VIEWS, VISIONS AND VISTAS IN DIALYSIS
Improving the Quality and Efficiency of Conventional Incenter Hemodialysis Jay Hingwala,*† Navdeep Tangri,*‡ Claudio Rigatto,*‡ and Paul Komenda*‡ *Section of Nephrology, Department of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada, †Health Sciences Centre, Winnipeg, Manitoba, Canada, and ‡Seven Oaks General Hospital, Winnipeg, Manitoba, Canada
ABSTRACT There is substantial variability at international, national, and regional levels in how effective dialysis providers are in the implementation of well-accepted interventions to deliver better health outcomes at reduced costs to payers. The growing number of dialysis patients within a finite pool of resources has led to searches for more efficient methods to provide patient care without compromising or diminishing quality. We review here some contemporary
concepts surrounding quality improvement and operations research that may provide clinician administrators to both improve efficiency and quality in facility based hemodialysis units. The creation of balanced scorecards, utilization of process mapping techniques, and the application of LEAN principles may readily improve how hemodialysis care is delivered in an environment of increasing patient volumes and reduced operating resources.
Background and Current Hemodialysis Experience
disparities are common in how providers strive for continuous quality improvement, set quality indicators and targets, data monitoring and feedback are undertaken, and finally how these targets are used in the process of reimbursement and remuneration. The growing number of dialysis patients within a finite pool of resources (2–4) has led to searches for more efficient methods to provide patient care without compromising or diminishing quality. This challenge is now highlighted and expedited by the recent reimbursement changes made by many insurers and governments for health care providers, often bundling remuneration or linking payment to certain quality indicators (e.g., Pay for Performance). Fortunately, dialysis programs are uniquely positioned in that they often have complete control over internal processes and resource allocation, creating an opportunity to take on this task. This paper will explore considerations that are essential for more efficient resource allocation within dialysis programs in the context of a balanced approach to maintaining a high degree of quality in the care delivered.
Patients with kidney failure requiring life-sustaining dialysis suffer from high morbidity and mortality, while consuming a disproportionate amount of health care resources. Evidence-informed interventions that may improve health outcomes while reducing costs for this patient group include delaying the need for dialysis, increasing transplantation rates, the use of home dialysis modalities, encouraging arteriovenous fistula use, and more frequent, long hemodialysis regimens. Despite these measures, however, the majority of kidney failure patients worldwide receive thrice-weekly facility- or clinic-based hemodialysis. There is substantial variability at international, national, and regional levels in how effective dialysis providers are in the implementation of well-accepted interventions to deliver better health outcomes at reduced costs to payers (1). Numerous reasons have been cited in explaining this variability including nephrologist preference, incentives/reimbursement structure, and availability of expertise. Furthermore,
Stakeholders and Priority Setting
Address correspondence to: Dr. Paul Komenda, Seven Oaks General Hospital Renal Program, 2300 Mcphillips Street, 2PD12, Winnipeg, MB, Canada R2V 3M3, or e-mail: [email protected]. Disclosures: The authors have no competing interests or potential conflicts of interest. Seminars in Dialysis—Vol 28, No 2 (March–April) 2015 pp. 169–175 DOI: 10.1111/sdi.12347 © 2015 Wiley Periodicals, Inc.
Although stakeholders are positioned from different perspectives on issues such as costs, priorities, perceived benefits, and impacts, multiple levels of stakeholders are interdependent and share a common goal to deliver quality care to patients. When changes to hemodialysis unit operating procedures are being designed, they should be considered in the 169
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context of a system and not as individual parts. Figure 1 depicts some steps in optimizing hemodialysis unit efficiency. All relevant stakeholders including front-line and support staff should be included, and change should involve patients, as the impact from their perspective adds value in a patientcentered, health care system (5–7). Further, quality should be defined in terms of health outcomes, satisfaction, and reduced cost (value), and take the patient’s perspective in addition to that of providers and payers (8). The current state must be documented and during the planning stages, stating the ultimate aim of the system, clearly defining the product being made, and considering who the beneficiaries or casualties of the change idea will be will increase the chance of a successful change. Finally, the desired future state can be created using a variety of tools such as LEAN, process engineering, and the concepts of optimal multidisciplinary care. Figure 2 displays an example of the diversity of stakeholders involved in patient care. In general, these are divided into three levels—macrosystem, mesosystem, and microsystem (6). Engagement and support from all levels, especially at the macrosystem level, is crucial to success. The macrosystem level works to incorporate cultural attitudes and goals into the organizational strategy. In general, policy makers from the government level and hospital boards are tasked with setting organizational
objectives, creating a platform of strategic aims, and creating a “blueprint” for allocating resources to achieve these aims. Other key players at this level include insurance providers and private businesses. The midlevel mesosystem supports and interfaces the board and the front lines. Examples of groups at this level are human resources, information technology systems, medical records, clinical departments, and continuous quality improvement committees. At the microsystem level, front-line workers are in direct contact with patients to deliver care. Stakeholders at this level can include nurses, patients, providers, health care aids, emergency medical services, cleaning staff, and technicians. Balanced Score Cards: The Triple Aim Don Berwick from the Institute for Health Improvement describes that improved health care systems are often best achieved through the balance of three interdependent elements—improving health outcomes, patient experience, and reducing costs (9). Together these are commonly described as the triple aim. Within a finite resource pool, improvement in one element often occurs at the expense of another aim, as resources are shifted from one portion of the triple aim to another. As such, effective measurement systems need to be established to
Design Future State • • •
LEAN processes (eliminate waste) Match tasks with appropriate team member Optimize scheduling to match demand with workload
Quality Management Plan Triple Aim Balanced Scorecard • • •
Health Outcomes Patient Experience Reduced Costs
Capture Current State • Process Mapping • Time in Motion Studies • Identify all inputs and desired outputs Fig. 1. Steps to improve hemodialysis unit efficiency.
