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Laboratory Toolbox for Process Improvement
Six Sigma at North Shore – Long Island Jewish Health System
Nancy Bliss Riebling, Laurel Tria (North Shore–Long Island Jewish Health System, Great Neck, NY)
DOI: 10.1309/H2U5QGDEGQ6MG1KT
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January 2008 Volume 39 Number 1 LABMEDICINE
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D
uring the 1990s, the health care industry began searching for better process-improvement models. Quality programs like Total Quality Management (TQM) had failed to sufficiently address systemic inefficiencies or deliver sustainable results. Without a tool to expose and deal with actual root causes, one of the primary targets for slashing the budget became labor. Simply trimming the workforce, however, was not the answer and did not produce the desired long-term effect. The clinical laboratory, which historically had been a revenue-generating department, now was becoming a cost center. The volume of tests, complexity, and cost were skyrocketing. Laboratory management found reliability could not be achieved through the control of accuracy in the analytical phase of the testing process alone, because studies showed 70% to 80% of laboratory errors occurred before that, in the preanalytical phase.1 At the same time, Six Sigma was gaining momentum in business communities worldwide.
• It includes a robust control phase to sustain results. In January 2002, the North Shore–Long Island Jewish (LIJ) Health System launched its Center for Learning and Innovation (CLI) in conjunction with General Electric and the Harvard School of Public Health. The corporate university features several divisions, one of which is Operational Performance Solutions. This group of employees is trained in the use of Six Sigma and Lean to improve efficiencies and enhance quality. The North Shore–LIJ Health System was the third health system nationwide to implement a Six Sigma initiative. North Shore–LIJ Health System, headquartered in Great Neck, NY, is the third largest nonsectarian health system in the country, comprising 15 hospitals. The Center for Learning and Innovation has trained 7 Master Black Belts, 25 Black Belts, and 158 Green Belts. In conjunction with Six Sigma training, employees acquire valuable change-management skills by taking classes in change acceleration process (CAP) and fast-track decision making (FTD). As one of the original Master Blacks Belts and the current Director of Operational Performance Solutions, my former department, the laboratory, became a pioneer in using Six Sigma, Lean, and FTD for process improvement because of my Six Sigma background as a medical technologist. Laboratory senior leaderSix Sigma had its beginnings in the 1980s at Motorola as a ship’s support and willingness to think outside the box was tool to manage production variation using rigorous statistical crucial for our success. analysis. It taught organizations the need to master customer Created in 1998, the North Shore–LIJ laboratory model focus, to process definitions, and to engage in measurement sysconsists of a strategically-located core laboratory using total labotem analysis, root-cause analysis, and consistent process monitorratory automation, a rapid-response laboratory in each of the ing. During the mid-90s, Jack Welch, CEO at General Electric, system’s 15 hospitals, a standardized laboratory information syscreated a vision for his organization based on the Six Sigma tem (LIS), standardized laboratory instrumentation, and consolimethodology. It became the way they did business. It was the dated testing at the core laboratory. Work for the core laboratory common language across diverse divisions. Six Sigma offers discomes from the health system’s hospitals, long-term facilities, tinct advantages over traditional initiatives in the following ways: clinical trials, physician offices, and reference testing. The labora• Six Sigma focuses on customer requirements, the “Voice tory performs over 4 million tests per year, of which approxiof the Customer”; mately 65% are routine testing for the North Shore–LIJ • It targets defects and process variation instead of averages; network, as well as all the network’s microbiology, special tests, • It uses a highly-structured, data-driven framework for molecular diagnostics, and reference testing. problem solving; and As part of the laboratory’s ongoing performance-improvement process, accessioning errors have been measured historically for years. This was the first issue the laboratory High Level Process Map: High Level Process Map: tackled using the Six Sigma methodology. Accessioning errors were a chronic problem for which consultants had previously been engaged without arriving at a successful resolution. Requisition for blood work • Physician supplies demographic information At the core laboratory, a multidisreceived at the core lab • Physician’s office draw specimens ciplinary team of technical, compliance, marketing, quality, and accessioning • Verify specimen with requisition Accessionerenters management staff was assembled to demographics & test • Register patient in LIS tackle the problem using the Define, in Laboratory Information • Order test Measure, Analyze, Improve, and ConSystem • Label specimen trol (DMAIC) approach.
