Improving healthcare : focus on flow in processes

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Improving healthcare: focus on flow in processes

‘If you can’t describe what you are doing as a process, you don’t know what you are doing’ - W. Edwards Deming

Instructor: prof.dr. R.J.M.M. Does Author: Margriet F.C. de Jong

Contact details:

e-mail: margrietdejong83@hotmail.com phone: +31-6-47660157

Date of submission: 20-12-2016 Confidentiality restrictions: none.

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Executive Summary

Healthcare systems worldwide and in particular in The Netherlands seem not to provide optimal quality considering the six dimensions of the Institute of Medicine, meanwhile healthcare spendings are rising yearly. Studies report that improvements in efficiency, effectiveness, safety, patient-centeredness, timeliness and equity can be made with process improvement methodologies. This case-study in the outpatient clinic of kidney

transplantation in a large academic medical center in The Netherlands investigated whether efficiency could be improved with a process improvement project following the

methodology of Lean Six Sigma. Focus was put on process-working and work-flow. The objective was to increase efficiency of the throughput time for the transplant-nephrologists and thereby retrieve a reduction of costs of personnel. Team members from all departments involved participated, including the Department Chair (the Champion) and the Black Belt. Critical-to-quality-characteristics (CTQs) were defined as processing time per task, file processing number and undertreatment frequency. Data of the work-flow of the transplant-nephrologists and of the laboratories of clinical chemistry, virology and pharmacy were collected and analyzed. The results were discussed in two team meetings. Three process improvements were assessed and prioritized to reduce the CTQ processing time of afterwork for the nephrologist from 150 to 10 minutes and the file processing number from 4 to 2 times: collaboration with regional laboratories, increasing the frequency of laboratory assessments and renewal of laboratory equipment.

This case-study is a practical example of how efficiency can be improved by focussing on healthcare processes and work-flow by performance measurements with analyses of data. Communication of these data leads to better integration of information throughout the corporate business, and thereby to incentives to improve. When management of healthcare organizations would incorporate the continuous improvement loop in the strategies and quality systems of their business control plan, the business could better align with the continuous changing environment. Furthermore, it may facilitate the interaction between patients and medical professionals, and may increase quality in terms of patient value and employee satisfaction, and affordable price.

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I. Introduction

Goal of healthcare systems and the Dutch healthcare system in particular is to deliver high-quality healthcare for an affordable price (Porter and Teisberg (2004), Christensen et al. (2009), Pomp (2010), Kaplan and Porter (2011), McClellan and Rivlin (2014), Institute of Medicine (2015)). It can be discussed however, whether both aspects of quality as well as affordable price are optimally addressed. Namely, as shown by others, although patient value should be what it is all about for healthcare providers, the current healthcare system beholds that most healthcare providers do not primarily focus on the quality aspect

particularly considering what is most valuable for the patient (Christensen et al. (2009), Verlet and Devos (2010), Kaplan and Porter (2011), Cullen et al. (2012)). Healthcare

providers seem not to fully engage to the job that needs to be done: meeting the patient’s needs. Instead of focusing on producing health, they focus on providing healthcare services. Furthermore, with respect to the second aspect of the goal of the healthcare system, healthcare costs are rising every year in The Netherlands (CBS (2015), CBS (2016),

Zorgwijzer.nl (2016)). This increase is a national topic with the important question how to mitigate. An important solution to improve both aspects may arise by focussing on processes, in which flow and performance measures are key components (Kaplan and Norton (2004), Kaplan and Norton (2008), Cullen et al. (2012), Hogan et al. (2012), Black et al. (2016)).

A. Quality

In healthcare no universally accepted definition for quality exists. The definition of the US Institute of Medicine (IOM) is often used. The IOM defines quality as ‘the degree to which health services for individuals and populations increase the likelihood of desired health outcomes and are consistent with current professional knowledge’ (Health Foundation (2013)). Herein, the IOM identifies six dimensions that healthcare needs to be: safe, effective, patient-centered, timely, efficient, and equitable (Institute of Medicine (2015)). These dimensions express what the core business of a healthcare provider should be:

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5 delivering value to the patient and meet the patient’s needs. For most patients these are: better health or being healthy. However, many healthcare providers tend to focus on their output, the healthcare services, instead of their outcome, producing health (Verlet and Devos (2010), Cullen et al. (2012)).

The healthcare system is a complex and adaptive system with many stakeholders and in which intelligent agents, i.e. the professionals need to adapt their behaviour to a changing environment (Rouse and Serban (2014)). Quality problems may arise from the changing environment and changing context in which the professionals perform their jobs. In this complex system, several aspects are proposed that draw attention to the services performed instead of to the patient’s values. For instance, healthcare has a growing complexity of science and technology and it has difficulties in exploiting the revolution in information technology (Rouse and Serban (2014), Institute of Medicine (2015)). Furthermore, it has an increase in chronic conditions. Perhaps most importantly it has a poorly organized delivery system (Institute of Medicine (2015)). This latter aspect causes the current healthcare system to not making best use of its resources. This may lead to, for example, for the patient to long waiting times after referral to a specialist, waiting times in waiting rooms to see a physician, waiting times to getting the diagnosis, waiting times to treatment. For employees it may lead to doing re-work or to spend too much time on administration. It is a challenge to eliminate all entities in the delivery system that causes these and other forms of waste.

B. Affordable price

Second component of the goal of healthcare is an affordable price. Healthcare costs in many countries are increasing, but the healthcare system in The Netherlands is one of the most expensive in the world. This is shown by high expenses per capita and high expenses per gross national product (ZorgWijzer.nl (2016)). These costs have been rising every year (CBS (2015), CBS (2016)). However, efficiency and effectiveness of healthcare systems are

questioned (Porter and Teisberg (2004), Kaplan and Norton (2008), Verlet and Devos (2010), Cullen et al. (2012)). Therefore, healthcare providers in The Netherlands are urged to

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6 decrease their costs but to still keep improving their quality (Pomp (2010)). Meanwhile, the Dutch Authority of Healthcare (NZa) has the task amongst others to decrease the

surveillance burden such that healthcare providers should better control costs (NZa (2009)). Therefore and even worldwide, healthcare already has been an easy target for implementing new tools and strategies that have been proven successful by other industries (Kaplan and Norton (2008), Van der Zande and Strikwerda (2008), McClellan and Rivlin (2014)). A well-known example is Lean manufacturing. The strategy of Lean manufacturing was originally developed by Japanese motor companies and also implemented in US aviation industry, amongst others. Core of Lean manufacturing is to eliminate waste from the process and to have zero-defects (Spear and Bowen (1999), Black et al. (2016)). Some studies

showed that this methodology could also in healthcare improve efficiency without adding expense and thus increase benefit/cost ratio (Parks et al. (2008), Hogan et al. (2012), White et al. (2015)). However, many healthcare providers up until now have not integrated such a strategy in the daily work processes.