Identify Key Stakeholders • Clinical Staff • Support Staff • Managers • Payers • Patients
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Fig. 2. Example of system-level organization of stakeholders.
monitor for continuous and sustained quality improvement, and ensure that unintended consequences are not occurring. Data collection for this purpose can be an imperative part of feedback in any continuous quality improvement process. When monitoring a system for improvement, it is important to include measures from all three triple aim elements. Balanced score cards (BSC) are valuable display tools to serve this purpose. The measures on a BSC work together to reflect the triple aim and mirror the strategic plan of on organization by allowing consolidation of multiple improvement projects into a single integrated platform (10,11) (e.g., Fig. 3). Front-line activities and measures may be transparently linked to business and governing priorities on the BSC (10). The BSC serve an additional purpose of visually displaying report cards of targets. The importance of this is highlighted in the United States, where quality targets are sometimes linked to physician reimbursement. Some of the targets in dialysis relate to anemia management, hemodialysis adequacy, optimal vascular access, patient satisfaction, mineral metabolism management, and dialysis safety events (12,13). Fresenius Medical Care (FMC) serves as an excellent example of an organization that has effectively implemented indicators for performance monitoring (13). FMC uses indicators that capture patient outcomes (satisfaction, compliance, and prolonged life expectancy), employee perspectives (personnel turnover, absenteeism, overtime, training hours, and employee satisfaction surveys), shareholder perspectives (treatment and patient growth, scheduling efficiency, personal, and other costs), and social responsibilities (energy savings and preservation of the environment) (10,11,14). Targets are based on health care, financial, and managerial guidelines. Raw data are consolidated to make a score for a
key performance indicator. When indicators show below target performance, they are targeted for improvement initiatives. When key performance indicators are exceeded, centers may receive incentives and be studied by other organizations. Principles of Operations Management Operations management consists of managing the oversight, design, and delivery of goods and services (15). More specifically, it aims to maximize efficiency, minimize resource use, while meeting customer requirements and satisfaction. In health care, this means providing accessible high-quality care for patients that improves their health outcomes while minimizing costs. The difficult task is often determining which underlying cause (i.e., root cause) to change first, as in most cases, multiple sources are contributing to suboptimal management. Costs savings derive commonly from improving efficiency, which subsequently reduces the demands on a system. When successful, the conserved resources can be reinvested in other areas of the triple aim that drive better patient outcomes and satisfaction. Efficiency is achieved through three general methods of decreasing wastes, decreasing variability in processes, and increasing flexibility in system capacity (6,15). A common tool used to eliminate overall process wastes is process mapping and value stream mapping, which defines value from the customer perspective, and then eliminates nonvalue-adding activities in the process (16). Any other activities not directly adding value can be essentially eliminated. A second method to reduce wastes is to lower resource wastes, which includes how health care workers spend their time. Common areas that lead to resource wastes are inventory
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Fig. 3. Example of a balanced scorecard for a hemodialysis unit. Green, meets or exceeds target; yellow, does not meet target but on track; red, requires continued focus.
mismanagement, not matching staff availability to patient demands, and patient waiting. Resource waste also takes place when tasks and duties do not parallel staff potential. Time and energy of staff is also wasted with unnecessary transport or motion and can potentially lead to adverse events. Some tools used to improve this are time in motion studies, work sampling, and the 5S’s (Sort, Stabilize, Shine, Standardize, and Sustain) which helps to physically organize a workplace to be more efficient (6). Optimal Use of Hemodialysis Equipment As dialysis technology has evolved, the hemodialysis machine does many jobs that previously were done manually. While on dialysis, vital signs and data reported by the machine are recorded and used as the main means to monitor patient safety. More frequent measurements, such as minute to minute or second to second are not feasibly attainable if they are collected manually. These data could provide valuable information to help predict which patients will develop hypotension during or after dialysis. In many dialysis centers, dialysis machines currently display blood pressures for nurses to manually enter onto run sheets. A more effective technique is to feed this information electronically into a central database that analyzes the patient’s blood pressure in real time, and then alerts the caregiver when the vital signs cross outside a control limit or have a worrisome trend. Then, at the end of a dialysis treatment, the patient’s vital signs, ultrafiltration records with corresponding hematocrit levels, blood and
dialysis flow rates, and access pressures can be transferred into an electrical medical record. This method can potentially provide better patient safety and save nursing time on manual entry of this information, which can then be reallocated to other activities such as educating patients and direct patient care. The Problem of Variable Workload Variability within a dialysis unit is best exemplified in dialysis scheduling. Patients’ demands fluctuate throughout dialysis treatments, the numbers of patients on dialysis in a shift vary as to the duration of their treatment times, and staff availability can change. Increasing flexibility within a system is vital to improving capacity and efficiency. As such, some centers have implemented a float nurse system (6,16,17), while others have created flexibility in staff available as backup to address some of these issues. As the rate-limiting step in flow through a hemodialysis unit is actual time on dialysis, maximal resources must be applied to the efficient initiation and termination of sessions. With this in mind, some centers have trained resource nurses such, to supervise and troubleshoot dialysis in between initiation and termination of a session with the goal of optimizing patient flow. LEAN Processes Improving efficiency, while preserving customer satisfaction, is a common goal in both business