Specimen Delivered
• Specimens placed on CLAS or delivered to department
Results
• Result • Chart • Bill
Figure 1_High-level process map.
Define During the Define phase, the team developed a high-level process map (Figure 1) beginning with the initial step of the physician filling out the requisition and drawing the specimen to the last step when the final chart copy is printed. Through careful data collection and analysis, the team found
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Feature 5% of the specimens accessioned at the core laboratory were inaccurate or incomplete, which was in line with previouslycollected historical data. These inaccuracies caused delays in reimbursement and decreased customer satisfaction. The Six Sigma team used change acceleration process tools, such as the threat/opportunity matrix, during the Define phase to obtain buy-in from the laboratory staff for the necessity of pursing this project. This tool demonstrated that, if successful, the laboratory would be able to increase productivity and customer satisfaction while decreasing the number of incomplete or inaccurate requisitions. If unsuccessful in the long term, the core laboratory’s reputation would be diminished, leading to a loss of revenue. Measure In the Measure phase, the first order of business was to create operational definitions to define a defect. The team defined a defect as a laboratory requisition with missing or inaccurate demographic, test, or ICD-9 information. The team performed a measurement system analysis by giving the requisition checking staff a test of 25 requisitions—some good, some bad. Each requisition was rated as good or bad on whether or not all 7 fields were entered in the LIS correctly. The gauge demonstrated repeatability, reproducibility, and accuracy in more than 90%. A review of 5,607 requisitions collected over a 1-week period revealed a defect rate of 283. To calculate defects per million opportunities (DPMO), the discrete data formula of D/ (U) (O) = 283/ (5,607) (7) × 1,000,000 = DPMO = 7,210 was used, where D= Defect, U=Unit, and O=Opportunity. The calculated DPMO of 7,210 is equivalent to a Sigma score of 3.9. The team also measured the number of requisitions processed per hour as 17 with an SD of 7. The team used the CAP tool of a stakeholder analysis to aid in determining a strategy to move those individuals who were moderately against the project to a more supportive position. It also helped identify those individuals who were likely to touch the process and thus could be a resource to the team. Analyze In the Analyze phase, the team benchmarked the core laboratory’s performance against other reference laboratories throughout the country. The core laboratory’s accessioning error rate of 3.9 Sigma was comparable to industry standards; however, the productivity of the accessioning staff had a large amount of variation and was below industry standard. The team used tools, such as the cause and effect (fishbone) diagram, to capture all the possible reasons (X’s) for accessioning errors (Y’s). They then began to create graphs (pictures) to separate the vital X’s from the trivial many. Graphical analysis using Pareto charts (Figure 2) indicated 50% of the accessioning errors were due to incorrect entry of the Social Security number for skilled nursing facility patients. This discovery was an enlightening observation or “ah-ha.” Before the analysis, the team members had been convinced the culprit would be the handwriting of physicians on the requisitions. This “X” proved to be statistically significant using the chi-square test for discrete data. The null hypothesis that all types of demographic errors are the same was rejected because the P value of 0.002 was less than 0.05, and thus the team could conclude a statistical difference in the number of defects that existed among the different demographic fields. The team also determined that a small
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percentage of the staff (5 out of 24) was making most of the errors, which follows the 80/20 rule (Figure 2). Improve In the Improve phase, the team drilled down using the Five Why tool.2 They found the skilled nursing facilities used addressographs for patient demographic information. Addressographs have multiple identifiers, making interpretation difficult for the accessioning staff. In addition, addressographs tend to be illegible when run through an addressograph machine. Peel-off labels located on the bottom of the core laboratory’s patient chart could be placed on the laboratory requisition, thus eliminating the need for the addressograph. The team also created desktop reference guides to be positioned at each accessioning station to alleviate accessioning errors. This helped make all the information new hires were supplied with at orientation and training readily available. Ongoing competency assessment was achieved by using blind proficiency specimens throughout accessioning. The team modeled the assessment on the proficiency testing program performed in the technical areas of the laboratory that are required for licensing. Control In the Control phase, the Six Sigma team implemented a plan that incorporates individual- and moving-range control charts for monitoring accessioner productivity. The DPMO and corresponding Sigma score for accessioning errors is monitored. At the end of the control phase, the process went from a 3.9 Sigma score to 4.5 Sigma. Productivity increased from 17 to 26 requisitions per hour with the standard deviation decreasing by 50% (Figure 3). The accessioning department was able to handle a 43% increase in outreach specimen volume without adding additional staff.
