University of Groningen Faculty of Economics and Business Technology and Operations Management

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Master Thesis

A framework for assessing the effective use of

resources at nursing wards

Author:

Casper Visser

c.visser.11@student.rug.nl s2560836

Supervisors:

dr. ir. D.J. van der Zee1

dr. N.D. van Foreest1

ir. T.J. Hoogstins2

1_{University of Groningen}

2_{University Medical Center Groningen}

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I

ABSTRACT

CONTEXT: Increasing global population as well as population aging cause an increasing demand of nursing wards. Budget, spatial, or governmental restrictions prevent most nursing wards from increasing their capacity. In addition, staff shortage – an increasing worldwide problem – also prevents nursing wards from expanding their capacity to deal with the increasing demand. Therefore, it is of utmost importance to use the available resources (which in fact determine a nursing ward’s capacity) as effective as possible. A first step towards improving the effective use of resources is to assess the current use. So far, no tool or framework exist to do so for nursing wards.

OBJECTIVE: The primary objective of this research is to develop a framework which can be used to assess the effective use of resources at nursing wards.

METHODS: A three-phase design science approach is used. The first phase, information gathering, consists of both a literature study and a single case study. The literature study provides the basic construct of the framework, whereas the case study will further shape the basic construct of the framework. The framework itself is developed in the second phase. The third phase consists implementing the framework into practice and the evaluation of it.

RESULTS: a framework is proposed which can be used to identify both internal related and external related capacity losses of a nursing ward. Several loss categories are proposed, and loss factors are related to the categories.

ORIGINALITY/VALUE: This research contributes to filling the knowledge gap that exists with respect to assessing the effective use of resources at nursing wards. Furthermore, it offers nursing wards a tool which can be used to easily identify different capacity losses over a wide range of sources, both internally related and externally related.

LIMITATIONS AND FUTURE RESEARCH: The framework’s generalizability is limited as it was evaluated for one nursing ward only. Future research should evaluate the framework’s generalizability by applying it to other nursing wards to. Furthermore, future research could focus on increasing the practical implication of the framework.

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II

PREFACE

Before you lies the master thesis “A framework for assessing the effective use of resource at nursing wards’. It has been written to fulfill the graduation requirements of the master program Technology and Operations Management at the University of Groningen.

Finishing this master thesis means reaching the finish line of my master program Technology and Operations Management at the University of Groningen. This master program really contributed to my understanding of how organizations and their operations are structured. In addition, the program offered the possibility to specialize in healthcare. Specializing in healthcare contributed to my understanding of the complexities and dynamics of the healthcare sector, but also raised my interest for future research and/or work.

Several persons have contributed academically and/or practically to my master thesis. I would like to thank two persons in special. First, I would like to thank dr. ir. van der Zee for his assistance and guidance throughout my research. His expertise in healthcare and enthusiasm motivated me to work on this project. He was able to explain several topics very clear and was also able to pose critical questions which made me (re)think about certain aspects. Despite his guidance during this research, the degree of freedom I was given was still significant and very pleasant. Second, I want to thank ir. T.J. Hoogstins in special for his assistance during the project. Hoogstins really helped me with coordinating and communicating with the staff members at the University Medical Center (UMCG). He also provided me with useful feedback and made the arrangements possible needed for my research. Furthermore, I would like to thank P. Lenselink, I. Castellanos, F. van der Heide, W. Brink, and all other staff members of the UMCG MDL nursing ward for their assistance, openness, and friendliness during the execution of my research. I experienced the working environment at the MDL nursing ward as very pleasant. Also, their interest in my research was very pleasant. At last, I want to thank W. Drent for assisting me in taking several measurements during my research.

I believe the healthcare sector is forced to change (rapidly) in the next decades, mainly due to population increase and the increasing focus on budget control/cutting costs. Viewing the healthcare from an operations perspective is a relative new area which is paired with innovation. This raises my interest, and I devoted myself to this research.

I hope you enjoy reading this thesis. Casper Visser

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III

LIST OF FIGURES

Figure 1. Conceptual model of a nursing ward ... 4

Figure 2. A three-phase design science approach ... 5

Figure 3. General system description nursing wards ... 8

Figure 4. Classification of production losses for calculating overall performance effectiveness ... 9

Figure 5. OEE measurement tool and the perspectives of performance integrated in the tool ... 10

Figure 6. Capacity concepts for resources ... 12

Figure 7. Basic construct for the proposed overall performance effectiveness framework for nursing wards ... 16

Figure 8. Flow diagram MDL nursing ward ... 17

Figure 9. Organogram MDL department ... 20

Figure 10. Flow diagram MDL nursing ward indicating capacity losses ... 24

Figure 11. Proposed overall performance effectiveness framework ... 27

Figure 12. MDL nursing ward bed unavailability ... 29

Figure 13. MDL nursing ward reserved bed time distribution ... 30

Figure 14. MDL nursing ward non-necessary stay ... 31

Figure 15. Resource effectiveness of the MDL nursing ward ... 32

LIST OF TABLES

Table 1. Sources and examples of the basic construct’s loss categories ... 16

Table 2. Quantification related to loss factors at the MDL nursing ward ... 29

Table 3. Non-necessary stay results ... 30

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VI

LIST OF ABBREVIATIONS

AZNN: acute zorgnetwerk Noord-nederland

EPD: electronic patient dossier

MDL: maag-darm-lever

OEE: overall equipment effectiveness

OFE: overall factory effectiveness

OPE: overall performance effectiveness

ORE: overall resource effectiveness

RS: research statement

TEEP: total effectiveness equipment performance

TPM: total productive maintenance

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1. INTRODUCTION

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1. INTRODUCTION

The healthcare industry faces an increasing pressure to reduce cost, improve operational quality, and patient’s satisfaction (Carlos, Gomes, Yasin M. et al. 2010). This pressure is caused by several factors, but most prominent due to population aging (United Nations, 2015). Population aging will have a significant impact on the healthcare sector. It increases care demand while hospitals are often not able to increase their capacity (i.e. the number of patients a hospital can provide care for) accordingly. Increasing capacity is often restricted by factors such as staff shortage, budgetary constraints, or spatial constraints (Arora, 2015; WHO, 2010). If increasing capacity – which is determined by the resources available – is not possible, it is of utmost importance to use the available resources as effective as possible. Effective use of resources implies to minimize capacity losses, i.e. losses that decrease the number of patients that can be treated. Examples of capacity losses are late patient dismissals and staff shortage or illness. Hospital key resources are staff, beds, and equipment.