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enterprises and health care settings. The LEAN model was initially developed by Toyota Production Systems, and was later adapted for use by the health care system (6). LEAN initiatives begin with a diverse group of stakeholders collectively documenting all detailed steps of a process. Wastes are then identified as any resources that are used without directly providing an action. The stakeholder group then simplifies the workflow process, being diligent not to remove critical steps that can create errors. The new streamlined process (i.e., value stream mapping) is then tested for workflow and is revised on an ongoing basis. From a dialysis patient’s perspective, a defect includes any part of the process that takes longer than an ideal time. This creates a bottleneck, fails to meet patient needs, causes the patient to wait, and can lessen the patient experience. Figure 4 shows the swim lane process map done by our hemodialysis unit. Once a process workflow is illustrated, a takt time can be established, which is the ideal time needed to complete a task. If supply is targeted to meet demands, then takt time is designed to match the demand rate. For example, if you have 30 dialysis treatments over one day (i.e., the demand), and your dialysis unit is open for 15 hours (900 minutes), then the takt time would be 900 minutes/30 treatments, which is 30 minutes per treatment to meet demands. As dialysis treatment needs 300-minute cycles for put-ons, dialysis treatments, takeoffs, and turnovers, the dialysis unit will need 10 dialysis
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stations to match their demands over one day. If cycle times remain constant, then this scenario would have no delays as takt time is met. This scenario however is not realistic as other factors beyond the total time the dialysis unit is open contribute to delays, such as staffing, patient arrival, or dialysis station availability. These bottlenecks invariably equate to patient wait times. When patients are forced to wait for their dialysis station to be ready, either their treatment times are reduced to meet stringent transportation times, or their treatments are continued past their scheduled times, leading to compounded delays on later shifts. This can translate into worse patient outcomes and experience. An Exercise in Optimal Hemodialysis Unit Scheduling One dialysis unit recognized that hectic scheduling was creating confusion among patients and staff, contributing to patient and staff dissatisfaction, and serving as a nidus for wait times. They reorganized their scheduling to have dependable start and end dialysis times, have more patient–staff contact, balance staff capacity to patient demands (especially during put-ons and takeoffs), match nurse duties to nurse-appropriate activities, have predictable shift times, and improve costs and productively. By first visually displaying current patient
Fig. 4. Seven Oaks Hospital hemodialysis unit—hemodialysis process swim lane diagram.
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scheduling, they discovered that when patients’ dialysis treatments start at similar times, multiple patients had overlapping put-ons and takeoffs, creating a busy and stressful period for patients and staff. From the display, they were also able to elicit where delays and waiting occurred for the next patient starting dialysis treatments in the same station. Next, they created a bar graph showing how many patients per hour are being put on and taken off dialysis treatments, with a superimposed graph displaying staff availability to work during those same times. Several issues were now apparent, such as the busy periods overwhelming staff capacity, and periods of staff underutilization was occurring when patient demand was less. Their improvement initiative involved evenly distributing shorter and longer dialysis treatment durations across all pods in the first two shifts, staggering start times for patients by 20 minutes, and placing the shortest treatment durations in the earliest start times. Together these steps limited simultaneous patient turnovers. They then started the second shift and third times after a turnover period. The third shift patients with the longest treatment durations were started first to shorten the day as much as possible. Once this schedule was established, distribution of staff times and staff shift times were established based on work demands, and staff break times were arranged to match periods of less demand. This model is successful in preventing groups of patients from arriving together in clusters that overwhelm the available capacity and takt time, which is an impetus for wait times. By staggering treatment start times to match standard work times, the demand variability in patients decreases, resources are not overwhelmed, less wait times accumulate (15), and patient experience and staff satisfaction improve (16,17). Achieving Effective Multidisciplinary Care Dialysis patient care occurs in a multidisciplinary model, which can result in workflow difficulties and duplication of work. The model of defining roles and dividing duties has been very successful
Fig. 5. Example of 5-station dialysis unit using staggered start times.
in multidisciplinary Renal Health Clinics (18), and has been highly effective to reduce practitioner cycle times and improve patient throughput, while maintaining quality of care. This success could be translated into dialysis units and help eliminate resource wastes (18). Our dialysis center performed a workflow study to understand the current state. Working with a large stakeholder group, standard operating procedures on specific staff responsibilities and duties were created to provide clarity of staff roles and standardize processes in workflow. In the future, these data could help us organize cycles for our dialysis unit. For example, when patients arrive to a dialysis unit waiting room, they all tend to wait for their dialysis station to be prepared. They then are weighed, vital signs are taken, the vascular access is accessed, and then dialysis begins. As these steps are virtually the same in all patients, this portion of the treatment can be divided into cycles that decrease variability in the setup process between patients. The unique patient needs relating to the treatment, medications, dialysis prescriptions, and special treatments, could be customized at the bedside along with addressing key patient-directed issues. Figure 5 depicts how a 5-station dialysis unit could be scheduled as staggered starts similar to the above example. If dialysis treatments were to be divided into 10-minute cycles during put-ons and takeoffs, it might make staff duties more clear, improve flow and usage of standard operating procedures, and improve patient satisfaction. During put-ons, a cycle of 10 minutes could include weighing a patient, bringing them to their station, and collecting their initial vital signs. The next 10-minute cycle could then involve connecting to vascular access. After dialysis treatment, creating of a cycle lasting 10 minutes to disconnect access, and then 10 minutes to weigh the patient and help them back to the waiting room for their transport home could be made. Cleaning a machine and turnover of a dialysis station could take 20 minutes. Before implementing a new system such as this, patient input is extremely important in this process, as patient experience could diminish if care resembled machine assembly lines.