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Figure 2_Graphical analysis using Pareto charts.
Fast-Track Decision Making
Change acceleration process is a philosophy and tool set designed to help overcome cultural barriers to change by creating a shared need, shaping a vision, and mobilizing commitment. Fast-track decision making (FTD), which is North Shore–LIJ’s version of GE’s “Work-Out” process, is a rapid problem-solving approach with team involvement and in-meeting decisions. It is a catalyst for change, focusing on the process to drive improvement and empowering the people closest to the process to
develop and implement appropriate solutions. Specimen movement within the laboratory was a “heartburn” issue for staff. The issue presented to the frontline supervisors and employees of the accessioning and technical departments was how to facilitate the movement of specimens from the nontechnical to technical area of the laboratory. The session led participants to propose the following 3 recommendations: 1. A runner position: someone to move specimens around the accessioning department;
Figure 3_Productivity.
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Figure 4_Identifying waste with notes.
2. A color-coded book listing all laboratory tests and which department performed the analysis; and 3. Color-coded signs throughout the laboratory matching the color coding in the book so accessioning staff members know where to deliver specific specimens in the laboratory. The employees designed the signs and books. The response from employees was so favorable that the idea was translated to other key areas within the laboratory, such as marketing and information services.
Lean
In 2005, the Operational Performance Solutions group added the Lean methodology to their toolbox of improvement methodologies. The principles of Lean thinking have been attributed to the Toyota Production System, which is to do the “right thing” in the “right way” to minimize waste. The goal of Lean is to reduce the non-value activities within a process. Key tools for a Lean initiative are the following: • Value stream mapping • 5S • Kaizen • Process balancing The laboratory’s first Lean project was to improve billing efficiency. The core laboratory spent about 12.1% of each dollar collected on billing-related expenses. The days sales outstanding (DSO) was 127 days. The laboratory collected approximately 20% of gross charges on non-client bills. The laboratory scheduled a 3-day Kaizen event. The Kaizen approach incorporates intense progress through the DMAIC process. The Define and Measure preparatory work is done by the Black Belt prior to the event. During a Kaizen event, staff
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is reassigned to work full time on the issue. 3 The first step is to create a value-stream map of the current process. Valuestream mapping entails diagramming the detailed activities of the process, showing the flow of materials and information through the process, and incorporating baseline data for lead times, queues, and cycle times.4 Each step is evaluated for its value contribution to the end product and effect on quality. If the step is a non-value-added step, it is considered waste and a good candidate for elimination. There are 7 types of waste: transportation, inventory, motion, waiting, overproduction, overprocessing, and defects (TIMWOOD). Business non-value-added steps are those which may not be eliminated due to licensure or accreditation.3 The team consisting of content experts identified all the types of waste in the process using colored Post-It notes (Figure 4). They prioritized the issues using N/3 voting, a tool to prioritize the most important items from list and build consensus on the team. This is accomplished by dividing the total number of items “N” by 3. Each team member then receives that many votes to use all on one issue or on multiple issues. The issues with the most votes are addressed first. Three key issues were identified: problem requisitions and error processing, client education, and issues management. The team used tools such as brainstorming and the control-impact matrix to develop solutions. The team uncovered that errors needed to be corrected in 3 different laboratory information systems (accessioning, technical, and billing) and that three different departments were making the same corrections (overprocessing). The team used the tool of process balancing to develop their improvement strategy. Key design principles are to stabilize cycle times, balance tasks and labor across process steps, and to optimize the number of process steps. By giving the
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Figure 5_Issue-management log.