This research is motivated by the maag-darm-lever (MDL) nursing ward at the University Medical Center Groningen (UMCG). The MDL nursing ward treats patients with diseases like esophagitis, hepatitis (liver disorder), pancreatitis, Chrohn disease, or gastro-enteritic channel cancer. Currently, a significant percentage of patients that should be treated at the MDL nursing ward need to be accommodated elsewhere due to capacity constraints. These patients are diverted to so called “off-ward” beds. It is undesirable to accommodate patients at another nursing wards, as patient safety is not well served in these off-ward beds (Anderson et al, 1988; Brownson & Dowd, 1997; Needleman et al, 2002). It would either imply that MDL nurses must move through the hospital to treat patients, or that the patients need to be treated by other nursing ward’s staff, which are not specialized in MDL related diseases or treatments.

Nursing wards are among a hospital’s key resources. Although hospitals are divided into separate departments, nursing wards are the places where the actual patient treatment is carried out (UMCG, n.d.). To illustrate, a patient that must undergo surgery does not stay at the operation room but is transferred – sometimes via an intermediate stay at the intensive care – to a nursing ward. Patients are treated at the nursing ward until dismissal. Nursing wards have a direct influence on a patient’s health, the provided quality of treatment, and length of stay (Graban, 2008), and are therefore seen as a one of the most important parts of the hospital.

An important step towards minimizing capacity losses is to assess how effective resources are currently used. In the healthcare domain, no structured approach exists how to do so. In the manufacturing

domain, however, such approaches do exist (e.g. Muchiri & Pintelon, 2008; Williamson, 2006;

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1. INTRODUCTION

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investigating another nursing ward than investigated by Reinsma, and consequently proposing a framework including a broader range of capacity losses.

The main objective of this research is ‘to develop a framework which can be used to assess the effective use of resources at nursing wards’. This objective contributes to filling the knowledge gap that exists around this topic. In addition, it serves a practical use since the MDL nursing ward can benefit from this research. This research is executed in three phases: (1) information gathering, (2) framework development, and (3) framework evaluation. The first phase consists of both a literature study and a case study, the second phase consists of the development (process), and the (3) phase will evaluate the framework by applying at a nursing ward.

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2. PROBLEM DESCRIPTION AND RESEARCH DESIGN

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2. PROBLEM DESCRIPTION AND RESEARCH DESIGN

This chapter will provide the problem background in section 2.1. Once the problem has been placed in context, the objective of this research is treated in section 2.2. The system and its boundaries are specified in the conceptual model in section 2.3. Furthermore, the research design will be discussed in section 2.4.

2.1 Problem background

As introduced previously, nursing wards are among a hospital’s key resources. They have a direct influence on a patient’s health, the provided quality of treatment, length of stay contributes significantly to a hospital’s expenditures (Graban, 2008). However, nursing wards experience pressure from society to increase their capacity due to population aging (United Nations, 2015). In addition, they experience pressure from top management to reduce costs and improve operational quality (Carlos et al. 2010).

Since nursing wards are often bounded by budget and/or space (Arora, 2015), simply increasing capacity to deal with the increasing demand is not an option. It is therefore of utmost importance to use the available resources as effective as possible. However, improving the effective use of resources (also termed ‘resource effectiveness’) at nursing wards is not trivial. Numerous sources of variability (e.g. patient characteristics or treatment uncertainty) harder hospital organizational improvements (Litvak & Long, 2000). In addition, there exist a great lack of interest by scholars to focus on organizational improvements of nursing wards, which causes that there exists no widely adopted approach for improving resource effectiveness at nursing wards. In fact, there even exists no method for assessing the current resource effectiveness, which actually should be the first step towards improving it. Hence, this research is aimed at providing a framework which can be used to assess the resource effectiveness of nursing wards.

2.2 Research objective

Derived from the problem background, the main objective of this research is stated below. To develop a framework which can be used to assess resource effectiveness of nursing wards in which the following definitions are used:

• A nursing ward is defined as the part of the hospital where patients are diagnosed and treated. Typical operations that are performed at a nursing ward are providing infusion or medication, measure blood pressure, and measuring/monitoring heart rate. Operations like medical imaging, surgery, or endoscopic research are not performed at the nursing ward.

• Resource effectiveness implies the extent to which a nursing ward’s resources are used for the intended results, so ideally, beds, equipment and medicines should be available for usage, time is spent only the right type of patients etc. Key resources are staff, beds, medicines, and equipment.

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2.3 Conceptual model

A general nursing ward can be approximated by a three-stage model (Figure 1). In the first stage, patients are admitted to the nursing ward and are assigned to a bed. In the second stage, the care process takes place which is different for each patient. Activities are for example providing patient care and monitoring of the patient. Resources needed in the process include but are not limited to: staff, medical equipment, medicines, and beds. In the third and final stage, patients are discharged if their condition is deemed sufficiently well from a medical point of view. Planning and control activities are for example capacity planning, staff planning, coordination of staff and patients, and coordinating with other departments.

Figure 1. Conceptual model of a nursing ward

2.4 Research design

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Figure 2. A three-phase design science approach 2.4.1 Phase 1 – information gathering

The first phase is concerned with the literature study and the investigation of the case study. Both topics are discussed in the next subsections.

Literature study

A qualitative literature approach will be applied in this research. In contrast to quantitative literature research, qualitative literature research uses inductive reasoning to obtain a better an in-depth understanding and insight of phenomena through study of narrative data (University of Arkansas, n.d.). Quantitative literature research, however, treats the literature as unit of analysis, and aims to predict or control phenomena trough collection and analyses of numerical data (e.g. meta-analysis) (Green, Hall, 1984). In this research, literature will serve as knowledge base and not as unit of analysis. Hence, a qualitative literature research will therefore be applied.

Case study – the MDL nursing ward

The UMCG is one of the largest hospitals in the Netherlands. More than 10.000 employees provide patient care, are involved in cutting-edge research and involved in education. The UMCG focuses on highly specialist care, care that cannot be provided in other hospitals (sometimes referred to as topflight referred care). The UMCG is a tertiary care hospital, which means it can only be accessed via first or second line care providers (general practitioners and regular hospitals, respectively).

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The UMCG MDL department experiences the pressure caused by population aging (as previously discussed). Currently, 15% of their patients need to be accommodated at so-called ‘off-ward beds’, i.e. beds at other nursing wards. It is undesirable to accommodate patients at another nursing wards, as patient safety is not well served in these off-ward beds (Anderson et al, 1988; Brownson & Dowd, 1997; Needleman et al, 2002). Since it is not possible for the MDL nursing ward to increase their capacity, it is expected that they can benefit from a framework for assessing the effective use of their resources in order to – eventually – treat more patients.