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In the multidisciplinary dialysis model of care, each team member plays an essential role, possessing valuable skill sets and knowledge unique to their specialized backgrounds. As nursing care is one of the main drivers of personnel cost in a dialysis unit (19,20), ensuring that this valuable resource is appropriately managed and optimally aligned with their professional skills is critical. When nurses perform clerical duties such as transcribing laboratory results, or logistical support such as setting up dialysis stations or transporting patients, these tasks could be accomplished by a qualified, but less expensive resource such as a health care aid (15). Further, with more technical jobs that have predictable steps and frequent repetition, such as setting up dialysis machines or establishing vascular access, lower skilled workers could be trained to complete these. For speciality trained staff, such as nurses, dieticians, physicians, or pharmacists, their time could be spent focusing on areas that utilize their skill sets including dialysis prescription adjustments, patient education, anemia management, dietary counseling, or transplant counselling, which can improve patient experience. Conclusion In a growing dialysis population, the challenge to provide high-quality care in an environment of economic constraints has become difficult, but remains a priority for nephrology communities. Much opportunity exists to improve upon the current system of care, manage our resource pool more appropriately, and allow patients to help guide our directions of priorities. References 1. West TD, Gupta M, Balas EA, West DA: Identifying cost management strategies in dialysis clinics: sustainable savings with positive outcomes. Am J Manag Care 8:449–460, 2002 2. Tonelli M: The roads less traveled? Diverging research and clinical priorities for dialysis patients and those with less severe CKD. Am J Kidney Dis 63:124–132, 2014
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3. Information CIoH: Treatment of End-Stage Organ Failure in Canada, 1999 to 2008—CORR 2010 Annual Report. Ottawa, ON, 2010 4. Collins AJ, Foley RN, Herzog C, Chavers B, Gilbertson D, Herzog C, Ishani A, Johansen K, Kasiske B, Kutner N, Liu J, St Peter W, Ding S, Guo H, Kats A, Lamb K, Li S, Li S, Roberts T, Skeans M, Snyder J, Solid C, Thompson B, Weinhandl E, Xiong H, Yusuf A, Zaun D, Arko C, Chen SC, Daniels F, Ebben J, Frazier E, Hanzlik C, Johnson R, Sheets D, Wang X, Forrest B, Constantini E, Everson S, Eggers P, Agodoa L: US Renal Data System 2012 Annual Data Report. Am J Kidney Dis 61: A7, e1-476, 2013 5. De La Rosa G: How applying lean principles in dialysis improved efficiency and patient satisfaction. Nephrol News Issues 27:36, 38, 2013 6. Teich ST, Faddoul FF: Lean management—the journey from Toyota to healthcare. Rambam Maimonides Med J 4:e0007, 2013 7. Batalden PB, Mohr JJ: Building knowledge of health care as a system. Qual Manag Health Care 5:1–12, 1997 8. Newmann JM, Litchfield WE: Adequacy of dialysis: the patient’s role and patient concerns. Semin Nephrol 25:112–119, 2005 9. Berwick DM, Nolan TW, Whittington J: The triple aim: care, health, and cost. Health Aff 27:759–769, 2008 10. Meliones JN, Alton M, Mericle J, Ballard R, Cesari J, Frush KS, Mistry K: 10-Year experience integrating strategic performance improvement initiatives: can the Balanced Scorecard, Six Sigma(R), and Team Training all thrive in a single hospital? In: Henriksen K, Battles JB, Keyes MA, Grady ML (eds). Advances in Patient Safety: New Directions and Alternative Approaches (Vol. 3: Performance and Tools). Rockville, MD: Agency for Healthcare Research and Quality, 2008:2–10 11. Cattinelli I, Bolzoni E, Barbieri C, Mari F, Martin-Guerrero JD, Soria-Olivas E, Martinez-Martinez JM, Gomez-Sanchis J, Amato C, Stopper A, Gatti E: Use of Self-Organizing Maps for Balanced Scorecard analysis to monitor the performance of dialysis clinic chains. Health Care Manag Sci 15:79–90, 2012 12. Fishbane S, Hazzan A: Meeting the 2012 QIP (Quality Incentive Program) clinical measures: strategies for dialysis centers. Am J Kidney Dis 60: S5–S13; quiz S14–S17, 2012 13. Grange S, Hanoy M, Le Roy F, Guerrot D, Godin M: Monitoring of hemodialysis quality-of-care indicators: why is it important? BMC Nephrol 14:109, 2013 14. Stopper A, Amato C, Gioberge S, Giordana G, Marcelli D, Gatti E: Managing complexity at dialysis service centers across Europe. Blood Purif 25:77–89, 2007 15. Soremekun OA, Terwiesch C, Pines JM: Emergency medicine: an operations management view. Acad Emerg Med 18:1262–1268, 2011 16. Hamilton G, Sessoms M: Improving workflow in the dialysis clinic (part 1). Nephrol News Issues 25: 32, 34, 36 passim, 2011 17. Sessoms M, Hamilton G: Improving workflow in the dialysis clinic: part 2. Nephrol News Issues 25: 27–28, 30, 32-24 passim, 2011 18. Collister D, Rigatto C, Hildebrand A, Mulchey K, Plamondon J, Sood MM, Reslerova M, Arsenio J, Coudiere R, Komenda P: Creating a model for improved chronic kidney disease care: designing parameters in quality, efficiency and accountability. Nephrol Dial Transplant 25:3623–3630, 2010 19. Komenda P, Gavaghan MB, Garfield SS, Poret AW, Sood MM: An economic assessment model for in-center, conventional home, and more frequent home hemodialysis. Kidney Int 81:307–313, 2012 20. Baboolal K, McEwan P, Sondhi S, Spiewanowski P, Wechowski J, Wilson K: The cost of renal dialysis in a UK setting–a multicentre study. Nephrol Dial Transplant 23:1982–1989, 2008
Improving the Quality and Efficiency of Conventional Incenter Hemodialysis Jay Hingwala,*† Navdeep Tangri,*‡ Claudio Rigatto,*‡ and Paul Komenda*‡ *Section of Nephrology, Department of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada, †Health Sciences Centre, Winnipeg, Manitoba, Canada, and ‡Seven Oaks General Hospital, Winnipeg, Manitoba, Canada
ABSTRACT There is substantial variability at international, national, and regional levels in how effective dialysis providers are in the implementation of well-accepted interventions to deliver better health outcomes at reduced costs to payers. The growing number of dialysis patients within a finite pool of resources has led to searches for more efficient methods to provide patient care without compromising or diminishing quality. We review here some contemporary
concepts surrounding quality improvement and operations research that may provide clinician administrators to both improve efficiency and quality in facility based hemodialysis units. The creation of balanced scorecards, utilization of process mapping techniques, and the application of LEAN principles may readily improve how hemodialysis care is delivered in an environment of increasing patient volumes and reduced operating resources.
