possible within the constraints present (e.g. time-horizon, radiology based, etc).

Concluding, the modalities of MRI, US, and Bucky are selected for the case study investigation.

2.4.3 Data Collection

In order to collect the necessary information, multiple sources have been used. These sources comprise: (1) documentation, (2) archival records, (3) interviews, and (4) direct observations.

The documentation used concerns administrative documents derived from an application called QualityOnline. These documents concern the formal yearly evaluations of the department, as well as, the current goals set. Additionally, documents were retrieved from the team leader, concerning the available staff and physical resources. Also documents concerning planning and control issues were subtracted from different sources related to the modality at hand.

Archival records primarily concern the data collected from the scheduling software package used, which in case is the Kodak CareStream Radiology Information System (RIS) package. This software is used to schedule patients with the appropriate radiologic modalities and enables the tracking of patients through the system. It registers the required diagnostic-activities, the patient-abnormalities involved, the requesting specialist or general practitioner, and other case-specific information (e.g. check-list for MRI-scans, contrast agents required, etc.). The program tracks a series of time registrations which have been used for determining examination volumes, arrival times, etc. The available measures are projected in Figure 8, and are defined successively.

Figure 8 - The patient lead-time in relation with available measures

Since most modalities require an appointment (except the Bucky-rooms and some emergency cases), the planning software registers the booking-date and time (T1) as well as the time of making the appointment (T0). Further the software records the time of arrival in case the patient arrives via the reception desk, which excludes the emergency patients and the inpatients. Consequently, as the radiologic technologist starts the required procedures for a certain patient, the actual moment of starting the appointment is recorded (T2) as well as its end (T3). Finally, as soon as the radiologist has finished the report, another point in time (T4) is measured which stands for the formal ending of the radiologic trajectory. Figure 8 visualizes these points in time, although it doesn’t indicate the actual spread in time. It should be noted that the setup time (T2’-T2) involved cannot be derived from the available data and has to be determined by means of interviews or direct observations.

Interviews were conducted with many different respondents, and they most often were of an open-ended nature (i.e. semi-structured). In terms of functions, the respondents interviewed concerned the head of logistics, head of radiology, team leader of radiology, various radiologic technologists, administrative staff, and IT-specialists.

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The different sources of evidence are linked with the research variables in Table 3. Additionally, information regarding the contextual analysis in chapter 3 came from Interviews and Documentation.

Research Variables Sources of Data

Characteristics of Demand:

- volume/variety of patients (-groups); Archival Records - volume/variety of requested services; Archival Records - uncertainties in patient-volume

/examination-mix.

Archival Records

Characteristics of Supply:

- process type (batch, setups, routings); Direct Observations, Interviews

- service characteristics Archival Records, Direct Observations, Interviews

- process uncertainty. Archival Records

Management Objectives:

- “order-winners”; Documentation

- lead-time/ waiting-time objectives; Documentation Planning and Control Shared Resource:

- Capacity of resource; Documentation, Interviews

- Allocation of resource; Direct Observation, Interviews - Loading/sequencing/scheduling of patients. Direct Observation, Interviews Performance:

- Patient Access-time; Archival Records

- Patient Waiting-time; Archival Records

- Resource Utilization. Archival Records

Table 3 - Relation between research elements and sources of data

2.4.4 Validity

Yin (2003) provides four tests which are commonly used for establishing the quality of empirical research. These tests concern: construct validity, internal validity, external validity, and reliability. The consequent paragraphs will apply these tests to this research design.

Construct validity is the extent to which we establish correct operational measures for the concepts being studied (Kidder & Judd, 1986). Construct validity can be achieved by (1) use of multiple sources of evidence, (2) a chain of evidence, and (3) by review of the draft case study (Yin, 2003). The technique of triangulation is used for collecting information from multiple sources while aiming at corroborating the same fact or phenomenon. Further, a chain of evidence is established by providing a well-documented case study which enables any third party to trace the research steps in retrospect (from research question to conclusions and back).

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External validity refers to the domain to which a study’s findings or presumed causal relationships may be generalized (Yin, 2003). Concerning case research, generalization is from each case to a broader theory, not from samples to populations as is the case with survey research relying on statistical generalization (Yin, 2003; Stuart et al., 2002). By using cross-case reflection and by comparing the outcome to the theory presented, results may be generalized to a broader theory. Also, by using logical extrapolation, the researcher might determine to where the findings might apply in other circumstances.

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3. Contextual Introduction

In order to portray the practical context in which this graduation research is conducted, this chapter provides a brief introduction of the Nij Smellinghe hospital and a more detailed focus towards the Radiology department. The latter provides an overview of the available resources and the management structure applied.