2.4.2 Phase 2 – framework development

The literature study during phase 2 will provide the basic construct of the framework, which implies generalized loss categories are proposed which are likely to be found in a nursing ward. This basic construct will provide directions in which capacity losses might be found and will be used during discussions performed with the staff members of the MDL nursing ward. These discussions will serve to validate whether the generalized categories are indeed applicable to the MDL nursing ward. In addition, the information provided by the MDL nursing ward staff will be used to further detail the framework, i.e. allocate different loss factors to the proposed categories. Note that this will be performed in an iterative way. Completeness of the model will be validated with the staff after adjustments.

2.4.3 Phase 3 – framework implementation/evaluation

The proposed framework will be implemented in practice, i.e. to quantify the found loss factors using several data sources. These sources include:

• UMCG patient data of MDL related patients ranging 10-2016 until 05-2017. This database will be used to provide a general overview of the nursing wards in terms of number of patients treated, type and frequency of diseases/treatment, and patient’s length of stay.

• UMCG electronic patient dossier (EPD) data ranging 12-2017 until 04-2018. This database will be used to quantify several loss factors, as will be explained later.

• Sample measurements using a non-necessary stay tool, which is elaborated in section 3.3.3. • Expert views of MDL doctors to approximate several loss factors that cannot be quantified by

the above-mentioned data sources.

Limitations of the data have to be acknowledged. The used databases (first and second bullet) cover data from approximately a half year. As care demand fluctuates throughout the year (Litvak et al. 2005), the obtained results may not be representable during an entire year. However, due to limitations in the data availability, it is chosen to work with the mentioned databases.

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3. THEORETICAL BACKGROUND

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3. THEORETICAL BACKGROUND

This chapter provides the theoretical background underlying this research. First, in section 3.1, a general description of a nursing ward is provided to specify the research context. In addition, challenged faced by nursing wards are discussed to stress the need for assessing the effective use of resources in nursing wards. Section 3.2 then proceeds by reviewing frameworks for doing so. In order to use such frameworks, capacity losses of a nursing ward need to be identified. Section 3.3 elaborates on several methods to identify those losses, each provided with relevant examples. Section 3.4 will discuss the main findings of this chapter.

3.1 Nursing wards

In Dutch hospitals, there are 27 acknowledged clinical specialisms, divided into three clusters (Nederlandse Federatie van Universitair Medische Centra [NFU], 2010): (1) the contemplative (beschouwend) cluster, (2) the supportive (ondersteunend) cluster, and (3) the cutting (snijdend) cluster. Contemplative specialisms are for example internal medicine, gastroenterology, and geriatrics. Supportive specialisms are focused on laboratory research for diagnostics and treatment, e.g. radiology, anesthesiology, and medical microbiology. Examples of cutting specialisms are various types of surgery (e.g. neuro-, plastic-, and general-), urology, and otorhinolaryngology (ear, nose, and throat).

Similar, nursing wards are divided into two categories: cutting nursing wards and contemplative nursing wards. Significant differences between the two exist in terms of patient’s care needs, medical staff involved, and planning processes (Reinsma, 2017). This research will focus on contemplative nursing wards. Henceforth, the term nursing ward implies contemplative nursing wards.

3.1.1 System description

Motivated by (Pannick et al., 2014; Patel & Juang, 2010; Reinstma, 2017;), a nursing ward system is modelled by a three-stage model as indicated in Figure 3. Patients arrive at the nursing ward from various sources, both within the hospital (other departments) as outside the hospital (revalidation centers, nursing homes, from home etc.). In the first stage, patients are admitted and assigned to a bed. Whether patients can be admitted at the nursing ward depends on the capacity and the planning of the nursing ward. Hence, this should be coordinated with the planning and control body. The capacity is mostly determined by the availability of key resources like staff, beds, and equipment. The care process of a nursing ward usually consists of patient diagnosis and treatment. If a patient’s condition is deemed sufficiently well from a medical point of view, the patient is discharged and destined to go home or to other destinations like nursing homes or revalidation centers. In some cases, the patient also can be discharged to another hospital department, hence not being discharged from the hospital. However, since the system being considered in this research is bounded by the nursing ward itself, the patient is still considered to be discharged.

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Figure 3. General system description nursing wards 3.1.2 Challenges faced

Increasing global population aging as well as population aging cause an increasing demand of nursing wards (United Nations, 2015). The number of patients demanding care increases, while, simultaneously, a patient’s age is positively related to its length of stay; the older the patient, the longer its stay at the hospital (Khosravizadeh, 2016; Liu, Phillips & Codde, 2001). This pressures nursing wards to deal with the increasing demand. However, several challenges are faced in the process. Despite increasing demand, governments around the world try to restrain the rapidly increasing healthcare costs. Donald Trump Sr. – POTUS – is set to introduce an alternative to the Affordable Care Act introduced by Barack Hussein Obama II – former POTUS – to lower healthcare spending (CNBC, 2018). Russia’s federal spending on health has reduced by 50% in the period 2012 – 2015 (Oxenstierna, 2016), and also China reduces its financing of public hospitals (Meng et al., 2004).

Medical staff shortage is also an increasing problem worldwide. The US faces a projected shortage of 1.1 million nurses by 2022 and 104.900 physicians by 2030 (American Nurses Association, 2017; Association of American Medical Colleges, 2017). India experiences a shortage of 2.4 million nurses (World Health Organization, 2010), China a shortage of 5 million nurses (Yun, Jie & Anli, 2010), and the Netherlands a shortage 100.000 in the next four years (UWV, 2018). In fact, the World Health Organization (2010) reported that every country – developing and developed – suffers from nurse shortage. Shortage of medical staff increases job demand and nurses’ workload will exceed their capacity. Also, shortage of nurses adversely affects the performance of nurses in ensuring proper care, hence significantly negatively impact patient care (Aboshaiqah, 2016).

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If increasing capacity is not possible to cope with rising demand, research should focus on the current resources available. Resources that are not used effectively decrease the means a nursing ward is able to spend on their intended goals/patients, hence decreasing their capacity. Some methods exist for assessing whether a nursing ward’s resources are used effectively (e.g. Carey, Sheth & Braithwaite, 2005; Lagoe et al., 2005), however no structured approach can be found in the healthcare domain. Structured approaches are found, however, in other domains, primarily in the manufacturing domain (e.g. Amminuddin et al., 2016; Dalmolen et al. 2013). The following sections explore these approaches and evaluate whether they can be translated to the healthcare domain.