Background and Current Hemodialysis Experience
disparities are common in how providers strive for continuous quality improvement, set quality indicators and targets, data monitoring and feedback are undertaken, and finally how these targets are used in the process of reimbursement and remuneration. The growing number of dialysis patients within a finite pool of resources (2–4) has led to searches for more efficient methods to provide patient care without compromising or diminishing quality. This challenge is now highlighted and expedited by the recent reimbursement changes made by many insurers and governments for health care providers, often bundling remuneration or linking payment to certain quality indicators (e.g., Pay for Performance). Fortunately, dialysis programs are uniquely positioned in that they often have complete control over internal processes and resource allocation, creating an opportunity to take on this task. This paper will explore considerations that are essential for more efficient resource allocation within dialysis programs in the context of a balanced approach to maintaining a high degree of quality in the care delivered.
Patients with kidney failure requiring life-sustaining dialysis suffer from high morbidity and mortality, while consuming a disproportionate amount of health care resources. Evidence-informed interventions that may improve health outcomes while reducing costs for this patient group include delaying the need for dialysis, increasing transplantation rates, the use of home dialysis modalities, encouraging arteriovenous fistula use, and more frequent, long hemodialysis regimens. Despite these measures, however, the majority of kidney failure patients worldwide receive thrice-weekly facility- or clinic-based hemodialysis. There is substantial variability at international, national, and regional levels in how effective dialysis providers are in the implementation of well-accepted interventions to deliver better health outcomes at reduced costs to payers (1). Numerous reasons have been cited in explaining this variability including nephrologist preference, incentives/reimbursement structure, and availability of expertise. Furthermore,
Stakeholders and Priority Setting
Address correspondence to: Dr. Paul Komenda, Seven Oaks General Hospital Renal Program, 2300 Mcphillips Street, 2PD12, Winnipeg, MB, Canada R2V 3M3, or e-mail: [email protected]. Disclosures: The authors have no competing interests or potential conflicts of interest. Seminars in Dialysis—Vol 28, No 2 (March–April) 2015 pp. 169–175 DOI: 10.1111/sdi.12347 © 2015 Wiley Periodicals, Inc.
Although stakeholders are positioned from different perspectives on issues such as costs, priorities, perceived benefits, and impacts, multiple levels of stakeholders are interdependent and share a common goal to deliver quality care to patients. When changes to hemodialysis unit operating procedures are being designed, they should be considered in the 169
170
Hingwala et al.
context of a system and not as individual parts. Figure 1 depicts some steps in optimizing hemodialysis unit efficiency. All relevant stakeholders including front-line and support staff should be included, and change should involve patients, as the impact from their perspective adds value in a patientcentered, health care system (5–7). Further, quality should be defined in terms of health outcomes, satisfaction, and reduced cost (value), and take the patient’s perspective in addition to that of providers and payers (8). The current state must be documented and during the planning stages, stating the ultimate aim of the system, clearly defining the product being made, and considering who the beneficiaries or casualties of the change idea will be will increase the chance of a successful change. Finally, the desired future state can be created using a variety of tools such as LEAN, process engineering, and the concepts of optimal multidisciplinary care. Figure 2 displays an example of the diversity of stakeholders involved in patient care. In general, these are divided into three levels—macrosystem, mesosystem, and microsystem (6). Engagement and support from all levels, especially at the macrosystem level, is crucial to success. The macrosystem level works to incorporate cultural attitudes and goals into the organizational strategy. In general, policy makers from the government level and hospital boards are tasked with setting organizational
objectives, creating a platform of strategic aims, and creating a “blueprint” for allocating resources to achieve these aims. Other key players at this level include insurance providers and private businesses. The midlevel mesosystem supports and interfaces the board and the front lines. Examples of groups at this level are human resources, information technology systems, medical records, clinical departments, and continuous quality improvement committees. At the microsystem level, front-line workers are in direct contact with patients to deliver care. Stakeholders at this level can include nurses, patients, providers, health care aids, emergency medical services, cleaning staff, and technicians. Balanced Score Cards: The Triple Aim Don Berwick from the Institute for Health Improvement describes that improved health care systems are often best achieved through the balance of three interdependent elements—improving health outcomes, patient experience, and reducing costs (9). Together these are commonly described as the triple aim. Within a finite resource pool, improvement in one element often occurs at the expense of another aim, as resources are shifted from one portion of the triple aim to another. As such, effective measurement systems need to be established to
Design Future State • • •
LEAN processes (eliminate waste) Match tasks with appropriate team member Optimize scheduling to match demand with workload
Quality Management Plan Triple Aim Balanced Scorecard • • •
Health Outcomes Patient Experience Reduced Costs
Capture Current State • Process Mapping • Time in Motion Studies • Identify all inputs and desired outputs Fig. 1. Steps to improve hemodialysis unit efficiency.