C. Processes

Important aspect of Lean manufacturing but also shown by other improvement

methodologies, is that evaluating an organization in terms of work processes may increase value and decrease costs by identifying and eliminating activities that do not add value (Foster et al. (2007), Juran and Godfrey (1998), Spear and Bowen (1999), Porter and Teisberg (2004), Komashie et al. (2007), Kaplan and Norton (2008), Pomp (2010)). Thinking in terms of work processes instead of structure (hierarchies, departments) forces to better allocate resources across activities. This will maximize the value of the service to the patient rather than maximize the financial value to specialties or departments. For example, one of the most important resources is human capital. Process thinking helps to making best use of this resource by optimal scheduling, but also by delivering support to and facilitate professionals instead of control them (Ghoshal and Bartlett (1999)). Process thinking may help to increase

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7 their but also other resources’ efficiency (Ghoshal and Bartlett (1999), Kaplan and Norton (2008), Pomp (2010), Cullen et al. (2012), Black et al. (2016)).

Flow is a key word in improving work processes and thereby in optimizing value delivery. Goal is to achieve work processes without waste. Seven forms of standard waste are distinguished: motion, transportation, waiting, rework, overproduction, processing, inventory, and defects. Continuous flow leads to eliminate waste and to better

corresponding to demand. Flow is sometimes referred to as ‘a batch size of one’ (Rouse and Serban (2014)). Demand, capacity and flow need to match each other in order to deliver optimal value. One can try to find the perfect match by first measure actual performance and secondly compare actual performance with goal performance. These performance measures also show the contribution and capacity of all resources including that of the professionals (Bower (1966)). Finally they may help with improvement to the goal

performance (Juran and Godfrey (1998)). Namely, when performance is measured and goals are set, waste can be eliminated. In healthcare, less deficiencies in processes lead not only to less costs but also to higher quality (Juran and Godrey (1998)).

In order to create these performance measures, data are needed. Data are helpful to improve processes and inform organizations about their performance. Analyzing data with statistical process control tools can give information about a process whether staying within acceptable limits, and if not, whether corrective actions could improve the process (De Mast et al. (2012)). In this way, operational data can be analyzed and translated into knowledge and better decision-making (Rouse and Serban (2014)). However, although information technology is more and more advanced, in daily healthcare practice the capabilities of technology are not optimally integrated. Getting data is easy, but getting useful data somewhat less (Haux (2006), Guillemette and Paré (2012)).

The question thus remains how we can improve healthcare quality and in the mean time mitigate the rising healthcare costs. It seems that still many processes in healthcare are far from having optimized flow and still are redundant with waste. In this thesis, the objective is to study this question by mapping and evaluating the outpatient clinic of an academic medical center as an everyday practice in terms of work-flow. The hypothesis is that the

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8 results will show easy contributions of improving patient value and reducing healthcare costs. Therefore, a process improvement project was undertaken in an academic medical center in The Netherlands. The project focused on the outpatient clinic of the Department of Nephrology, subdivision Kidney Transplantation. The aim of the project was to investigate the amount of waste in productivity of the professionals and whether improving work-flow could reduce this waste.

II. Framing

This paragraph describes the concepts and frameworks that are used to study the problem of this thesis. The first is the choice of the setting in which the real-life case will be studied, namely an academic outpatient clinic. The second is the methodology of Lean Six Sigma that is used to study the case. Finally, the value stream map and process statistics used in the case-study are explained.

A. Setting

A large academic medical center was chosen to perform the prospective case-study. This case was used as a real-life cohort to investigate the efficiency of healthcare working in an outpatient clinic of an academic medical center. Especially in academic centers, employees often experience performing their patient care as inefficient and slow (Aschenbrener (1996)). Academic staff experiences this inefficiency mainly because of workload, work scheduling, role conflict, role ambiguity, the magnitude of administration and job control (Catano et al. (2010), Ylijoki (2013)). The outpatient clinic was chosen as the subject of the research, since in the academic outpatient clinic many patients are treated in the same process because of its specialization for patients with similar conditions. The outpatient clinic is one of the main outputs of hospitals and their daily practice. Process improvement in

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9 this area of patient care may thus lead to a large benefit in terms of optimizing patient care and thus patient value, but also in reducing waste, increasing efficiency and work-flow for the professionals and through all reducing costs. In this study, the outpatient clinic of kidney transplantation was chosen.

B. Methodology

The case was studied within the methodology of Lean Six Sigma (LSS). LSS is a management structure and methodology for organizing improvement activities, mainly for cost reduction and quality improvement (Bisgaard (2009)). LSS has been proven successful in industry, but has successfully been used in healthcare the last decades as well (Parks et al. (2008), DelliFraine et al. (2010), Niemeijer et al. (2011), Schoonhoven et al. (2011), De Mast et al. (2012)). LSS executes values that fit management of quality and safety issues, namely continuous innovation and improvement, focus on the customer, data-driven decisions, and focus on the issues that determine performance (Bisgaard (2009)). LSS focuses on routine operations within processes and aims to make these more efficient and more effective. LSS aims to eliminate waste and to optimally make use of scarce resources. The methodology of LSS is not a strategy itself but is meant to be used as a tool to implement, execute and leverage the designed strategy of the business (De Mast et al. (2012)).

LSS has a project-based and structured approach. The methodology for quality improvement in LSS is the research-based methodology known as DMAIC: Define – Measure – Analyze – Improve – Control (Bisgaard (2009)). These five phases are the guide throughout the improvement project. Firstly, the problem is defined and a cost-benefit analysis shows the usefulness of the project. Project objectives are specified. A team is composed with a Champion from the management and an employee as Green or Black Belt who executes the project. Secondly, critical-to-quality-characteristics (CTQs) are defined and they are

measured as baseline data in the measure phase. The validity and reliability of this

measurement process is examined. Thirdly, in the analyze phase, the team tries to find the cause for quality problems in the process and waste. They identify influence factors with

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10 help of tools focused on results. The diagnosis is made complete. Fourthly, in the improve phase, the impact of influence factors is established. The team develops solutions that could eliminate the causes, and process changes or adjustments are implemented. When the solutions are found to be not sufficient, the team needs to find an alternate solution. This can be an iterative process for continuous learning. In the final control phase, the Black Belt needs to develop control systems to ensure the control of implemented improvements in the future. Out-of-control-action-plans (OCAPs) are made. Finally, the Black Belt is

discharged from the project by the Champion and the project is closed.

All aspects of LSS make this methodology useful to investigate the research question for the real-life case-study. Moreover, in the academic medical center of interest, LSS is an often-used methodology for improvement projects (Niemeijer et al. (2012)). Especially for healthcare projects using LSS, Niemeijer et al. (2011) described nine improvement themes related to patient safety, patient satisfaction, and business-economic performance of a hospital. In this case-study the template ‘decreasing cost by improving productivity of personnel’ was used.