3.2 Measuring resource effectiveness

There are several structured approaches available in the manufacturing domain to (1) determine capacity losses, and (2) determine the resource effectiveness of a given object. Among the approaches discussed are overall equipment effectiveness (OEE), total equipment effective performance (TEEP), overall factory effectiveness (OFE), and overall performance effectiveness (OPE). How the frameworks relate to each other is depicted in Figure 4. These approaches/frameworks are reviewed to identify similarities with a nursing ward to establish the basis of a framework for assessing resource effectiveness in nursing wards. Please note the difference between loss categories (e.g. commercial related) and loss factors (e.g. no demand), as these terms will be used throughout the remainder of this research.

Figure 4. Classification of production losses for calculating overall performance effectiveness. Reprinted from “Performance measurement using overall equipment effectiveness (OEE): literature review and practical application discussion,” by P.

Muchiri and L. Pintelon, 2008, International Journal of Production Research, 46:13, 3517-3535 3.2.1 Overall equipment effectiveness

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(1988). The objective of TPM is to achieve zero breakdowns and defects related to equipment. Reducing breakdowns and defects leads to reduction in inventory, reduction in costs, improved production rate, and eventually to increased productivity, especially for automated processes (Muchiri & Pintelon, 2008).

The main objective of the OEE tool is to identify losses that decrease equipment effectiveness. Nakajima (1988) identified six big losses that decrease equipment effectiveness, divided into three categories: downtime losses, speed losses, and quality losses. The OEE measurement tool including the six big losses encountered in a manufacturing environment is illustrated in Figure 5 (Muchiri & Pintelon, 2008).

Downtime losses:

1. Time and quantity losses due to equipment breakdown or failure. 2. Set-up and adjustment losses, for example during product changeovers. Speed losses:

3. Idle time and small stoppage losses.

4. Reduced speed loss due to difference in equipment design speed and actual operating speed. Quality losses:

5. Quality defects and rework losses caused by malfunctioning production equipment. 6. Start-up losses, for example due to bad communication during shift takeovers.

Figure 5. OEE measurement tool and the perspectives of performance integrated in the tool. Reprinted from “Performance measurement using overall equipment effectiveness (OEE): literature review and practical application discussion,” by P.

Muchiri and L. Pintelon, 2008, International Journal of Production Research, 46:13, 3517-3535

The strength of the OEE measurement tool is that it integrates multiple important aspects of manufacturing, namely maintenance effectiveness, production effectiveness, and quality effectiveness. These perspectives correspond respectively to the factors availability rate (A), performance efficiency (P), and quality rate (Q). OEE is then defined by the product of the three (Slack, et al., 2010):

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3. THEORETICAL BACKGROUND 11 𝐴 =𝑂𝑝𝑒𝑟𝑎𝑡𝑖𝑛𝑔 𝑡𝑖𝑚𝑒 𝐿𝑜𝑎𝑑𝑖𝑛𝑔 𝑡𝑖𝑚𝑒 ∗ 100% 𝑃 =𝑁𝑒𝑡 𝑜𝑝𝑒𝑟𝑎𝑡𝑖𝑛𝑔 𝑡𝑖𝑚𝑒 𝑂𝑝𝑒𝑟𝑎𝑡𝑖𝑛𝑔 𝑡𝑖𝑚𝑒 ∗ 100% 𝑄 =𝑉𝑎𝑙𝑢𝑒𝑎𝑏𝑙𝑒 𝑜𝑝𝑒𝑟𝑎𝑡𝑖𝑛𝑔 𝑡𝑖𝑚𝑒 𝑁𝑒𝑡 𝑜𝑝𝑒𝑟𝑎𝑡𝑖𝑛𝑔 𝑡𝑖𝑚𝑒 ∗ 100% Limitations of OEE

Although the OEE measurement tool as described above is widely used, several authors point out the limitations of the framework. Huang et al. (2003) argue that it the OEE measurement tool is limited to productivity measurement of individual equipment. This is further supported by Scott and Pisa (1998) who argue that machines do not occur in isolation. Equipment is mostly part of a larger integrated system, and Oechsner et al. (2003) therefore argue that the ultimate objective of a factory is not to have brilliant individual equipment, but rather to have a highly efficient integrated system. These limitations of OEE led to modifications of and extensions to the frameworks. In sections 3.2.2 – 3.2.4, a few relevant modified versions of the OEE measurement framework are discussed. In addition, their difference with respect to the original OEE framework is explained. Review of the frameworks can be found in section 3.2.6.

3.2.2 Total equipment effective performance

In contrast to OEE which measures effectiveness of planned production schedules, total effectiveness equipment performance (TEEP) measures effectiveness based on calendar hours (365 days, 24 hours). TEEP if therefore also referred to as the “bottom line” utilization of assets (Stamatis, 2010). The concept of TEEP was first introduced by Ivancic (1998), who argued that OEE’s limitation lies in the fact that it does not include planned downtime (e.g. plant shutdown, breaks). In some cases, planned downtime can take up a significant part of production. If planned downtime is then not included, calculation of OEE would create a distorted view of the situation at hand. TEEP gives insights into the necessary activities required when not planning to make a product. Calculations to determine TEEP can be found in both (Ivancic, 1998), as well as (Stamatis, 2010). Like OEE, TEEP is limited to equipment-level effectiveness assessment.

3.2.3 Overall factory effectiveness Scott and Pisa (1998) state that:

“The manufacturing process is a complex web of interactions among process tools, materials, people, departments, companies, and processes. These inter-dependent activities cannot be set apart from each other, but too often they are viewed in isolation, and there is a lack of coordination in deploying available factory resources (people, information, materials, tools) to manage work efficiently.”

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12 3.2.4 Overall performance effectiveness

There exist productivity measurement tools that include more losses than those proposed in OEE, one of which is the overall performance effectiveness (OPE). OPE is used to measure all losses related to production, in which losses are measured by either production losses or time losses (Muchiri & Pintelon, 2008). OPE can be explained best by illustration, see Figure 4. Note that the differences between the different frameworks is also indicated in Figure 4.

3.2.5 Resource effectiveness in healthcare

Based on the OEE, Vissers and Beech (2005) propose a framework for assessing the performance of resource effectiveness of hospital departments (Figure 6). Explanation continuous below the figure.

Figure 6. Capacity concepts for resources. Reprinted from “Health operations management: patient flow logistics in health care” by J. Vissers and R. Beech, Psychology Press.

The following definitions apply to Figure 6:

• Potential capacity is the total amount of resources (in theory) available.

• Available capacity is the total capacity that is actually available. Non-available capacity is due to for example staff illness or equipment shortages.

• Usable capacity is the capacity that is actually used. A part of this is non-usable capacity due to for example restrictions posed by hospital top management.

• Utilized capacity is the capacity that is actually used, in contrast to idle capacity which is available capacity that is not used, for example since there is no demand and the bed is empty. • Productive capacity is the capacity that is actually assigned to treat patients. Set-up capacity is

lost due to for example preparations of operations rooms or beds.