Identify Key Stakeholders • Clinical Staff • Support Staff • Managers • Payers • Patients
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171
Fig. 2. Example of system-level organization of stakeholders.
monitor for continuous and sustained quality improvement, and ensure that unintended consequences are not occurring. Data collection for this purpose can be an imperative part of feedback in any continuous quality improvement process. When monitoring a system for improvement, it is important to include measures from all three triple aim elements. Balanced score cards (BSC) are valuable display tools to serve this purpose. The measures on a BSC work together to reflect the triple aim and mirror the strategic plan of on organization by allowing consolidation of multiple improvement projects into a single integrated platform (10,11) (e.g., Fig. 3). Front-line activities and measures may be transparently linked to business and governing priorities on the BSC (10). The BSC serve an additional purpose of visually displaying report cards of targets. The importance of this is highlighted in the United States, where quality targets are sometimes linked to physician reimbursement. Some of the targets in dialysis relate to anemia management, hemodialysis adequacy, optimal vascular access, patient satisfaction, mineral metabolism management, and dialysis safety events (12,13). Fresenius Medical Care (FMC) serves as an excellent example of an organization that has effectively implemented indicators for performance monitoring (13). FMC uses indicators that capture patient outcomes (satisfaction, compliance, and prolonged life expectancy), employee perspectives (personnel turnover, absenteeism, overtime, training hours, and employee satisfaction surveys), shareholder perspectives (treatment and patient growth, scheduling efficiency, personal, and other costs), and social responsibilities (energy savings and preservation of the environment) (10,11,14). Targets are based on health care, financial, and managerial guidelines. Raw data are consolidated to make a score for a
key performance indicator. When indicators show below target performance, they are targeted for improvement initiatives. When key performance indicators are exceeded, centers may receive incentives and be studied by other organizations. Principles of Operations Management Operations management consists of managing the oversight, design, and delivery of goods and services (15). More specifically, it aims to maximize efficiency, minimize resource use, while meeting customer requirements and satisfaction. In health care, this means providing accessible high-quality care for patients that improves their health outcomes while minimizing costs. The difficult task is often determining which underlying cause (i.e., root cause) to change first, as in most cases, multiple sources are contributing to suboptimal management. Costs savings derive commonly from improving efficiency, which subsequently reduces the demands on a system. When successful, the conserved resources can be reinvested in other areas of the triple aim that drive better patient outcomes and satisfaction. Efficiency is achieved through three general methods of decreasing wastes, decreasing variability in processes, and increasing flexibility in system capacity (6,15). A common tool used to eliminate overall process wastes is process mapping and value stream mapping, which defines value from the customer perspective, and then eliminates nonvalue-adding activities in the process (16). Any other activities not directly adding value can be essentially eliminated. A second method to reduce wastes is to lower resource wastes, which includes how health care workers spend their time. Common areas that lead to resource wastes are inventory
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Hingwala et al.
Fig. 3. Example of a balanced scorecard for a hemodialysis unit. Green, meets or exceeds target; yellow, does not meet target but on track; red, requires continued focus.
mismanagement, not matching staff availability to patient demands, and patient waiting. Resource waste also takes place when tasks and duties do not parallel staff potential. Time and energy of staff is also wasted with unnecessary transport or motion and can potentially lead to adverse events. Some tools used to improve this are time in motion studies, work sampling, and the 5S’s (Sort, Stabilize, Shine, Standardize, and Sustain) which helps to physically organize a workplace to be more efficient (6). Optimal Use of Hemodialysis Equipment As dialysis technology has evolved, the hemodialysis machine does many jobs that previously were done manually. While on dialysis, vital signs and data reported by the machine are recorded and used as the main means to monitor patient safety. More frequent measurements, such as minute to minute or second to second are not feasibly attainable if they are collected manually. These data could provide valuable information to help predict which patients will develop hypotension during or after dialysis. In many dialysis centers, dialysis machines currently display blood pressures for nurses to manually enter onto run sheets. A more effective technique is to feed this information electronically into a central database that analyzes the patient’s blood pressure in real time, and then alerts the caregiver when the vital signs cross outside a control limit or have a worrisome trend. Then, at the end of a dialysis treatment, the patient’s vital signs, ultrafiltration records with corresponding hematocrit levels, blood and
dialysis flow rates, and access pressures can be transferred into an electrical medical record. This method can potentially provide better patient safety and save nursing time on manual entry of this information, which can then be reallocated to other activities such as educating patients and direct patient care. The Problem of Variable Workload Variability within a dialysis unit is best exemplified in dialysis scheduling. Patients’ demands fluctuate throughout dialysis treatments, the numbers of patients on dialysis in a shift vary as to the duration of their treatment times, and staff availability can change. Increasing flexibility within a system is vital to improving capacity and efficiency. As such, some centers have implemented a float nurse system (6,16,17), while others have created flexibility in staff available as backup to address some of these issues. As the rate-limiting step in flow through a hemodialysis unit is actual time on dialysis, maximal resources must be applied to the efficient initiation and termination of sessions. With this in mind, some centers have trained resource nurses such, to supervise and troubleshoot dialysis in between initiation and termination of a session with the goal of optimizing patient flow. LEAN Processes Improving efficiency, while preserving customer satisfaction, is a common goal in both business