billing clerk access to the 3 information systems, demographic information could be corrected in all systems at once. This decreased the days-to-price from greater than 14 to less than 5 and reduced the variation in accessioning cycle times. To enhance client education, a user-friendly requisition was developed with accompanying laminated guides and highlighted required information. Thank-you letters were sent to physician offices that were 100% compliant. An issue-management log was designed for easy access on any computer so issues could be logged and tracked (Figure 5). To create and maintain an organized, clean, and highperformance workplace, the team used the 5S principles. 5S is a systematic way to improve the workplace, and the 5 S’s stand for: Sort (remove all unnecessary items from the work environment), Simplify (label and arrange key items in the area), Shine (clean the area), Standardize (develop a consistent way of performing the tasks), and Sustain (develop checklists and audits to maintain the improvement). The team reported out after the initial Kaizen and then at 30 and 60 days afterwards. Using tools such as the RACI chart, the team was able to keep track of their progress (Figure 6). A RACI chart enables the team to keep track of who is Responsible (to actively participate in an activity), Accountable (the key person for the deliverable), Consultation (a person with an expertise or decision making ability), and Inform (people affected by the project). The improvements have been sustained. Current metrics show the billing department at a DSO of 91, with approximately 10.9% of each dollar collected spent on billing-related expenses. 12
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Value Analysis Teams One of the challenges an organization faces when implementing Six Sigma and Lean is translating the knowledge learned from a completed project to other areas. A laboratory turnaround time project done at one hospital whose improvements we would try to roll out at another hospital would meet resistance. The old adage “we’re different” would surface. Another project would be done with a similar outcome. As part of the system initiative of standardization and best practice, Value Analysis Teams were established for key areas and disciplines. The laboratory team consists of laboratory managers from all system facilities. The team reports monthly to senior leadership on key indicators of patient experience, quality, and financial performance. The laboratory’s quality initiative is “to decrease the turnaround time of routine laboratory tests from draw to result to less than 60 minutes.” The laboratory created a multidisciplinary team with employees from the phlebotomy, accessioning, and technical departments at 4 different hospitals. The team participated in a 3-day Lean Kaizen at one hospital, and the improvements were rolled out as a pilot for all hospitals. Solutions included moving equipment into a horseshoe shape design to decrease non-value-added walking (Figure 7), using a runner to get specimens down to the laboratory in small timely batches, the purchase of additional small centrifuges, and the movement of printers and phones closer to key technical areas. The team followed the Kaizen, 30- and 60-day report-out format. The team reconvened at another facility for a one-day FTD. They reviewed the current process and then, using the strategies already implemented at the
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Figure 6_Responsible, Accountable, Consultation, and Inform (RACI) chart.
Figure 7_Redesigning workflow.
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Feature previous site, put the improvements in place, building on what they learned while incorporating the existing culture of the facility into their improvement strategy. The resulting success (Table 1) created cross-functional teams across job functions and facilities. Table 1_Turnaround Times (TAT) Less Than 60 Minutes
Lessons Learned Implementing the tools of Six Sigma and Lean are a journey not for the fainthearted, as Chief Learning Officer Kathy Gallo, RN, PhD, MBA, likes to say. In order to be successful, the organization needs to commit the resources to educate the staff in the methodologies. Many organizations underestimate the people or the acceptance portion of the equation Q × A = E. The “Q” is the quality or technical aspect of change, the “A” is the acceptance portion (the people who will or will not make it happen), and the “E” is the effectiveness of the change or project. You can develop a robust solution using the tools (Q=7), but if there is no buy-in from staff (A=1), the effectiveness is minimal (E=7). If you achieve buy-in (A=7) by educating the staff, your effectiveness exponentially increases (E=49). Lessons we have learned are that education does not mean everyone on the team needs to be a statistics expert. Front-line staff can learn to use control charts and develop operational definitions and value stream maps while leaving the hypothesis testing to the Black Belts. Senior leadership support is vital. Accountability at all levels is the key to success. Incorporating the tools into the Value Analysis Teams has taken the organization from a project perspective to common language approach. Six Sigma and Lean are how we do business. LM
1. Pierangelo B. Errors in laboratory medicine. Clin Chem. 2002;48:691–698. 2. For definition of the Five Why tool, go to www.asq.org/sixsigma/ terms/index.html. 3. Michael, G. The Lean Six Sigma Pocket Tool Book. New York, NY: McGraw Hill; 2005: 2. 4. Trusko B, Pexton C. Improving Healthcare Quality & Cost with Six Sigma. Upper Saddle River, NJ: FT Press; 2007:378.
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