C. Analyzing methods

In the evaluation of the work processes in the case-study, several statistical and analyzing methods are used. Firstly, control charts are graphed to evaluate patterns in all CTQs. As a method for process control, the control chart may help to discern real disturbances as assignable causes from noise fluctuations (De Mast et al. (2012)). The individuals chart is a type of control chart that displays the individual measurements with a lower control limit and an upper control limit both at a distance of 3σ from the data’s mean. Out of this bandwidth outliers with assignable causes can be recognized.

Further process statistics performed are capability analysis and Failure Mode and Effects Analysis (FMEA). Capability analysiss of the CTQ shows in a histogram the spread of the CTQ value compared to the spread of its requirement, when the process is in statistical control (De Mast et al. (2012)). In a process that is capable in producing output that meets

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11 the customer’s expectations, the spread of the CTQ is smaller than the spread of

requirements and the CTQ is centred in the histogram. The process capability analysis gives an estimate of the CTQ’s proportion that does not meet the requirements. The CTQs used in the study have an upper requirement norm imposed by the team members, the upper specification limits. The process capability analysis makes it is thus possible to compare the CTQ values to their requirements. FMEA can identify and prioritize disturbances (De Mast et al. (2012)). Cause and effect of each disturbance are determined in a team meeting. The Black Belt determines the prioritization by rating each disturbance with the formula: occurrence x severity x detectability. The occurrence is rated on a scale of 1-10, i.e. hardly ever to almost continuously, respectively. The severity is rated by its effect onto the CTQs in a similar scale. The detectability is rated on a scale 1-10, i.e. immediately detected to

detected only until a problem has already emerged, respectively. The analysis results in a risk priority number (RPN) that helps to prioritize the disturbance factors.

Analyzing methods used are autopsies, best-of-the-best (BOB) and worst-of-the-worst (WOW), Ishikawa-diagrams, Waterfall-charts and value stream maps. With autopsies The Black Belt tries to reconstruct what went wrong in the process and tries to gain insight in causes of the problem. With BOB vs. WOW the Black Belt compares several very good and bad examples of the output of the process (De Mast et al. (2012)). Together with the team members involved the Black Belt considers all the differences between the best and worst examples. Theses differences develop a pattern of the fundamental differences between BOBs and WOWs. Ishikawa-diagrams are a visualization of cause and effect relationships. The CTQ is the effect, and the team members try to find causal factors in the following six categories: employee, ICT, information, process method, customer and external factors. Waterfall-charts visualize the effect of influence factors. Whole columns represent the initial and final values, and floating columns denote the intermediate values. The floating columns show the cumulative effect of sequentially introduced countermeasures in improvement of the CTQ.

Finally, to visualize the process in the case-study, value stream maps are used. A value stream map is a flow-chart of the process in which the processing and waiting times, and rework are graphed (Tapping et al. (2002), Womack and Jones (2003), Kemper et al.

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12 (2010)). In the value stream map sequences of activities that deliver value are mapped.

Some activities create more value than others. For instance, direct patient-clinician interaction will deliver more value than administrative activities or activities in the

laboratories. Although all should be done efficiently, the activities with less value should not distract resources from the higher value activities. Since work processes enable the

sequences of activities, value stream maps make it easy to recognize forms of waste and inefficiencies in the processes. In the case-study, value stream maps will be made to give insight in the current and a more optimal process.

III. Case description

The University Medical Center Groningen (UMCG) in The Netherlands is a 1,339-bed, large academic medical center employing more than 10,000 people. The mission and its bipartite vision are described as (UMCG 2015): ‘Building on the future of health in patient care, scientific research, education and further studies, and outshine ánd innovate in all these core tasks, because it can always be better. […]’, respectively ‘From human to human, in everything we do’ and ‘Healthy Aging’. This mission and vision fit the goal of the project to improve, and ultimately never stop improving the organisation.

Facts and numbers of the UMCG in 2015 were (Universitair Medisch Centrum Groningen (2016)): 35,000 admissions, 840,549 outpatient clinic visits of which 183,873 were first visits and 35,366 to the emergency department. The UMCG is an academic center with special focus on transplantation. It is the only medical center in The Netherlands that performs all possible organ transplantations. In 2015 179 kidney transplantations, 59 liver transplantations, 35 lung transplantations, 6 heart transplantations, 6 pancreas

transplantations, 2 small intestine transplantations and 137 bone marrow transplantations were performed. The departments of the UMCG are grouped in divisions (Figure 1). Care paths flow through the several departments.

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13 Figure 1. Organization chart: care paths through divisions with synergies considering patients and resources.

The kidney transplantation program is the second largest in The Netherlands and still growing. The program sticks to similar vision and mission as the UMCG does. The region where hospitals mainly refer from to the UMCG is large and reaches a length of

approximately 175 km driving distance at most. Six nephrologists in the Department of Nephrology are dedicated to the kidney transplantation program. The clinical part of the transplant nephrologists’ work exists of assessing patients for suitability for kidney transplantation and assessing potential living kidney donors. Furthermore, in together 11 half-day outpatient clinics per week, they see the patients after their transplantation (from weeks to many years thereafter). The market segment that the transplant-nephrologists take care of are those patients in preparation of a kidney transplant or people in preparation of kidney donation, and those patients with a kidney transplant, all in the North-Eastern part of the Netherlands.

When seeing patients in the outpatient clinic, the nephrologists feel that they need the same amount of time that the half-day outpatient clinic took in order to handle the afterwork. This afterwork-processing consists of checking laboratory results, adjusting the

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14 treatment plan and discuss the results and alterations of the treatment plan on the phone with the patients. Since the region of the UMCG is large, patients cannot come one day in advance for the blood samples having drawn. Since the blood samples need to be sent to three laboratories and some laboratory measurements are laborious, the results are ready in two to six days after the outpatient clinic. However, since it is important to evaluate the kidney function the same day the blood was drawn, the nephrologists need to do rework with the laboratory checks. Furthermore, many times the patients do not respond to the phone calls the first time, which results in rework as well. Some nephrologists therefore choose not to make adjustments to the treatment plan in case of little optimizing

medication adjustments. Finally, more and more patients would like to know the status of their kidney transplant while seeing their nephrologist in the consulting-room.

The UMCG has had experience with LSS since 2007 (Niemeijer et al. (2012)). A Master Black Belt coordinates, supports and educates the Black, Green and Orange Belts in the UMCG. In 2015, in light of this thesis, a Lean Six Sigma project was performed as

examination project in the kidney transplantation outpatient clinic. The Master Black Belt supported the graduate. Goal of the project was to improve efficiency of work-flow for the transplant-nephrologists in performing their outpatient clinics. Measurements for this prospective study were performed In December 2015 and January 2016, and the project was closed in June 2016. The case and results are described through the DMAIC-phases.

A. Define

In the first phase, the project is identified and defined, and its objective, scope and anticipated benefits are stated. CTQs are described as well as the process involved that is step-wise being evaluated. Last step in this phase is to define the organization of the project and stakeholders.