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enterprises and health care settings. The LEAN model was initially developed by Toyota Production Systems, and was later adapted for use by the health care system (6). LEAN initiatives begin with a diverse group of stakeholders collectively documenting all detailed steps of a process. Wastes are then identified as any resources that are used without directly providing an action. The stakeholder group then simplifies the workflow process, being diligent not to remove critical steps that can create errors. The new streamlined process (i.e., value stream mapping) is then tested for workflow and is revised on an ongoing basis. From a dialysis patient’s perspective, a defect includes any part of the process that takes longer than an ideal time. This creates a bottleneck, fails to meet patient needs, causes the patient to wait, and can lessen the patient experience. Figure 4 shows the swim lane process map done by our hemodialysis unit. Once a process workflow is illustrated, a takt time can be established, which is the ideal time needed to complete a task. If supply is targeted to meet demands, then takt time is designed to match the demand rate. For example, if you have 30 dialysis treatments over one day (i.e., the demand), and your dialysis unit is open for 15 hours (900 minutes), then the takt time would be 900 minutes/30 treatments, which is 30 minutes per treatment to meet demands. As dialysis treatment needs 300-minute cycles for put-ons, dialysis treatments, takeoffs, and turnovers, the dialysis unit will need 10 dialysis
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stations to match their demands over one day. If cycle times remain constant, then this scenario would have no delays as takt time is met. This scenario however is not realistic as other factors beyond the total time the dialysis unit is open contribute to delays, such as staffing, patient arrival, or dialysis station availability. These bottlenecks invariably equate to patient wait times. When patients are forced to wait for their dialysis station to be ready, either their treatment times are reduced to meet stringent transportation times, or their treatments are continued past their scheduled times, leading to compounded delays on later shifts. This can translate into worse patient outcomes and experience. An Exercise in Optimal Hemodialysis Unit Scheduling One dialysis unit recognized that hectic scheduling was creating confusion among patients and staff, contributing to patient and staff dissatisfaction, and serving as a nidus for wait times. They reorganized their scheduling to have dependable start and end dialysis times, have more patient–staff contact, balance staff capacity to patient demands (especially during put-ons and takeoffs), match nurse duties to nurse-appropriate activities, have predictable shift times, and improve costs and productively. By first visually displaying current patient
Fig. 4. Seven Oaks Hospital hemodialysis unit—hemodialysis process swim lane diagram.
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scheduling, they discovered that when patients’ dialysis treatments start at similar times, multiple patients had overlapping put-ons and takeoffs, creating a busy and stressful period for patients and staff. From the display, they were also able to elicit where delays and waiting occurred for the next patient starting dialysis treatments in the same station. Next, they created a bar graph showing how many patients per hour are being put on and taken off dialysis treatments, with a superimposed graph displaying staff availability to work during those same times. Several issues were now apparent, such as the busy periods overwhelming staff capacity, and periods of staff underutilization was occurring when patient demand was less. Their improvement initiative involved evenly distributing shorter and longer dialysis treatment durations across all pods in the first two shifts, staggering start times for patients by 20 minutes, and placing the shortest treatment durations in the earliest start times. Together these steps limited simultaneous patient turnovers. They then started the second shift and third times after a turnover period. The third shift patients with the longest treatment durations were started first to shorten the day as much as possible. Once this schedule was established, distribution of staff times and staff shift times were established based on work demands, and staff break times were arranged to match periods of less demand. This model is successful in preventing groups of patients from arriving together in clusters that overwhelm the available capacity and takt time, which is an impetus for wait times. By staggering treatment start times to match standard work times, the demand variability in patients decreases, resources are not overwhelmed, less wait times accumulate (15), and patient experience and staff satisfaction improve (16,17). Achieving Effective Multidisciplinary Care Dialysis patient care occurs in a multidisciplinary model, which can result in workflow difficulties and duplication of work. The model of defining roles and dividing duties has been very successful
Fig. 5. Example of 5-station dialysis unit using staggered start times.
in multidisciplinary Renal Health Clinics (18), and has been highly effective to reduce practitioner cycle times and improve patient throughput, while maintaining quality of care. This success could be translated into dialysis units and help eliminate resource wastes (18). Our dialysis center performed a workflow study to understand the current state. Working with a large stakeholder group, standard operating procedures on specific staff responsibilities and duties were created to provide clarity of staff roles and standardize processes in workflow. In the future, these data could help us organize cycles for our dialysis unit. For example, when patients arrive to a dialysis unit waiting room, they all tend to wait for their dialysis station to be prepared. They then are weighed, vital signs are taken, the vascular access is accessed, and then dialysis begins. As these steps are virtually the same in all patients, this portion of the treatment can be divided into cycles that decrease variability in the setup process between patients. The unique patient needs relating to the treatment, medications, dialysis prescriptions, and special treatments, could be customized at the bedside along with addressing key patient-directed issues. Figure 5 depicts how a 5-station dialysis unit could be scheduled as staggered starts similar to the above example. If dialysis treatments were to be divided into 10-minute cycles during put-ons and takeoffs, it might make staff duties more clear, improve flow and usage of standard operating procedures, and improve patient satisfaction. During put-ons, a cycle of 10 minutes could include weighing a patient, bringing them to their station, and collecting their initial vital signs. The next 10-minute cycle could then involve connecting to vascular access. After dialysis treatment, creating of a cycle lasting 10 minutes to disconnect access, and then 10 minutes to weigh the patient and help them back to the waiting room for their transport home could be made. Cleaning a machine and turnover of a dialysis station could take 20 minutes. Before implementing a new system such as this, patient input is extremely important in this process, as patient experience could diminish if care resembled machine assembly lines.