A similar framework was proposed by Reinsma (2017). Reinsma adopted an overall resource effectiveness (ORE), similar to the OEE approach, and validated his developed framework at the surgery nursing ward in the UMCG. He defined three loss categories and assigned loss factors to each category. The categories and corresponding loss factors are:

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• Productivity. Loss factors included speed losses (e.g. delayed surgery) and waiting times • Quality. Loss factor is patient with complications.

3.2.6 Reflection - towards a framework for nursing wards

The discussed approaches all have a similar goal: to provide an explanation of how capacity (whether time or resources) is spent by identifying different types of capacity losses. There exists, however, some significant differences between the approaches.

Timeframe

All approaches are similar in a way that they should be able to explain 100% of the time being considered. Losses are formatted in percentages and deduced from the 100%. What is left is the resource effectiveness. The models do, however, differ in what timeframe is considered. The OEE disregards planned downtime and only focusses on planned production time. This is unsuitable for a nursing ward, where planned downtime (e.g. due to staff shortages) can play a significant role. More suitable is the TEEP approach, which considers 24/7 365 days a year, like in a nursing ward. Also, OFE and OPE consider an entire year when determining resource effectiveness and are hence also suitable to be applied at a nursing ward.

System complexity

As discussed in section 3.1.1, a nursing ward is integrated in a highly complex and variable environment of a hospital. A nursing ward cannot be viewed as a system in isolation, which causes that an OEE approach cannot be adopted. Similar, the TEEP approach views systems as isolated and is hence not suitable. Argumentation often provided with the OFE that processes are a complex web of interaction among resources, people (staff), and departments, is more suitable for a nursing ward. Similar argumentation causes that the OPE approach is also suitable to be applied at a nursing ward.

Scope

As illustrated in Figure 4, the models consider different scopes for identifying capacity losses. Both OEE and TEEP only consider operation related losses. Additional internal business-related reasons are included in the OPE approach. In addition, also external reasons like commercial related losses or logistic related losses are included in the OPE, hence considering the widest scope for identifying capacity losses. Since a nursing ward is integrated in a highly complex and variable environment, it is important to consider also external reasons for capacity loss, and therefore it is important to use a wide scope.

The OPE approach is hence the most suitable approach to be applied to a nursing ward. It provides the broadest scope for identification of capacity losses, considers systems as complex integrated systems which is like a nursing ward, and also includes planned downtime which can play a significant role for nursing wards. The OPE framework thus will provide a basic construct (i.e. the loss categories (Figure 4)) for the development of a framework for assessing the effective use of resources at nursing wards.

3.3 Nursing ward capacity losses

This section acts as a starting point of exploring different types of loss factors that can be found in a nursing ward by discussing several methods used for doing so. Insights that will be obtained contribute to linking the different loss factors to loss categories of the OPE, similar to Figure 4.

3.3.1 Total productive maintenance

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systematically works to reduce seven types of waste (Muda), mainly by the approach of Kaizen (Borris, 2006). By using eight pillars of activity, TPM focusses on achieving “zero” losses (e.g. zero waiting time or zero motion of employees) and maximal equipment effectiveness. Note that the term zero does not imply that it should not exist, but rather implies not more than the absolutely minimum. Deduced from TPM is the concept of Lean manufacturing.

3.3.2 Lean manufacturing

Doing more with less, that is the essence of Lean manufacturing. Lean focuses on speed and doing this right the first time, with less people, less time, less inventory, and less money. One of the concepts of Lean manufacturing is to reduce non-value-added activities like motion, overproduction, correction, inventory, underutilization of human resources, and transportation (Feld, 2001).

Lean manufacturing applied to a healthcare setting has been widely studied in literature (e.g. Wysocki, 2004; Radnor & Boaden,2008; Womack & Miller, 2010). Elijz et al. (2008) provide a checklist for healthcare managers to evaluate whether introducing Lean is valuable for their department. Lean in healthcare is based on three main pillars: process estimation, patient-oriented management, and engaging and leading employees (Lindenau-Stockfisch, 2011). The next sections describe each of these three phases, which serve as initial direction for identifying loss factors.

Process optimization

As previously mentioned, Lean focusses on reducing waste (muda). According to (Graban, 2008), the following types of waste – including examples – can be found in nursing wards:

• transportation: unnecessary movement of patients and equipment • motion: unnecessary movement of staff. Often paired with transportation • defects / errors: wrong medication or wrong use of (technical) equipment

• waiting: patients waiting for treatments or employees waiting due to a non-streamlined workflow (e.g. physicians waiting for lab results)

• inventory: excess storage and supply that increase costs for handling goods

• overproduction: any task that is carried out without actual need (e.g. double examinations due to miscommunications)

• over processing: any task that is designed to add value to patients but is not aligned with patient needs (e.g. scheduling too many tests)

• human potential: failure of leadership or not enhancing employees’ participation in the improvement process (e.g. not recognizing talent of staff members).

Regardless of the type of waste and which combinations are present, waste decreases value since resources are not allocated adequately (Lindenau-Stockfisch, 2011). To stress again, since hospitals are often bounded by budget and or space, it is desired to use available resources as effective as possible. Hence, the presence of waste is not desired and should be minimized.

Patient-oriented management

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15 Engaging and leading employees

Besides processes and patients, employees are critical in hospitals. Lean promotes reflected interaction with employees to obtain higher outputs. Employees can provide first-hand information about the processes and possible improvements. It is therefore important to engage with and lead the employees. For this reason, it is chosen to involve employees (MDL nursing ward staff) in the process of developing the framework.

Using Lean as method to identify loss factors

Building on the third pillar – engaging employees – quality improvements and waste reductions in hospitals require a systematic process where “all employees (managers, physicians, nurses, laboratory people, technicians, office people etc.) actively participate in identifying and reducing non-value-adding activities (waste)” (Dahlgaard, Pettersen, Dahlgaard-Park, 2011). A widely adopted method used to involve employees in identifying waste is by using non-structured interviews (Worley & Doolen, 2006). Non-structured interviews serve as initial information regarding waste losses. The main idea is that employees are the ones that are aware of the losses that occur at a nursing ward, and hence they should be questioned. A more structured, long-term approach used for identifying losses can be found in (Dahlgaard, Pettersen, Dahlgaard-Park, 2011). Due to time restrictions, using non-structured interviews is more suitable for this research. In agreement with Dahlgraard, Pettersen, and Dahgaard-Park (2011), it is important to perform non-structured interviews with employees executing different functions, i.e. managers, head doctors, nurses, and head nurses.