The process to be improved is the daily handling of the kidney transplantation

outpatient clinic from the perspective of the transplant-nephrologists. This includes the staff work-time before, during and after the outpatient clinic in order to evaluate the patients

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15 who visited the clinic that day. This consists of the preparation and afterwork, i.e. checking results and making further arrangements with the patient. The project’s objective is to decrease the afterwork in terms of processing time and file processing number per

outpatient clinic performed. Therefore, the project’s scope is decreasing this processing time and file processing number, and thereby enhancing productivity and decreasing negative emotions of the professional.

Three CTQs are to be improved. Firstly, processing time is the processing time per task per outpatient clinic. Tasks are distributed among the nephrologist, clinical chemist, virologist and pharmacist. Secondly, the file processing number is the number of file handling episodes per outpatient clinic by the nephrologist. Thirdly, the undertreatment frequency is the frequency per outpatient clinic that the nephrologist chooses not to call the patient because of acceptable but not optimal laboratory results (mainly drug levels). That means that when the nephrologist would have had the results when the patient was still in the consulting room, the nephrologist would have discussed and indeed adapted the treatment plan with the patient.

Anticipated benefits when having improved these CTQs are distributed to the customer and the business. The customer may have less waiting time to treatment plan, higher sense of his own state of health/illness, and higher satisfaction. The business may have enhanced productivity of the nephrologists by lowering the number of rework. The business may have a reduction of costs, and a higher operating speed.

The process is described in a SIPOC (supplier – input – process – output – customer) model and shown in Figure 2. The patient with a kidney transplant visits the outpatient clinic

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16 and on the same morning blood is being drawn and urine is being collected on the

department of clinical chemistry. Blood is sent to the three departments of clinical

chemistry, virology and pharmacy. At the microbiology laboratory mainly three viruses are assessed: Cytomegalovirus (CMV), Epstein Barr virus (EBV) and BK virus. The latter most times takes longest (2 days). At the pharmacy laboratory mainly three drug trough levels are assessed: tacrolimus, mycophenolic acid and everolimus. The latter two most times take longest (2-6 days). Just after or just before the blood drawing, the patient visits his treating nephrologist. During the consult the laboratory results of that day are not ready yet since the time period between the blood drawing and entering the nephrologist’s consulting room is too short for the laboratories to perform all measurements and arrive to published results. The first results are ready the same afternoon, and later results are reported within two to six days. The nephrologist needs to check the most important results of renal function the same day and needs to check the other results during the next days. If necessary, the nephrologist calls the patient to make additional appointments or alterations to the

treatment plan. Some nephrologists told that they sometimes tolerate not making additional changes to the plan as agreed on during the visit, because of understanding problems for patients on the phone or difficulty to reach patients by phone.

The nephrologists reported that the afterwork of all additional laboratory checks and subsequent calls to the patient took them three to four times of file handling episodes during the days, and they perceived this inefficient and annoying. The first aim of the project was to improve their efficiency in performing their outpatient clinics and thereby to reduce costs of personnel. The project assumed a reduction of 3 hours per working week per nephrologist, resulting in a total value of 104,000 euros revenue per year. Therefore, an LSS-team with 10 members was composed: all 6 transplant-nephrologists including the Black Belt, the department chair (Champion), one clinical chemist, one virologist and one hospital-pharmacist. Tasks of the team were several. Every team member needed to collect their process data in sub-steps and provide these weekly to the Black Belt for validation in sample surveys. They needed to provide information about the sub-processes in the separate departments to the team members in the team meetings. Together they needed to

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17 brainstorm about influence factors and improvement factors. All stakeholders were pleased to work in the team and positive at stake.

B. Measure

In the second phase of DMAIC, the measure phase, the problem definition is made precise and measurable. A second step in this phase is to validate that sufficient reliable data can be collected.

To measure the objective of improving the efficiency of personnel, three CTQs are defined (Figure 3): processing time per task per outpatient clinic, file processing number and undertreatment frequency. Tasks consist of patient file handling for the nephrologists, and

Figure 3. CTQ-flowdown

of handling time of blood samples for the laboratories. These blood samples’ processing times are split in sub-steps: arrival of the blood sample on the laboratory, starting the analysis, having result of the analysis, authorization of the analysis, and publication in the electronic patient file. File processing number is the number of file handling episodes that the transplant-nephrologist needs to do to accomplish the afterwork of checking the laboratory results, adjusting the treatment plan and calling the patient. Namely, the same day of the outpatient clinic the kidney function has to be checked for major deteriorations,

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18 the next day results of the most important immune suppressive medication (tacrolimus) needs to be checked, and the day after or even more days thereafter other results of drug levels (everolimus, mycophenolic acid) and virology are ready and need to be checked, and if necessary, adjusted. For all CTQs the unit of study is ‘per outpatient clinic’ and the goal ‘as short as possible’.

Data were collected in three working weeks in 30 outpatient clinics. Data of the nephrologists were validated in a sample survey in which 75% of their data was checked by the Black Belt. CTQ ‘undertreatment’ had a total measure of one. This CTQ is therefore not being statistically analyzed but it is discussed in the team meetings. The laboratory

registration system registers exact timing of sub-steps in the process of blood sample handling. Within the department of clinical chemistry a subset of data was collected manually. These data were validated in a sample survey in which 15% of data was checked by the Black Belt. Autopsies and BOB vs. WOW were performed on the data and checked.

IV. Results

In the next three phases of the DMAIC the results of the project are retrieved. The results lead the aim of the project: to investigate the amount of waste in productivity of the professionals and whether improving work-flow could reduce this waste.

A. Analyze

In the third phase of the DMAIC, the diagnosis of the problem is being found by analyses of the data. The precise and measurable CTQs defined in the measure phase can show the magnitude of the problem and what causes might be. Therefore, firstly, the current process is precisely diagnosed in data, and secondly, influence factors are identified.

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19 task, file processing number and undertreatment frequency. The data were analyzed per specialist (nephrologist, clinical chemist, virologist, pharmacist). The baseline levels of the process are summarised in a value stream map (VSM) with points of waste (Figure 4). The mean time spent by the nephrologist on afterwork was 150 min (range 30-330 min). The

Figure 4. Value stream map of the baseline situation of the project.

time spent on afterwork was not depending on nephrologist, day of outpatient clinic or type of drug that needed to be evaluated in the pharmacy laboratory. Figure 4 shows that the afterwork for the nephrologist almost equals the processing time of the outpatient clinic itself. In other words, for one half-day of outpatient clinic a nephrologist needs similar time for the process handling of afterwork. Furthermore, Figure 4 shows that the processing times in the laboratories differ: mean times of 96, 590 and 1,820 minutes for the laboratories of clinical chemistry, pharmacy and virology respectively. All laboratories showed high variability in the measurements (ranges 42-342, 161-4,331 and 29-10,591 minutes respectively). In the laboratories of clinical chemistry and pharmacy this variability was not associated with day of outpatient clinic or type of measurement. In the laboratory of virology the highest outliers were the samples drawn on Fridays. Upper specification

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20 limits (USL) for the processing times were set in the team discussion. The USLs were

analyzed in process capability reports as follows:

• 60 minutes for clinical chemistry; 60% of blood samples did not reach this processing time;

• 280-1,440 minutes for pharmacy depending on the drug analyzed; 280 minutes was the USL for the main drug tacrolimus and >80% of blood samples did not reach this target;

• 1,440 minutes for virology blood samples and 50% of blood samples did not reach this target.