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In the multidisciplinary dialysis model of care, each team member plays an essential role, possessing valuable skill sets and knowledge unique to their specialized backgrounds. As nursing care is one of the main drivers of personnel cost in a dialysis unit (19,20), ensuring that this valuable resource is appropriately managed and optimally aligned with their professional skills is critical. When nurses perform clerical duties such as transcribing laboratory results, or logistical support such as setting up dialysis stations or transporting patients, these tasks could be accomplished by a qualified, but less expensive resource such as a health care aid (15). Further, with more technical jobs that have predictable steps and frequent repetition, such as setting up dialysis machines or establishing vascular access, lower skilled workers could be trained to complete these. For speciality trained staff, such as nurses, dieticians, physicians, or pharmacists, their time could be spent focusing on areas that utilize their skill sets including dialysis prescription adjustments, patient education, anemia management, dietary counseling, or transplant counselling, which can improve patient experience. Conclusion In a growing dialysis population, the challenge to provide high-quality care in an environment of economic constraints has become difficult, but remains a priority for nephrology communities. Much opportunity exists to improve upon the current system of care, manage our resource pool more appropriately, and allow patients to help guide our directions of priorities. References 1. West TD, Gupta M, Balas EA, West DA: Identifying cost management strategies in dialysis clinics: sustainable savings with positive outcomes. Am J Manag Care 8:449–460, 2002 2. Tonelli M: The roads less traveled? Diverging research and clinical priorities for dialysis patients and those with less severe CKD. Am J Kidney Dis 63:124–132, 2014
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3. Information CIoH: Treatment of End-Stage Organ Failure in Canada, 1999 to 2008—CORR 2010 Annual Report. Ottawa, ON, 2010 4. Collins AJ, Foley RN, Herzog C, Chavers B, Gilbertson D, Herzog C, Ishani A, Johansen K, Kasiske B, Kutner N, Liu J, St Peter W, Ding S, Guo H, Kats A, Lamb K, Li S, Li S, Roberts T, Skeans M, Snyder J, Solid C, Thompson B, Weinhandl E, Xiong H, Yusuf A, Zaun D, Arko C, Chen SC, Daniels F, Ebben J, Frazier E, Hanzlik C, Johnson R, Sheets D, Wang X, Forrest B, Constantini E, Everson S, Eggers P, Agodoa L: US Renal Data System 2012 Annual Data Report. Am J Kidney Dis 61: A7, e1-476, 2013 5. De La Rosa G: How applying lean principles in dialysis improved efficiency and patient satisfaction. Nephrol News Issues 27:36, 38, 2013 6. Teich ST, Faddoul FF: Lean management—the journey from Toyota to healthcare. Rambam Maimonides Med J 4:e0007, 2013 7. Batalden PB, Mohr JJ: Building knowledge of health care as a system. Qual Manag Health Care 5:1–12, 1997 8. Newmann JM, Litchfield WE: Adequacy of dialysis: the patient’s role and patient concerns. Semin Nephrol 25:112–119, 2005 9. Berwick DM, Nolan TW, Whittington J: The triple aim: care, health, and cost. Health Aff 27:759–769, 2008 10. Meliones JN, Alton M, Mericle J, Ballard R, Cesari J, Frush KS, Mistry K: 10-Year experience integrating strategic performance improvement initiatives: can the Balanced Scorecard, Six Sigma(R), and Team Training all thrive in a single hospital? In: Henriksen K, Battles JB, Keyes MA, Grady ML (eds). Advances in Patient Safety: New Directions and Alternative Approaches (Vol. 3: Performance and Tools). Rockville, MD: Agency for Healthcare Research and Quality, 2008:2–10 11. Cattinelli I, Bolzoni E, Barbieri C, Mari F, Martin-Guerrero JD, Soria-Olivas E, Martinez-Martinez JM, Gomez-Sanchis J, Amato C, Stopper A, Gatti E: Use of Self-Organizing Maps for Balanced Scorecard analysis to monitor the performance of dialysis clinic chains. Health Care Manag Sci 15:79–90, 2012 12. Fishbane S, Hazzan A: Meeting the 2012 QIP (Quality Incentive Program) clinical measures: strategies for dialysis centers. Am J Kidney Dis 60: S5–S13; quiz S14–S17, 2012 13. Grange S, Hanoy M, Le Roy F, Guerrot D, Godin M: Monitoring of hemodialysis quality-of-care indicators: why is it important? BMC Nephrol 14:109, 2013 14. Stopper A, Amato C, Gioberge S, Giordana G, Marcelli D, Gatti E: Managing complexity at dialysis service centers across Europe. Blood Purif 25:77–89, 2007 15. Soremekun OA, Terwiesch C, Pines JM: Emergency medicine: an operations management view. Acad Emerg Med 18:1262–1268, 2011 16. Hamilton G, Sessoms M: Improving workflow in the dialysis clinic (part 1). Nephrol News Issues 25: 32, 34, 36 passim, 2011 17. Sessoms M, Hamilton G: Improving workflow in the dialysis clinic: part 2. Nephrol News Issues 25: 27–28, 30, 32-24 passim, 2011 18. Collister D, Rigatto C, Hildebrand A, Mulchey K, Plamondon J, Sood MM, Reslerova M, Arsenio J, Coudiere R, Komenda P: Creating a model for improved chronic kidney disease care: designing parameters in quality, efficiency and accountability. Nephrol Dial Transplant 25:3623–3630, 2010 19. Komenda P, Gavaghan MB, Garfield SS, Poret AW, Sood MM: An economic assessment model for in-center, conventional home, and more frequent home hemodialysis. Kidney Int 81:307–313, 2012 20. Baboolal K, McEwan P, Sondhi S, Spiewanowski P, Wechowski J, Wilson K: The cost of renal dialysis in a UK setting–a multicentre study. Nephrol Dial Transplant 23:1982–1989, 2008