3.3.3 Non-necessary stay

Patients that stay at a nursing ward unnecessary from a medical point of view contribute to capacity loss of the nursing ward. Panis, Verheggen, and Pop (2002) developed an instrument “to assess the appropriateness of hospital stay and to identify the causes of in appropriateness”. Five internal and surgical departments in the University Hospital of Maastricht with a total capacity of 700 beds were assessed using the instrument. Results showed that that 26.8% of the hospital stay was inappropriate. Similar results are found by Carey, Sheth and Braithwaite (2005), that propose a similar instrument which can be used to “detect, quantify, and characterize delays that unnecessarily prolonged hospitalization”. A case study using the instrument at 16 departments of a tertiary care university-affiliated teaching hospital showed that 13.5% of all patients stayed unnecessary.

As both hospitals investigated in the above-mentioned studies are like the UMCG, their results are likely to apply to the UMCG to. Both studies found similar reasons for unnecessarily prolonged hospitalization (loss factors). Difference was made between reasons of the hospital itself that influence the unnecessary stay (e.g. problem with medical staff) as well as reasons outside the hospital that preventing patients from leaving the hospital (e.g. no transportation available or failing to deliver take-home medication on time (also supported by Lees (2012)). The most significant capacity losses are listed below. The case study performed in this research will conclude whether these losses hold for the MDL nursing ward to.

• No bed available in other skilled care/nursing facilities

• Delay in medical procedures such as consultations, diagnostics, lab results, and surgery • Delay in discharge planning/procedure.

• Primary care not available

Using non-necessary stay as method to identify loss factors

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whether a patient stays unnecessary or not, patient by patient. Both appendices (A and B) provide an instrument which can assist in the process (Carey, Sheth & Braithwaite, 2005).

3.4 Main findings literature study

The manufacturing domain provides several methods to assess resource effectiveness. The OPE approach provides the most wide-scoped framework and hence most suitable for the highly integrated system of a nursing ward. The main structure of the OPE, consisting of the generic loss categories, is suitable for applying at a nursing ward. Identification of the individual loss factors is partly covered in section 3.3, although the remainder is yet to be performed by the case study. In conformity with Lean philosophy, loss factors will be identified by using non-structured interviews with employees executing different functions such as a manager, head nurse, and head doctor. In addition, the non-necessary stay instrument provided by Carey, Sheth, and Braithwaite (2005) can also assist in identifying loss factors. Figure 7 illustrates the basic construct of the proposed framework, while Table 1 provides additional explanation of the loss categories by providing several examples.

Figure 7. Basic construct for the proposed overall performance effectiveness framework for nursing wards

Loss category Loss factor Source

Regulations Government regulations,

hospital wide regulations

AZNN, 2018; Bittencourt et al., 2018; Lees, 2012

Logistic related

No bed available in other skilled facility, (take-home) medication supply failure

Carey, Sheth & Braithwaite, 2005; Lees, 2012; Panis, Verheggen & Pop, 2002

Business related

Suboptimal planning, human potential loss, discharge procedure not completed

Bittencourt et al., 2018; Carey, Sheth & Braithwaite, 2005; Graban, 2008; Lindenau-Stockfish, 2011; Panis, Verheggen & Pop, 2002;

Process related

Delay in medical procedures, transportation, motion, overproduction, over

processing, planned downtime, unplanned downtime

Aboshaiqah, 2016; Bittencourt et al., 2018; Carey, Sheth & Braithwaite, 2005; Graban, 2008; Lindenau-Stockfish, 2011; Panis, Verheggen & Pop, 2002;

Medical related

Defects/errors, complications Graban, 2008; Lindenau-Stockfish, 2011

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4. SYSTEM DESCRIPTION

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4. SYSTEM DESCRIPTION

This chapter discusses the case study system by introducing the UMCG nursing ward in section 4.1. The subsequent sections 4.2 - 4.6 each discuss a part of the system.

4.1 MDL nursing ward system

The MDL department consists of three separate (both functional as locational) sectors: the nursing ward, the endoscopic center, and the outpatient department. The nursing ward deals with the treatment and care of patients. The endoscopic center provides (advanced) internal investigations regarding both lungs and MDL related diseases. The main goal of the endoscopic center is diagnosis of the disease. In some cases, an additional goal can be treatment, e.g. removal of a polyp. The outpatient department provides diagnosis and minor treatment for patients that do not need to stay overnight. Note that, in contrast to other hospitals (e.g. Haagland Medisch Centrum, n.d.) the outpatient department is located within the UMCG.

Figure 8 illustrates the flow diagram (system) of the MDL nursing ward. The system boundaries are limited to the patient inflow sources, the MDL nursing ward (C3VA) process, and the patient outflow destinations. The description of the system continuous below the figure.

Figure 8. Flow diagram MDL nursing ward

4.2 Patient inflow

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18 Emergency patient sources

• Other hospitals. UMCG is the most specialized hospital in the northern Netherlands. In addition, the UMCG is a so called ‘tertiary healthcare provider’.

“Tertiary care is specialized consultative care, usually on referral from primary or secondary medical care personnel, by specialists working in a center that has personnel and facilities for special investigation and treatment. (Secondary medical care is the medical care provided by a physician who acts as a consultant at the request of the primary physician.)” (John Hopkins Medicine, 2011).

Hence, other hospitals that lack the expertise for a certain treatment or are stuck at diagnosing, transfer the patient to the UMCG and in some cases to the MDL nursing ward. It does happen that also patients without complicated care needs are transferred to the UMCG, but this is not the focus of the UMCG.

• Other departments. Patients can be transferred from other departments to the MDL nursing ward for three reasons:

- Other departments/ nursing wards do not have sufficient capacity to host the patient.

When the MDL nursing ward does have capacity left, the patient is transferred. Each morning there is a short meeting in which multiple departments discuss the capacity available for other department’s patients.

- Patients that initially should be hosted at the MDL nursing ward but were transferred

to another department due to capacity issues, are transferred back as soon as possible.

- Patients that have multiple or complex diseases but at some point, only require

MDL-related treatment are also transferred to the MDL nursing ward.

• Emergency department. Patients that arrive at the emergency department and need MLD-related treatment or diagnosis are transferred to the MDL nursing ward.

• Outpatient department. As depicted in Figure 9, the outpatient department is part of the MDL department. To recall, the outpatient department provides diagnosis and minor treatment for patients that do not need to stay overnight. In some cases, the patient’s situation is deemed urgent and the patient needs to be transferred directly to the MDL department. In non-urgent situations, the patient is sent home. In case the patient does need to be taken in the MDL nursing ward at a later stage, the patient is deemed as an elective patient and belongs to the elective patient source ‘from home’, as will be discussed later.

