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InAHQ Six sigma workshop 5
Donald E. Lighter, MD, MBA, FAAP, FACHE Basis of six sigma Vocabulary lesson Defect rates DMAIC – another approach to improvement Example: Broward Health Needle Stick Program © 2010 IHQRE All rights reserved © 2010 IHQRE All rights reserved Scientific approach – based on data Measurement is key – without measures – no six sigma Statistical testing Design of experiments © 2010 IHQRE All rights reserved © 2010 IHQRE All rights reserved LSL – Lower Specification Limit Lowest quality that the customer will tolerate USL – Upper Specification Limit Value below which performance of a product or process is acceptable; can designate the highest level of quality a company can produce COQ – Cost of Quality Cost of ensuring that quality standards are met COPQ - Cost of Poor Quality Cost of not achieving quality standards, includes waste, rework, and excess costs of resources © 2010 IHQRE All rights reserved Often measured by process capability indices or sigma levels Process Mean is Off-Target LSL Process Variation is High LSL USL Move Mean – Center Process USL Reduce Variation Lower Spread On-Target LSL USL LSL = Lower spec limit USL = Upper spec limit © Donald E Lighter, MD (2009) DPMO – Defects per million opportunities Example: 3 medication errors per week 1220 prescriptions on average filled per day DPMO = [3 / (7x1220)] x 1,000,000 = 351 DPMO What sigma level does that represent? © 2010 IHQRE All rights reserved Sigma 3 Defects per million 66,807 Long term capability 93.3% 4 621 99.4% 5 233 99.98% 6 3.4 99.9997% © 2010 IHQRE All rights reserved DPMO DPMO of 351 lies 3 66,807 between 4 and 5 sigma 4 621 5 233 6 3.4 Sigma Where does your med error rate fall? © 2010 IHQRE All rights reserved Sigma 2 3 4 5 6 © 2010 IHQRE All rights reserved Quality Yield 68.0% 93.3% 99.4% 99.98% 99.9997% COPQ Uncompetitive 25 - 40 % 15 - 25 % 5 - 15 % Minimal Sources: Juran Institute; Mikel Harry, Six Sigma, (1999) (with ± 1.5 σ shift) PPM IRS - Tax Advice (phone-in) (140,000 PPM) 1,000,000 100,000 Restaurant Bills Doctor Prescription Writing Payroll Processing Order Write-up Journal Vouchers Wire Transfers Airline Baggage Handling 10,000 • 1,000 100 Purchased Material Lot Reject Rate Best-in-Class 10 Average Company 1 1 2 3 4 Domestic Airline Flight Fatality Rate (0.43 PPM) 5 6 7 Sigma Scale of Measure © 1994 Dr. Mikel J. Harry - V4.0 © 2010 IHQRE All rights reserved Source: Six Sigma Academy: http://www.charlottespin.org/docs/6Sigma.ppt#374,8,Slide 8 © 2010 IHQRE All rights reserved Price decline © 2010 IHQRE All rights reserved Price decline } Cost Recovery $$ © 2010 IHQRE All rights reserved Improvement Approaches DMAIC - Define, Measure, Analyze, Improve, Control Design Approaches DFSS – Design For Six Sigma DMADV – Define, Measure, Analyze, Design, Verify DMEDI – Define, Measure, Explore, Design, Develop, Implement DOE – Design of Experiments Process capability measures DPMO – Defects Per Million Opportunities Cpk – process capability © 2010 IHQRE All rights reserved SIPOC – Supplier, Input, Process, Output, Customer Voices VOC – Voice of the Customer VOP – Voice of the Process VOE – Voice of the Employer VOB – Voice of the Business CTQ – Critical To Quality CTC – Critical To Customer © 2010 IHQRE All rights reserved Y = f(x) Y represents the VOC or other desired outcome f(x) represents the mathematical relationship of inputs (critical x’s) to the VOC Six sigma – modifications of the inputs to eliminate defects in critical x-values can optimize customer service to a level of 99.9997% © 2010 IHQRE All rights reserved Define Select key characteristics (Customer Y) Measure Analyze Validate measurement system for Y Identify variation sources in Y Establish process capability for creating Y Screen causes of change in Y and identify critical x values Define performance standards for Y FOCUS: Y Define improvement objectives for Y Uncover variable relationships between critical x values FOCUS: Y FOCUS: Y and critical x values Improve Control Establish operating tolerances on critical x parameters Determine ability to control critical x parameters Validate measurement system for critical x parameters Develop and implement