The file processing number of afterwork per outpatient clinic had a median of 3 (range 1-6). Undertreatment was only scored once. Table I summarizes the performance of the CTQs of the baseline situation, the desired situation and the intended benefits.

Table I. Summary of the performance of CTQs.

CTQ Current performance Desired performance Intended benefits

Processing time, no.

-nephrologist 150 min, 5x 10 min, 2x Less negative emotion 1,800 eu/week -clinical chemist 96 min 60 min Less negative emotion

Better-informed patient -pharmacist tacrolimus 580 min tacrolimus 240 min Less negative emotion

MMF 3,240 min MMF 1,440 min Improved quality of care -virologist 1,820 min 1,440 min Less negative emotion

Improved quality of care

Undertreatment freq. 1x 0 Improved quality of care

Legend: CTQ: critical-to-quality characteristic, eu: euro, freq.: frequency, no.: number, min: minutes. Second step in the analyze phase is trying to find influence factors that may improve the current situation. The Black Belt analyzes the CTQ’s behaviour and tries to find influence

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21 factors that cause the CTQ to fail to meet requirements. With this knowledge possible

countermeasures can be designed.

Team members had a brainstorm session after obtaining the results of the analyses. They used BOB vs. WOW, Ishikawa-diagrams and FMEA to find influence factors. For the two CTQs processing time and file processing number the following main influence factors were provided in the team meeting:

• Late reporting of laboratory results because of:

o Lack of collaboration of the hospital laboratories with regional laboratories where the patient can have blood drawn in advance,

o Layout of the UMCG: department for blood drawing far away from the laboratory itself,

o Out-dated laboratory equipment,

o Need for manual processing at laboratory of pharmacy,

o Long transport time to laboratory for blood samples that are sent to the department of clinical chemistry first and from there transported to the laboratories of virology and pharmacy,

o Time of the day and frequency of starting the laboratory processes in laboratories of pharmacy and virology.

In the FMEA the influence factors were prioritized to cause of failure. Late blood drawing had the highest RPN (RPN 800). Thereafter the following influence factors had high RPN scores: infrequent samplings in the laboratories (RPN 640), slow laboratory equipment (RPN 600), slow sample measurements (RPN 250) and busyness on the laboratory due to

crowding of patients (RPN 250).

For the CTQ undertreatment frequency the main influence factors as considered by the team were:

• Late reporting of the laboratory results (next day or later), • Patient not responding to phone calls.

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22 B. Improve

In the fourth DMAIC phase, the improve phase, the most important influence factors are determined. Firstly, the effect of these most important influence factors is established. Secondly, improvement actions are designed.

The influence factors that were discussed in the team session were examined. The effect of these influence factors was established in a second team meeting. Experts estimated the reduction that would be derived when those factors would be resolved. Waterfall-charts were created to show the effect of these reductions. Three main

improvements were assessed to reduce the CTQ processing time of afterwork from 150 to 10 minutes:

• Collaboration with regional laboratories: 50% (70 min) of the planned reduction, • More frequent laboratory assessments per day: 21% (30 min) of the planned

reduction,

• Renewing laboratory equipment: 14% (20 min) of the planned reduction. Preventing crowdedness of patients in the laboratory department of blood drawing and decreasing processing time of the manual measurements in the laboratories would further reduce the CTQ 10 minutes each. The first three improvements were assessed to reduce the file processing number from 5 to 2 times. The CTQ undertreatment frequency was not further evaluated because of the single positive measurement.

The designed improvement actions were listed in a process matrix to document identified potential influence factors and to plan subsequent studies. The clinical chemist is held responsible for instigating collaboration with the regional laboratories. The pharmacist and virologist are held responsible for upgrading the frequency of assessments in their laboratories. At the end of the project this upgrading was already being implemented in the pharmacy laboratory and even fully implemented in the virology laboratory. Renewal of the laboratory equipment was already being communicated throughout the hospital.

Agreements for deadlines were made with the specialists involved. Results of the blood measurements will be ready one day before or the day of the outpatient clinic by

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23 sampling at home by dry blood spot measurement (pharmacy). At least 75% of patients who come 75 minutes before time of their scheduled consult will have results ready by renewal of faster laboratory equipment.

C. Control

In the final control phase process control is improved and the project is closed. The improvement actions need to be embedded in the process and therefore a quality control system is structured and recorded. This phase also aims to facilitate on-going small

improvements in the process. Finally, the financial controller verifies the revenues of the project and then the Champion can discharge the Black Belt from the project.

The improvement actions as described in the improve phase were recorded. Three tools are used to prevent the process to drift from the new settings of the process and thereby from set requirements. Firstly, responsibilities as described in the former phase are recorded with reporting times per specialist. Secondly, the implementation plan and new designed process are recorded for the team members. Thirdly, an Out-of-Control Action Plan (OCAP) is formulated as an organizational and managerial process control tool. This OCAP specifies control items, control methods, responsibility, requirements and response plan in the two process-steps blood drawing and starting of sampling. The team members will report their proceedings every four months and evaluate number of delayed results and number of regional assessments. Norms for the laboratories of clinical chemistry, pharmacy and virology to report the results were set at 60, 280 and 1,440 minutes respectively. Norm for processing time of afterwork done by the nephrologist was set at 10 minutes and for file processing number at a maximum of 2. Staff and patients involved in the improvement actions are informed. The ultimate VSM that will be targeted is shown in Figure 5.

This leads to the benefit realization of a revenue of 94,500 euros produced by the improvement actions, as approved by the controller. This value does not implicate a reduction of staff, but will be used to do more kidney transplantations per year with equal full-time equivalents of the transplant-nephrologists. Since transplantation is a focus for the

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24 Figure 5. Value stream map of the goal-situation of the project.

UMCG, more efficient work is necessary to realize the increasing number of

transplantations. The soft benefits that will be realized are more joy in work and higher quality of work for the nephrologist, and for the patient less waiting time, better patient awareness about health status, higher quality of care and increase of satisfaction.