• Endoscopic center. The endoscopic center is also part of the MDL department. Like the outpatient department, if the patient’s situation is deemed urgent, he or she will be directly transferred to the MDL nursing ward.

Elective patient source

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4.3 MDL nursing ward care process

Admission

Patients are admitted by a member of the nursing staff. During the admission, multiple questions are asked to the patient which are important to know for diagnosis or treatment (e.g. use of alcohol or drugs). In addition, several tests like measuring blood pressure are performed. If a bed is available, the patient is transferred to his/her bed and is explained how the nursing ward works and what the patient can expect. In some cases, the patient is told his/her expected length of stay at the nursing ward. Elective patients are asked to be present at a certain time for their admission, whereas emergency patients of course cannot be planned and are admitted once they reach the nursing ward.

Diagnosis

In case a patient’s cause of complaint or disease is unknown, the patient needs diagnosis. Although diagnosis is almost always paired with treatment, it does represent a different functional process. Diagnosis can be performed at the nursing ward itself (physically) but is also performed in combination with other departments like radiology. During the entire process the patient occupies a bed at the nursing ward.

Treatment

If a diagnosis is set or was already known (e.g. with chronic diseases like Chrohn), a patient is left with the functional process of treatment. Treatment varies among patients and since it is not the main focus for this research, it is not discussed in further detail.

Dismissal

At some point, from a medical perspective, the patient is in sufficiently well condition to be dismissed from the MDL nursing ward. Besides the condition of the patient, several factors must be considered before actual dismissal can take place. These include, but are not limited to, whether transport is available, whether take-home medicines are available, whether the dismissal procedure is set in motion, and several factors related to the patient’s destination, as discussed in the next subsection.

4.4 Patient outflow

Factors that should be considered before dismissal and transferring the patients to their destinations, are the capacity of the destination and the patient’s care needs. It can happen that a patient needs certain treatment which the staff at the destination does not have sufficient knowledge of. In that case, the MDL nursing ward is asked to retrain the staff. For hospitals, institutions, and departments staff implies the actual staff, whereas staff related to patients send home are usually homecare employees.

Other hospitals

Patients that do not need the level of expertise offered in the UMCG but do need to be monitored by nursing staff can be transferred to other hospitals.

Other institutions

Patients that cannot be transferred to their own home for some reason can be transferred to other (care) institutions. Examples are nursing homes and revalidation centers.

Other departments

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undergo surgery are also dismissed from the MDL nursing ward (and transferred to the operation room or surgery nursing ward).

Home

Patients that that are not transferred to one of the three above mentioned destinations are send home.

4.5 Resources

Key resources at the MDL nursing ward consists of staff, beds, medical equipment, motion equipment (e.g. patient lift or bed mover), medicines, technological equipment, and miscellaneous resources. The different staff functions are illustrated in Figure 9. In general, hospitals in the Netherlands experience a shortage in staff available (UWV, 2018), and this also poses a problem for the MDL department. In case staff is not sufficiently available, beds will be closed, which in turn decreases capacity. Besides the nursing ward’s own resources, the ward is affected by shared hospital resources like laboratories, or medical imaging facilities. For example, patients that might need to wait several days for laboratories results when the laboratory is busy.

Figure 9. Organogram MDL department

4.6 Planning

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21 The planning process can be described as follows

1. Doctors place bed orders for patient’s in Epic, the UMCG digital work environment. Bed orders for elective patients are usually placed several weeks in advance, whereas orders for elective patients are placed once the emergency department concluded that the patient need to be hosted at the MDL nursing ward.

2. Planning nurses are notified by the open bed orders in Epic, and simultaneously control the capacity planning. The available capacity depends on staff availability, patient characteristics (e.g. prisoners, patients that need to be isolated), and the planning (beds are usually reserved for patients that are taken in the next day). Also, recently, there was a large shortage of beds in most of the hospitals in the Northern Netherlands due to a flu outbreak. A regional-wide cooperation of hospitals forced the MDL nursing ward to reserve several beds for these flu-related patients.

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5. FRAMEWORK DESIGN

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5. FRAMEWORK DESIGN

This chapter provides the development process of the framework as well as the framework itself. The development process of the framework will be described in section 5.1. Obtained loss factors from execution of the development process are discussed in section 5.2. The framework which can be used to assess the effective use of resources at nursing wards is presented in section 5.3. Recommendations of how to quantify the loss factors of the proposed framework are provided in section 5.4.

5.1 Framework set-up

The development process of the framework is discussed in this section. The applied methods and obtained insights of those methods is first discussed. Second, the different employees interviewed during this research are discussed. Third, the structure of the interviews is explained.

5.1.1 Methods and insights

Lean theory suggests involving staff in improvement processes (Ohno, 1988). Its importance has been widely recognized in the healthcare industry (van Rossum et al., 2016). Lean in healthcare, as being used in this research is defined as follows.

Lean healthcare is a management philosophy to develop a hospital culture characterized by increased patient and other stakeholder satisfaction through continuous improvements, in which all employees (managers, physicians, nurses, laboratory people, technicians, office people etc.) actively participate in identifying and reducing non-value-adding activities (waste) (Dahlgaard, Pettersen, Dahlgaard-Park, 2011)

In conformity with Lean healthcare as defined above, non-structured interviews were held with employees executing different functions. The goal of these non-structured interviews was to identify loss factors in a qualitative way. During these non-structured interviews, a survey was used to assist in identifying loss factors related to non-necessary stay of patients (Appendix B).

5.1.2 Employees interviewed

As described above, employees were interviewed to qualitatively identify loss factors. The following employees were interviewed. A motivation why that particular employee was interviewed is also provided. The main idea behind interviewing employees at different functions is to obtain a comprehensive list of loss factors.

• The manager of the MDL department was interviewed because he is responsible for all commercial/ financial related interests of the nursing ward. Based on literature, it was not expected that a nursing ward experiences commercial related capacity loss. To validate this, the manager was interviewed.

• The head doctor was interviewed because it was expected that he should be aware of all medical related losses, as the head doctor is final responsible for all medical related decisions at the nursing ward.

• The head nurse was interviewed because she is responsible for all the nurses, planning nurses, trainees, the quality of the nursing ward, and efficiency of the nursing ward. Loss factors related to those responsibilities thus should be known by the head nurse.

• The doctors of the MDL department are responsible for medical decisions regarding patients. Doctors were interviewed in addition to the head doctor – to identify medical related losses – to obtain information from other points of view as well.

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5. FRAMEWORK DESIGN

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(new) patients. If the available bed capacity must be decreased (as a result of loss factors), they are the ones who are aware of it.