process controls on critical x parameters FOCUS : critical x FOCUS: critical x © 2010 IHQRE All rights reserved DMAIC Process Management © 2010 IHQRE All rights reserved Source: Long T, Healthcare Organizations: What to do when the low hanging fruit is gone, available at http://healthcare.isixsigma.com/library/content/c030527a.asp, November, 2005. Upper Line: Best current performance Time 0 15 min 15 min Patient Registers at Front Desk, Chart Pulled Time 0 10 min 25 min 15 min 5 min 20 min Nurse reviews chart 25 min 15 min 45 min 20 min 5 min 25 min Patient enters exam room 45 min 5 min 55 min 25 min 5 min 30 min Physician reviews chart 55 min 15 min 75 min 30 min 1 min Physician enters room 75 min 5 min Lower Line: Worst current performance PERT Chart reveals variation in process of 50 min (31 – 81 minutes), due to slack times SIPOC Supplier – multiple to staff and supply office Input – patient visit – starts the process Process – time to encounter Output – patient satisfaction, throughput, quality metrics Customer – the patient 31 min Where can this process improve? © 2010 IHQRE All rights reserved 81 min Upper Line: Best current performance Time 0 15 min 15 min Patient Registers at Front Desk, Chart Pulled Time 0 10 min 25 min 15 min 5 min 20 min Nurse reviews chart 25 min 15 min 45 min 20 min 5 min 25 min Patient enters exam room 45 min 5 min 55 min 25 min 5 min 30 min Physician reviews chart 55 min 15 min 75 min 30 min 1 min Physician enters room 75 min 5 min Lower Line: Worst current performance 31 min Define – check the VOC; what does the customer want? Rapid intake, more time with doctor Survey – wait time of 15 minutes or less (CTC) Team approach – determine areas for shortening time © 2010 IHQRE All rights reserved 81 min Upper Line: Best current performance Time 0 15 min 15 min Patient Registers at Front Desk, Chart Pulled Time 0 10 min 25 min 15 min 5 min 20 min Nurse reviews chart 25 min 15 min 45 min 20 min 5 min 25 min Patient enters exam room 45 min 5 min 55 min 25 min 5 min 30 min Physician reviews chart 55 min 15 min 75 min 30 min 1 min 31 min Physician enters room 75 min 5 min 81 min Lower Line: Worst current performance Measure – well, we’ve already done that, haven’t we? Develop operational definitions for any quality metrics not currently measured Baseline measurements © 2010 IHQRE All rights reserved Upper Line: Best current performance Time 0 15 min 15 min Patient Registers at Front Desk, Chart Pulled Time 0 10 min 25 min 15 min 5 min 20 min Nurse reviews chart 25 min 15 min 45 min 20 min 5 min 25 min Patient enters exam room 45 min 5 min 55 min 25 min 5 min 30 min Physician reviews chart 55 min 15 min 75 min 30 min 1 min 31 min Physician enters room 75 min 5 min 81 min Lower Line: Worst current performance Analyze – what is critical to quality? Review by nurse and physician Ensuring care is delivered and follow up occurs Analyze - Which steps can be improved? Chart pull – pull the chart the night before (or use an EMR, like you should) – net improvement of 15 to 25 min Improve nurse chart review – change chart arrangement, include summary sheet, ensure completeness of chart before giving to nurse – net improvement of 3 – 12 min And on it goes… © 2010 IHQRE All rights reserved Top line – “best” possible process performance Time 0 15 min X 15 min Patient Registers at Front Desk, Chart Pulled Time 0 10 min 25 min Time 0 3 min 3 min Patient registers, nurse pulls chart from ready area, reviews Time 0 3 min 6 min 3 min 2 min 5 min Patient enters exam room 6 min 2 min 10 min 5 min 2 min 7 min Physician reviews chart 10 min 5 min 17 min 7 min 1 min Physician enters exam room 17 min 3 min Bottom line – “worst” possible process performance 8 min Improve Implement time savings strategies Reduction in times as noted above Review performance through time survey © 2010 IHQRE All rights reserved 21 min Top line – “best” possible process performance Time 0 15 min X 15 min Patient Registers at Front Desk, Chart Pulled Time 0 10 min 25 min Time 0 3 min 3 min Patient registers, nurse pulls chart from ready area, reviews Time 0 3 min 6 min 3 min 2 min 5 min Patient enters exam room 6 min 2 min 10 min 5 min 2 min 7 min Physician reviews chart 10 min 5 min 17 