V. Summary, conclusions and recommendations

A. Summary

This study is a real-life case in a large academic hospital and shows that delineating work processes, and evaluating and eliminating their points of waste with an improvement project following the methodology of Lean Six Sigma, can easily improve work-flow and efficiency. The case-study was performed In the outpatient clinic of kidney transplantation of a large academic medical center in The Netherlands. The medical center was known with the methodology of Lean Six Sigma. The objective was to increase efficiency by decreasing processing time of afterwork for the transplant-nephrologists, and thereby retrieve a

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25 reduction of costs of personnel. The critical-to-quality-characteristics were defined as

processing time per task, file processing number and undertreatment frequency. The team was composed of all six transplant-nephrologists including the Black Belt, the department chair (Champion), a clinical chemist, a hospital-pharmacist and a virologist. Data of

processing times in sub-steps and file processing numbers were collected, validated and analyzed with control charts and capability analyses. Mapping these data in a value stream map clearly showed their points of waste as expressed by waiting times and rework.

Discussion with team members about cause and effect, best-of-best cases vs. worst-of-worst and failure-mode-and-effect-analysis developed a priority set of interventions that could improve the CTQs to the target levels. The scheduled interventions were increasing the frequency of sampling in the laboratories, exploring and implementing cooperation with regional laboratories, renewal of laboratory equipment and fastening manual

measurements.

Accomplishing these improvement interventions would result in a deliverable for the organization of almost 100,000 euros as approved by the controller. This would not be entered to reduce number of personnel, but to accomplish more kidney transplantations per year including preparations and follow-up of donors and recipients with a similar team size of transplant-nephrologists since transplantation is a main focus of the academic medical center involved. Besides the hard benefit in euros, soft benefits may emerge like increased healthcare quality, better patient awareness about health status and less negative emotions of the staff-employees in performing their daily practice. It was thus shown that a mismatch between supply and demand in terms of laboratory diagnostics and personnel can easily go unnoticed, and can be mapped and improved using a data-based methodology focussing on improving work-flow and reducing waste. The hypothesis that the results of the case-study would show easy contributions of improving patient value and probable reduction of healthcare costs was confirmed.

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26 B. Discussion

This case-study focuses on improving both aspects of the goal of the healthcare system namely high-quality healthcare and affordable price. The improvements proposed in the study fit in all dimensions that healthcare needs to be as stated by the Institute of Medicine. The output of the improvements makes the outcome healthcare quality more effective, more patient-centered, more efficient, and more equitable (Institute of Medicine (2015)). Furthermore, by higher effectiveness and efficiency, the improvements may also lead to safer, timelier and more affordable healthcare. This study supports findings by others that focus on patient value is lacking to at least some degree in the current healthcare system and that quality might be improved by increasing productivity of personnel (Christensen et al. (2009), Verlet and Devos (2010), Kaplan and Porter (2011), Niemeijer et al. (2011), Cullen et al. (2012), Niemeijer et al. (2012)).

As found in this study, productivity of personnel increases when processes are arranged with optimal flow. After implementation of the proposed improvements, the optimal flow will ultimately also result in better information to the patient since all

information to the patient can be given in the face-to-face contact. The patient can be better informed about his current health status and thereby the patient can better improve his health. The outpatient clinic becomes better patient-centered and delivers more value to the patient (Porter and Teisberg (2004), Kaplan and Porter (2011)). Since the outpatient clinic is one of the main daily outputs of hospitals, process improvement in this area of patient care may lead to a large benefit in terms of optimizing patient care and patient value, but also in reducing waste, and increasing efficiency and work-flow for the professionals. Through all healthcare spending may decrease.

When considering process improvement projects, improving flow is one of the main concepts (Cullen et al. (2012), Hogan et al. (2012), Slack et al. (2015), White et al. (2015), Black et al. (2016)). Important theorist in the concept of flow is psychologist Mihaly

Csikszentmihalyi. In his definition, flow is the state of consciousness that makes a person to fully engage to his activities with making that experience truly satisfying and accomplishing successfully (Csikszentmihalyi (1990)). Flow is then characterized by some of the following

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27 amongst others: having a clear goal, focused concentration on the present moment, sense of personal control over the activity and immediate feedback (Csikszentmihalyi (1990)). These characteristics embrace those components that we strive for in every day healthcare practices for adding value to our patient care: enabling choice, being better informed as physician/professional, giving better information to the patient in the present moment, reducing errors and waste by feedback, and by all improve quality (Porter and Teisberg (2004)). Besides flow of monetary, flow in healthcare can be recognized as work-flow in processes, flow of care paths through divisions in corporate strategy (Figure 1) and flow of information (Slack et al. (2015)). In all, continuous flow better corresponds to the

characteristics of the demand curve (Rouse and Serban (2014), Slack et al. (2015)). Question remains how process improvement can contribute to better quality and reduction of costs not only in the medical center studied, but also in other centers and the healthcare system. The Ministry of Health focuses amongst others on effective and efficient care, but it is argued that we do not deliver that yet (Christensen et al. (2009), Pomp (2010), Verlet and Devos (2010), Kaplan and Porter (2011), Cullen et al. (2012)). The challenge is to increase the organization of the healthcare delivery system and thereby quality and

efficiency, and deliver economic success of the healthcare system. Therefore, we need to evaluate opportunities in business control, process-working, performance measurement, and continuous learning and improvement, with the concept of flow in mind.

B.1 Business control in the healthcare system

Opportunities for improving the delivery system of healthcare organizations can be found when firstly acknowledging the elements of the business control system and management functions. Starting points for the healthcare organization should be to describe the goals for the market segment and to analyze the business’ opportunities and threats.

Companies in industry begin their business control by developing a strategy

statement including mission, vision, value proposition and threats. These are translated into an organization-task structure based on a cause-effect business model, and translated into

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28 measurable objectives in the operational plan (Kaplan and Norton (2008)). During execution of the operational plan, internal results and external data on the business environment including competitors are systematically monitored. Redirecting actions are taken when necessary. The strategy is periodically evaluated and adapted, thereby starting the loop again. So when the vision, mission and ambitions are clearly set, the management has clear which information is needed and where to coordinate in the work-flow. The amount of processes can be planned and coordinated. Namely, an organization with high-quality information and high-integrative thinking is able to handle more processes.

The functions of management in a business control process are seven: the

constitutional task, forward looking, organizing, enabling people, coordination, monitoring and learning, and accountability (Fayol (1917), Strikwerda (2014)). When the vision, mission and corporate governance are defined in the first task, the management needs to foresee possible chances and developments and translate these into strategy in the second task. With pro-active control and commitment the future can be shaped. The third task is

organization including defining amounts of self-organization and internal accountability. By enabling people in the fourth task, complexity leadership leads to facilitating and supporting the employees. Fifthly, coordination includes allocation efficiency. Resources need to be distributed most efficiently to processes. Sixthly, monitoring and learning sets performance management, and creates knowledge by learning and development. Finally, trust by the community is gained by external accountability. In all, information for performance measurements, feedback and compensation are key.