3.2 Background information about Nij Smellinghe

3.2.1 Introduction

The roots of Nij Smellinghe date back to the years shortly after the Second World War, and were initiated by a group of protestant churches. During the years after the war, the hospital has seen many changes and found its current location as from 1970. The name was derived from a local river crossing an old Benedictine Monastery which was said to house medical functions during the fourteenth century.

Currently, Nij Smellinghe is a medium-sized acute general hospital with 339 beds and 23 specialties, offering a range of basic hospital services to patients in a catchment area of about 120.000 inhabitants. The catchment area concerns the South-Eastern area of Friesland, formed by the municipalities of Smallingerland, Opsterland, Achtkarspelen, Ooststellingwerf, Tietjerksteradeel, Marum, and Grootegast.

The hospital management strives to become a top five hospital within the Netherlands. The formal mission is defined as “the patient is determinant for our actions”, which denotes an emphasis towards patient-centered care. The defined mission seems pertinent with respect to the current dynamics within the healthcare environment, which have been briefly sketched in the area of concern. In a recent independent benchmark of a Dutch newspaper, the Nij Smellinghe hospital was scored as the number six of best hospitals in the Netherlands5.

3.2.2 Organizational Overview

The Nij Smellinghe Hospital is a non-profit private institution (i.e. foundation), which is governed by means of a two-tier board. This concerns a management board and a separate supervisory board. The management board is formed by an executive director, and five general managers who are individually responsible for the following clusters: (1) ambulatory services, (2) inpatient services, (3) non-medical appliances, (4) medical supportive services, and (5) human resources and corporate services. This management board is directed by a one-headed executive board. An organisational chart is included in appendix 1. The department of Radiology is part of the medical supportive services.

3.3 The Radiology department

3.3.1 Introduction

Diagnostic radiology has always been a ‘service’ that is tapped into by other specialties. The vital business of radiologists is to provide accurate diagnostic information to those who request it, as quickly and efficiently as possible. As a medical specialty, radiology can be classified into four

5

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subfields. This includes (1) diagnostic radiology, (2) nuclear medicine, (3) therapeutic radiology (i.e. radiation oncology), and (4) interventional radiology (i.e. minimal invasive procedures using image guidance). Except for therapeutic radiology, the department of Radiology offers these different subfields by means of a diverse set of radiologic modalities and specialised staff.

3.3.2 Management Structure & Objectives

The management structure of the department of Radiology is based on the concept of dual management, which basically divides responsibility over two heads. One head is responsible for organisational matters, whilst another is responsible for the medical issues (one of the radiologists). On a lower level, different specialised teams are formed around the different modalities available. These teams have one member appointed who provides primary communication with the head of organisational matters when need be. Further, a team leader is assigned with the responsibility for providing adequate staffing levels for each modality.

The management of patient lead times consists of a formal management document stating the maximal allowed waiting/lead times per modality (see appendix 2). These objectives are guided by a national norm -the so called treek-norm6- which sets specific lead-time criteria for diagnostic departments. Further, the actual performance is monitored by randomly measuring lead times with a frequency of about twice every year. The results are reported and serve as a basis for corrective actions. Other issues which are monitored are: phone availability, patient (dis)satisfaction, (near) accidents and absence-rate of staff.

Besides the current control-loop on the lead-time performance, there are no further arrangements concerning the management of resources in terms of planning and control. This emphasises the ‘supportive’ character of the department, which likely causes the absence of resource-related objectives (in terms of efficiency or availability) and/or a focus towards specific patient-trajectories requiring the resources.

3.3.3 Available Modalities

The diagnostic imaging equipment available to the department of radiology supports a broad spectrum of radiologic applications. Table 4 presents the major resources available, together with figures of yearly demand and unit price. The estimates for 2008 are based on information of the head of Radiology and are determined by means of extrapolating historic increases of demand. The information regarding unit price concerns dimensionless numbers which indicate a relative factor for the unit price of typical examinations per modality. The actual unit prices are considered classified information, and are therefore not provided.

Modality Amount 2006 2007 2008* _{Unit Price}

Magnetic Resonance Imaging (MRI) 1 3626 3963 4100 7

Ultrasonography (US) 2 7313 7879 9000 2

Projectional Radiography (Bucky) 3 44260 47095 49800 1

Computed Tomography 1 4269 4433 4700 4

Nuclear Medicine 1 1875 1863 1900 12

Fluoroscopy 3 1993 2089 2400 6

Mammography 1 2272 2479 2600 4

Table 4 – Yearly Demand/ Unit Price of Available Modalities

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Resource Sharing in the Healthcare Environment