min 7 min 1 min Physician enters exam room 17 min 3 min Bottom line – “worst” possible process performance 8 min Results New Step 1 – average time 3.7 minutes New Step 2 – average time 2.1 minutes New Step 3 – average time 5 minutes New Step 4 – average time 1.8 minutes Average number of encounters per day = 50 © 2010 IHQRE All rights reserved 21 min Top line – “best” possible process performance Time 0 15 min X Time 0 15 min Patient Registers at Front Desk, Chart Pulled Time 0 10 min 3 min 3 min Patient registers, nurse pulls chart from ready area, reviews 25 min Time 0 3 min 6 min 3 min 2 min 5 min Patient enters exam room 6 min 2 min 10 min 5 min 2 min 7 min Physician reviews chart 10 min 5 min 17 min 7 min 1 min Physician enters exam room 17 min 3 min Bottom line – “worst” possible process performance New Step “Defect” 1 0.7 min 2 0.1 min 3 3.0 min 4 0.8 min Total 4.6 min © 2010 IHQRE All rights reserved 8 min DPMO 92,000 Given the best possible performance of 8 minutes, the current sigma level is 2 – 3σ 21 min Top line – “best” possible process performance Time 0 15 min X 15 min Patient Registers at Front Desk, Chart Pulled Time 0 10 min 25 min Time 0 3 min 3 min Patient registers, nurse pulls chart from ready area, reviews Time 0 3 min 6 min 3 min 2 min 5 min Patient enters exam room 6 min 2 min 10 min 5 min 2 min 7 min Physician reviews chart 10 min 5 min 17 min 7 min 1 min 8 min Physician enters exam room 17 min 3 min Bottom line – “worst” possible process performance •Where to target? The low hanging fruit is gone. •Time to start reaching higher •What are the next steps? © 2010 IHQRE All rights reserved 21 min Support different situations with specific tools Target largest variance Physician chart review variance = 3 minutes Represents 65% of variance (3/4.6) How to approach? Control Sustain the gains Ensure that new processes become New Step “Defect” 1 0.7 min 2 0.1 min 3 3.0 min 4 0.8 min Total 4.6 min DPMO 92,000 standard procedure Continue measurement to ensure control “Control” Charts! © 2010 IHQRE All rights reserved Choose strategic focus during SPP Identify processes related to focus Apply DMAIC to key processes Set stretch goals to approximate six sigma specification limits Black belts and green belts work with staff to design and implement Execute © 2010 IHQRE All rights reserved Belts! Six Sigma Tae Kwon DO! Champion – supervisory oversight and support Black belt – highest level of expertise in six sigma process, extensive training; direct projects Green belt – project management for six sigma projects; some training, but not as extensive in statistical approaches © 2010 IHQRE All rights reserved Needle stick risks well known (Hep B, Hep C, HIV/AIDS) Risk to employee health Cost of testing Anxiety while awaiting tests or symptoms Treatment costs – monetary and side effects Loss of work time Prevention seen as best option Broward Health’s Environment of Care (EoC) Key Group (corporate-level safety committee) set strategic challenge to reduce contaminated needle sticks Six sigma process management – DMAIC – selected for approach Available at: http://www.isixsigma.com/index.php?option=com_k2&view=item&id=1530&Itemid=155&Itemid=1, August 2010 © 2010 IHQRE All rights reserved Collect data Workers compensation records and employee health nursing department data able to supply the exact cost of each needle stick case over past several years Cost savings sources included: lost time, medical care, lab work, medications, and transportation Estimate of savings: $50,000 a year. Create project charter: Record review of all needle sticks, including a checklist for standardized recording Data used to create prevention measures by key stakeholders, including the manufacturers and suppliers of needles and delivery devices Safe Needle Device Committee formed to study new safety devices on the market Deliverables: Gantt chart with a list of tasks, sub-tasks and projected timelines for completion Regular project team reports including causes, contributing factors, and approaches to prevention and education © 2010 IHQRE All rights reserved EoC Key Group (project sponsor) appointed a team: Safety officers Nursing Workers compensation Infection control Employee health Ad