Firstly, as thus can be learned from industry, one of the starting points for an organization is to describe the goals for the market segment that the business serves. For the healthcare system that is to recognize that value for the patients is to be healthy or healthier, and not to consume healthcare services. Nowadays however, as in the case-study, provision of the healthcare is centered around the convenience of healthcare providers instead of the patients, and even that is not optimally organized. Developing technologies and incentives could improve the value for patients (Kaplan and Norton (2004), Kaplan and Porter (2011), Volpp (2016)). In this case-study, LSS was used to create insight for the employees and team members in the current process performance and thus creates

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29 incentives to improve. Indeed, the methodology is meant to implement, execute, and

leverage the strategy that the business has designed (De Mast et al. (2012)). In the business control plan LSS can be used in the tasks of forward looking, organization, coordination, and monitoring and learning.

Secondly, another starting point is to evaluate opportunities and threats that the business might encounter. Internal and environmental analyses are integrated in the traditional strengths – weaknesses – opportunities – threats (SWOT)-framework (Barney (1995)). Internal attributes are resources and capabilities. It is argued that to make best use of the most important resource in society, namely human capital, organizations need to change from systems that control people, to systems that facilitate and support people (Ghoshal and Bartlett (1999)). Structure might remain, as in the case-study by the medical center’s hierarchy and structure with divisions, but this structure must become the

infrastructure for achieving the organization’s purpose that is achieved by processes. The processes in care paths eventually result in the aims of healthcare as expressed by the IOM (Institute of Medicine (2015)). In the case-study, the human capital was not optimally facilitated and supported to perform most efficiently. It was shown to improve with the methodology of LSS.

Furthermore, other threats for the healthcare system might come from the

environment that continually demands higher quality and effectiveness of services while it is continuously changing (Dekker (2014), Institute of Medicine (2015)). Some of these threats can be recognized for example in increase in chronic conditions, growing complexity of science and technology, and the revolution in information technology (Institute of Medicine (2015)). The enabling new technologies should support both clinicians’ work-flow and thought-flow but that seems not to be optimally achieved (Ball and Bierstock (2007)). Countermeasures for the threat of the changing environment can be found in better implementation of these enabling technologies, but also in the complexity and adaptability of the healthcare system itself. Complexity in business processes must yield less varied outcomes and the professionals working in this system must recognize, adapt to and align with the changing environment (Rouse and Serban (2014)). Human capital thus needs to be organized in the business control plan complementary to the organization and information

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30 capital to achieve these adaptations and align with the changing environment. Nonetheless, because the system is continuously adapting, it keeps redesigning itself (Rouse and Serban (2014)). Managers thus need to systematically innovate the strategy by finding the balance in exploitation and exploration (March (1991)). Indeed, LSS is a methodology that can be used for continuous improvement when incorporated in the strategy.

As this case-study found, business control has not been organized optimally as long as the systems and structures increase clinicians’ work while these provide them little if any benefit. Quality will then not increase and costs will not reduce. The business control plan should incorporate improvement methodologies to keep improving. These methodologies are important in at least four managerial functions, namely forward looking, organization, coordination, and monitoring and learning. Keys to integrate improvement loops are process-thinking, performance measurement and standardized data with application of information technologies. All together they may reduce variability and waste (Ball and Bierstock (2007), Rouse and Serban (2014), Black et al. (2016)).

B.2 Process-working

A famous quote of a world authority on quality control W. Edwards Deming once was: ‘If you can’t describe what you are doing as a process, you don’t know what you are doing’. Since it are processes that connect elements like strategy and objectives from the business control plan with each other and with the structure of the organization, processes indeed need to have key focus in the organization (Ghoshal and Bartlett (1999), Kaplan and Norton (2008), Christensen et al. (2009), Cullen et al. (2012), Black et al. (2016)). In industry quality can easily be found in the product, but in healthcare that is somewhat more cumbersome since that is about the (better) health status of the patients that is sometimes hard to measure. Since most of this product is realized by process-working, quality needs to be partly expressed in the service (Komashie et al. (2007)). However, process elements in hospitals have many features in common with other service and academic organizations that contribute to easier development of failures and even barriers to learning from them

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31 (Tucker and Edmondson (2003)). Examples are time pressure, unpredictability in workload, and the reliance of the employees on others for supplies, information and ability to achieve their jobs (Tucker and Edmondson (2003), Catano et al. (2010), Ylijoki (2013)). Learning from failures is further impeded since the tasks carried out by the professionals are knowledge-intensive, highly variable, and performed in the physical presence of customers (Tucker and Edmondson (2003)). Therefore, efficiency and effectiveness in process-thinking are key, since these withhold from distraction to improve.

Efficiency can be improved and controlled in different types of processes, for example operational, supportive and administrative processes. In this case-study, an operational process was subject since operational processes are the processes that lead to the patient-clinician contact. Supportive and administrative processes, and the resource allocation process and scheduling need to support and facilitate the operational processes, since these are critical for the strategy execution and improving the delivery system of healthcare (Kaplan and Norton 2008). Managerial function is to prioritize improvement projects by assessing long-term value and to integrate improvement loops in all processes. Herein, as well as in assessing future demand, performance measurement and standardized data are key.

B.3 Performance measurement

Performance measures are essential since they are the link from strategy to output, lead to analyzable data of the process and resources, lead to information that creates knowledge about waste and possibilities for improvement, and they fulfill the business control plan with feedback.

To link the strategy with its objectives into process operations, measurable performance indicators have to be set in the business control loop (Kaplan and Norton (2008), Slack et al. (2015)). Measuring the performance of the processes is needed to evaluate whether target goals have been reached (Juran and Godfrey (1998)). This requires defining process state variables, their units of measure and how such measurements can be

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32 made. By defining performance measures and their targets, waste can also defined.

Everything that causes the performance measures to be out of the acceptable limits and thus out of control can be defined as waste (De Mast et al. (2012), Slack et al. (2015)).

The performance measures bring up the data needed to analyze the processes, performance and resources. With statistic control methods process characteristics like variability and noise, process capability and drift can be measured and analyzed to

investigate patterns and capacity to reach targets (De Mast et al. (2012), Slack et al. (2015)). These tools can furthermore help finding causes of variability, and thereby help eliminating variability and improve the zone of control. In this case-study, variability was also found when the control variables processing time per task en file processing number were analyzed. The data have a role in advancing efficient and effective processes since they expose waste that can be eliminated in order to create better process-flow without handoffs (Slack et al. (2015), Black et al. (2016)). Furthermore, data also have a role in the business control process by informing the organization about overall progress and costs, but also about allocation and contributions of resources including human capital (Bower (1966)). When considering human capital, the employees thereby could be more easily facilitated and supported in their processes in order to eliminate waste that they encounter.