• Nurses were interviewed as they are the ones who execute most of the daily (care) tasks. Non-value-added activities are usually well known by nurses (e.g. searching for medicines) and experienced on a daily basis. Although, in principle, the head nurse should be aware of such loss factors, in practice it is found that nurses do not always communicate their ideas. Hence, it important to interview (several) nurses as well.

5.1.3 Interview structure

Although the interviews were unstructured in a sense that (not all) questions were prepared in advance, a similar structure was used in each interview. The structure can be described as follows:

1. Start with providing some background information about this research, the goal of this research, and what kind of frameworks exists for identifying capacity losses in the manufacturing domain (mostly the OEE was explained due to its simplicity). This background information should provide the interviewee with sufficient information to understand the goal of the interview.

2. Ask the interviewee what kind of tasks, activities, and responsibilities they perform/have on a ‘regular’ day. Also ask what differs on a non-regular day. The idea is to obtain a clear image of the interviewee’s daily processes.

3. Proceed by asking what kind of loss factors they experience during their daily processes. 4. Validate loss factors mentioned by other interviewees by asking whether he/she recognizes

them.

5. In case planning nurses are interviewed, the non-necessary stay survey instrument (Appendix B) was used, as planning nurses are aware of the inflow and outflow, and possible loss factors related.

Please note that these non-structured interviews were performed iteratively, so several employees were interviewed more than once. The loss factors need to be validated by other employees, preferably by other functions, as well. This increases the validity of the loss factors. The next section will discuss the results from the interviews.

5.2 Framework loss factors

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5. FRAMEWORK DESIGN

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Figure 10. Flow diagram MDL nursing ward indicating capacity losses 5.2.1 Patient inflow related losses

1. ‘Non-complicated’ admissions. As discussed earlier, the UMCG is a specialized hospital which focusses on highly complex care. It turns out that in some cases, the MDL nursing ward admits patients with relative simple care needs. In principle, these patients do not belong at the UMCG and should be admitted at another hospital in the region. These patients occupy a bed which otherwise is allocated to a patient with complicated care needs, and hence is seen as capacity loss.

2. Late arrival patients. Sometimes, patient’s admission that should take place in the morning, takes place in the evening due to late arrival of the patient. Hence, care tasks cannot be performed at the designated time and hence is seen as capacity loss.

3. Expectation management patient. During admission, the patients are sometimes told their expected length of stay. To illustrate the loss related to mismanagement of patient’s expectations, consider the following example: a patient is told at the outpatient department that he/ she should be counting on a stay of six days at the MDL nursing ward. It turns out that the patient can leave at the third day. However, the patient refuses to leave since he/she was told that his/her stay would be six days and demands to stay for three more days (e.g. since it provides a safe feeling being at the nursing ward instead of at home). The patient is not forced to leave and hence occupies a bed unnecessary for three more days. This is seen as capacity loss.

5.2.2 Process related losses

4. Unnecessary admission. The head doctor pointed out that patients are admitted sometimes unnecessary from a medical point of view due to for example social indication (feeling of safety), or that the doctor is pressured by patient or family. These admissions result in not performing the right tasks for the right patient and hence is seen as capacity loss.

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5. FRAMEWORK DESIGN

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6. Regional bed allocation. Bed capacity issues does not only hold for the MDL nursing ward, but also on a larger regional scale. To cope with a significant flu outbreak, the hospitals in the northern Netherlands started an initiative together with ‘Acute Zorgnetwerk Noord-Nederland (AZNN) to deal with bed capacity issues (AZNN, 2018). The regional point for bed capacity (regiopunt beddencapaciteit) checks the bed capacity of all hospitals in the northern Netherlands three times a day. To illustrate: consider a situation where an ambulance picks up an emergency patient. The ambulance contacts the regional point, which tells the ambulance to which hospital the patient should be brought. Due to this initiative, the MDL nursing ward is obligated to reserve several beds, which decreases their capacity.

7. Beds unavailable (planned). Beds unavailable (planned). Beds are sometimes made unavailable, meaning it cannot be occupied by a patient and hence decreases the capacity of the MDL nursing ward. This can be due to the following reasons:

- Contact isolation: of a patient at a multiple patient room.

- Staff shortages: it decreases the number of patients the staff can handle

- Care intensity: some patients require a high intensity of care. To illustrate, one nurse is allocated to about four patients with regular care needs. However, some patients require one-on-one care (e.g. small intestine transplantation patients). This means that the capacity is decreased by three patients.

- Mentally confused patients: they might pose a danger to other patients and hence when placed at a multiple patient room, the other beds might be made unavailable. - Prisoners: prisoners need to be accompanied by guards are placed at multiple people

rooms because the guards also stay overnight. Logically, the other beds are closed due to safety reasons.

- Rooming-in: patients that are being cared by family members due to for example a language barrier or mental illness.

- (weekend) leave: depending on the medical condition, patients are sometimes allowed to leave the nursing ward during the weekend. During this period, their bed is reserved for them.

8. Beds reserved. Beds are reserved for two reasons:

- For patients that are transferred to the intensive care beds are reserved for a maximum of 24 hours

- Beds are reserved when one patient is dismissed, and the next day an elective patient needs admission. So, this bed is unavailable for one day, while in fact it is empty. 9. Beds unavailable (unplanned). Beds can also be made unavailable for unplanned reasons like

staff illness.

10. Non-value-added activities. Activities that do not contribute to a patient’s health are deemed unnecessary. Although staff believes it does not directly affect capacity, they acknowledge that it increases workload. Increasing workload, if not managed, can lead to capacity loss due to staff illness (e.g. burnout). Examples of non-value-added activities are:

a. Searching for medicines b. Searching for equipment

11. Waiting for other departments. Waiting for other departments is used as umbrella term but includes waiting for scarce hospital resources like the operation room (surgery), MRI scans, or X-ray.

University of Groningen Faculty of Economics and Business Technology and Operations Management

Master Thesis

A framework for assessing the effective use of

resources at nursing wards

ABSTRACT

PREFACE

TABLE OF CONTENTS

LIST OF FIGURES

LIST OF TABLES

LIST OF ABBREVIATIONS

1. INTRODUCTION

2. PROBLEM DESCRIPTION AND RESEARCH DESIGN

2.1 Problem background

2.2 Research objective

2.3 Conceptual model

2.4 Research design

3. THEORETICAL BACKGROUND

3.1 Nursing wards

3.2 Measuring resource effectiveness

3.3 Nursing ward capacity losses

3.4 Main findings literature study

4. SYSTEM DESCRIPTION

4.1 MDL nursing ward system

4.2 Patient inflow

4.3 MDL nursing ward care process

4.4 Patient outflow

4.5 Resources

4.6 Planning

5. FRAMEWORK DESIGN

5.1 Framework set-up

5.2 Framework loss factors