hoc members from the lab, interventional radiology, respiratory therapy, finance and purchasing departments Team created a process map of all situations in which healthcare workers can be stuck by a sharp or needle Drawing blood, administering an injection, starting an IV, removing an IV, obtaining arterial blood gases, and obtaining cultures and specimens High risk steps noted 2005 - needle stick metric (sticks/10000 adjusted pt days) Measured past five years for trend analysis Threshold of 3 sticks/10000 APD set based on historical data. Data analysis revealed slight increase (17 percent) in the number of sticks in fiscal year 2004 – RCA performed © 2010 IHQRE All rights reserved 2 1 © 2010 IHQRE All rights reserved 1. Most sticks were due to unsafe passing of sutures or instruments during surgery and the use of nonsafety intramuscular (IM) needles. 2. The next most frequent cause was disposal related, including four sticks from needles being placed in the trash impacting environmental services staff. Contaminated needle sticks defined as defects in the care system Opportunities for error = one stick per employee per workday Hospital data showed: Table 1: Contaminated Needle Stick Data, 2005 through 2010 Year-to-date Fiscal Year Opportunities for Error 2005 2006 2007 2008 2009 2010 YTD 1,201,000 1,482,500 1,522,500 1,605,250 1,833,500 457,746 Defects Contaminated Needle Sticks per Unit DPMO Process Sigma 86 97 106 113 89 20 0.000057 0.000065 0.000070 0.000070 0.000049 0.000044 57 65 70 70 49 49 5.36 5.32 5.31 5.31 5.40 5.42 © 2010 IHQRE All rights reserved RCA: Team studied safety device use, ▪ 2003 – 9% of contaminated needle sticks were due to lack of an acceptable safety device; 10 percent were due to using the safety device incorrectly Interventions prior to 2010: multiple safe needle devices and needle-less devices were evaluated and selected to eliminate the first root cause Other measurements: Data on subtasks and cycle time related to contaminated needle sticks (in-depth review of the accident reports and review with the employee health nurses and workers compensation) ▪ Measured by number, cost, manhours worked, adjusted patient days and DPMO Data on the cost of contaminated needle sticks for fiscal year 2006 and the first half of fiscal ’07 system-wide ▪ ▪ ▪ ▪ Time spent reporting, managing and following up on the exposures Salaries Laboratory testing $86,618 in 6 quarters for 144 contaminated needle sticks; average cost of a single contaminated needle stick was $602 © 2010 IHQRE All rights reserved Subtasks involved in contaminated needle sticks were analyzed for 12-month period August 2008 to August 2009. Table 2: Contaminated Needle Sticks from August 2008 to August 2009 and Activity Subtask Number Percent Drawing blood 23 26% No explanation 18 21% During disposal 9 10% Using other hand to close safety device 8 9% In the trash, impacting environmental services staff 6 7% During surgery After giving insulin 6 6 7% 7% After giving an injection 6 7% Removing or adding to an IV 5 6% Total 87 © 2010 IHQRE All rights reserved Team informed nursing, laboratory, and respiratory therapy managers that drawing blood was the highest risk subtask Team worked with purchasing to bring in a new vacutainer needle for drawing blood.. Benchmarking data obtained Literature search Benchmark job titles involved in needle sticks - nursing staff most involved, but laboratory staff, physicians, housekeepers and other healthcare workers are also injured Define tasks at highest risk Evidence for efficacy of multi-faceted intervention program © 2010 IHQRE All rights reserved • Focus on • Testing and implementing safety devices • Training staff • Ensuring awareness of user lack of adherence as source of contaminated needle sticks © 2010 IHQRE All rights reserved Did you know, all contaminated needle sticks are due to technique/user error? Did you know, all contaminated needle sticks are due to technique/user error? • Wear gloves. • Keep other hand away from needle. • Use safety devices with one hand. • If device does not activate, just discard as is. • Carry only one sharp at a time for disposal. • Avoid use of needles whenever possible. • Use a needle-less device to obtain specimens