Information is thus a critical aspect in performance measurement of the business control process. The manager should persistently ask for the information needed set as the performance measures. That information is required to understand what works and does not work and to control and improve effective operations. When information has been collected, processed and disseminated, it improves anticipation and control. Freely disseminated information promotes information symmetry between patients, providers, healthcare organizations, and the healthcare system. It promotes all quality dimensions: safe, effective, patient-centered, timely, efficient, and equitable (Institute of Medicine (2015)). Indeed, the case-study showed that lack of information because of lack of

performance measures created waste in personnel efficiency but also in lack of the incentive to improve. Furthermore, in the care paths, integrating resources and activities and aligning positions can only be achieved by free flow of information between the divisions or business units (Prahalad and Hamel (1990)).

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33 Finally, performance measures are necessary for feedback and compensation in the business control loop (Juran and Godfrey (1998)). With feedback the actual process is compared to the targets in order to correct waste or errors when they occur. Compensation counteracts this waste with a process response when it occurs. In the case-study the

feedback-compensation loop was established by agreeing to the out-of-control-action-plans. Systematical control of the process is reached by evaluating whether the process smoothly flows into targets set and if not, how to bring the process back in track. Data and

performance measures are thus important because they can be translated with feedback and compensation into knowledge, decision-making, and improvements (Rouse and Serban (2014)). They help organize the delivery system of healthcare, but all this effectuated in the continuous improvement loop.

B.4 Continuous learning and improvement

Performance measurement, feedback and control may hold processes in acceptable limits and in control. However, still healthcare quality and costs are at stake. The healthcare system up until now seems either not to optimally set adequate performance measures and act to them, or just not to learn from daily problems and errors encountered by their

employees (Tucker and Edmondson (2003), Institute of Medicine (2015)). It can be discussed whether healthcare business management has an inferior esteem of importance for business control in comparison to care, education and research (Kaplan and Porter (2011)). However, better management of business control can lead to better outcome in the latter three. This is illustrated by the case-study. The transplant-nephrologists years long spent too much time on their outpatient clinic in comparison what was set by the performance measures.

Variability in the laboratory processes was high. The nephrologists had high quantity of waste in their daily practice that lead to high waste of resources including the human capital. The case-study however also shows that a data-based methodology providing performance measures, information and team motivation can eliminate the waste. Incorporating process improvement in the business control loop might contribute to better quality and less costs

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34 by promoting internal processes and prevention from drift. Goal is a continuously learning organization that continuously adapts to the changing environment.

The case-study is an example of an organizational learning process in which the efficiency of the resource human capital was increased. The case-study used the methodology of LSS as a proven healthcare methodology to increase efficiency and effectiveness (Parks et al. (2008), DelliFraine et al. (2010), Niemeijer et al. (2011),

Schoonhoven et al. (2011), De Mast et al. (2012)). Healthcare organizations may use LSS to improve quality and efficiency in internal processes, but they need to coordinate and monitor its organizational learning process also (Dekker (2014)). Improvement of internal process performance creates higher value for the customer, while learning and growth set as strategy objective may prevent from drift by describing the interaction of people,

organization and technology (Kaplan and Norton (2004), Dekker (2014)).

This learning and growth must prevent hospitals from drift. Hospitals may always experience variable input because of acute patients who force time-pressure and

unpredictability of workload and that may be a threat for eventual drift. Drift from

acceptable control limits can be as much as possible prevented with control tools. Therefore, a quality improvement system needs to be a systematic cycle in the organization and its business control loop (Juran and Godrey (1998), Tucker and Edmondson (2003), Dekker (2014)). Methodologies that translate data into knowledge and decisions, like LSS, are the means of engineering and transforming the healthcare system to higher quality and more affordable price (Rouse and Serban (2014)). Governance of healthcare organizations should focus on continuous improvement with focus on healthcare processes and innovation in order to deliver optimal value to the patient.

A helpful tool to achieve continuous learning in the organization might be LSS for greater improvements and kaizen for continuous small improvements. Kaizen is one of the concepts in Lean manufacturing and means good change in Japanese (Slack et al. (2015), Black et al. (2016)). Employees of all layers of the organization perform improvement projects. Kaizen is a method to keep the organization an ever-learning organization. Leadership together with implementation of an improvement production system like LSS and kaizen can best be moved on to the front line employees, as in this case-study (Slack et

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35 al. (2015), Black et al. (2016)). All forms of waste need to be recognized and pulled to an improvement by all layers of employees. Individual comparative physician data are helpful in feedback on quality and cost and these may be the physicians’ incentive to improve care (Shortell (2016)). Indeed, physicians and healthcare providers are already a little underway to make and test changes by building interdisciplinary teams, increasing cost transparency, and leveraging technology (Compton-Phillips (2016)). Employees need to internalize this way of working. For business control and managerial tasks, human resource departments may support these improvements by training and development, and hiring and selection of employees. Lifelong learning is an essential skill to adapt to change and the ever-changing environment, and then after all industry may also learn from healthcare (Wiersinga and Levi (2016)).

C. Conclusions

This study shows in a real-life case of a large academic hospital that delineating work

processes, and evaluating and eliminating their points of waste with a process improvement project following the methodology of Lean Six Sigma, can easily improve work-flow and efficiency. In this case-study, the deliverable for the organization was calculated and approved at almost 100,000 euros. It was shown that a mismatch between supply and demand in terms of process-flow of laboratory diagnostics and personnel can easily go unnoticed, and can be mapped and improved using a data-based methodology and

interdisciplinary team working. Besides the hard monetary benefit, benefits for the patients are better and faster information that may lead to improved healthcare quality. Benefits for the employees are decreased processing time and file processing number of afterwork which result in less negative emotion. The hypothesis was confirmed that the results would show easy contributions of improving patient value and reducing healthcare costs.

Thinking in terms of work processes instead of structure (hierarchies, departments) forces to better allocate resources across activities. Data and performance measurement provide information to all employees and the management about optimal flow in many

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36 resources. This leads to incentives to improve process-flow and better business control.

When the healthcare system can innovate to an integrated data-based process

improvement production system, the healthcare delivery system will be better organized. Quality will increase for probably a more affordable price. The integration of a continuous improvement system in the business control loop leads to a lifelong learning organisation and ability to align with the changing environment.

D. Recommendations

An accumulating number of articles and books is written urging for a transformation or redesign of healthcare in order to improve quality and mitigate the still increasing healthcare spendings. The findings of this case-study give practical recommendations how to set up to these goals. The findings plead for use of a data-based methodology like LSS to map, analyze and improve processes in healthcare. Such improvement projects are the continuous

incremental improvements that are performed by the front line employees of the

organization. Collecting and communication of data and their use as performance measures in processes must lead to better integration of information throughout the corporate business, and thereby to the incentives to improve. It is advisable to use performance measures, also since they close the loop of continuous improvement and lifelong learning. Management of healthcare organizations should incorporate this continuous improvement loop in the strategies and quality systems of their business control plan. That may facilitate the interaction between patients and medical professionals, and may increase quality in terms of patient value and employee satisfaction, affordable price and adaptive capacity to the ever-changing environment. The pursuit of quality and safety is not for the timid after all.

Improving healthcare : focus on flow in processes