from all catheters. • Never hand an exposed needle to another person. • Never discard needles into trash or drapes. • Never reach into needle boxes. • Vacutainers are to be disposed with needle. • Never try to overfill sharps containers. • Assume soiled trays/drapes contain needles and sharps. • Get help beforehand with a confused or combative patient. Safe Sharps Disposal - Prevent Contaminated Sticks • While wearing gloves: • Hold device in one hand. • Keep other hand away. • Activate safety sheath/button with one hand. • Drop sharp into container flap. • Flip the flap with one finger. • Do not touch sharps container. • Change out container when 3/4 full. © 2010 IHQRE All rights reserved 2009 Number of contaminated needle sticks down 21 percent over 2008 Overall avoided $135,942.00 in cumulative costs to Broward Health year over year from the baseline of $78,798.00 in needle-stick related costs in 2000 Costs of contaminated needle sticks up 29 percent over 2008 due to treatments for HIV and lost time © 2010 IHQRE All rights reserved Institutionalize policies and procedures established by the performance improvement process • Remove barriers to correct behavior • Ensure safety devices are in place and utilized • Training and awareness in classroom and online programs Monitoring systems • Safety officers, workers compensation, and employee health nurses track rates and reports and intervene with specific and system improvements • Rates and costs reported quarterly at each of the five regional quality committees • Rates placed on the corporate dashboard for the Board of Directors and the Quality Assurance and Oversight Committee • CFO reviews quarterly cost savings metrics in the Environment of Care, including contaminated needle stick costs. © 2010 IHQRE All rights reserved Which one Is mine? Lean Six Sigma can find the answers Donald E. Lighter, MD What are six sigma metrics Translating metrics to health care Setting six sigma targets Accounting for measurement error DPMO Rolled Throughput Yield DPU First Pass Yield Sigma Level DPMO • 'Opportunity' is the possibility of a defect • One unit may have many opportunities for a defect • Example – a physician bill to an insurer is one unit, but any of the fields on the bill could be incorrect; thus there are several opportunities for each unit 6s process improvement projects aim for <3.4 DPMO Provides a common standard to compare the defect rates and performance between processes Example: 3 medication errors per day 1220 orders/prescriptions on average filled per day DPMO = [3 / (1220)] x 1,000,000 = 2460 DPMO What sigma level does that represent? © Donald E Lighter, MD (2009) Sigma DPMO 3 66,807 4 621 5 233 6 3.4 © Donald E Lighter, MD (2009) DPMO of 2460 lies between 4 and 5 sigma A DPMO/6σ table provides the actual sigma level Defects per 100 31 27 24 21 18 16 14 12 10 8 7 6 5 4 3 2 2 1 1 1 Defects Defects per per Success rate 10,000 1,000,000 3,090 309,000 69.1% 2,740 274,000 72.6% 2,420 242,000 75.8% 2,120 212,000 78.8% 1,840 184,000 81.6% 1,590 159,000 84.1% 1,360 136,000 86.4% 1,150 115,000 88.5% 968 96,800 90.32% 808 80,800 91.92% 668 66,800 93.32% 548 54,800 94.52% 446 44,600 95.54% 359 35,900 96.41% 287 28,700 97.13% 228 22,800 97.72% 179 17,900 98.21% 139 13,900 98.61% 107 10,700 98.93% 8,200 99.18% 82 Sigma Value 2.0 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 3.0 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 Defects per 100 1 Defects per 10,000 62 47 35 26 19 14 10 7 5 3 2 2 1 1 Defects per 1,000,000 6,210 4,660 3,470 2,560 1,870 1,350 968 687 483 337 233 159 108 72 48 32 21 13 9 5 3.4 The med error sigma level is 4.3 Success rate 99.379% 99.534% 99.653% 99.744% 99.813% 99.865% 99.903% 99.931% 99.952% 99.966% 99.9767% 99.9841% 99.9892% 99.9928% 99.9952% 99.9968% 99.9979% 99.9987% 99.9991% 99.9995% 99.99966% Sigma Value 4.0 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 5.0 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 6.0 DPU = average number of defects per unit based on processing a number of units. For example: • 3 errors in 1220 med orders, one reworked, two (IV mixtures) scrapped • DPU = 2/1220 = 0.0016 • DPU counts only the units scrapped, not the units for which errors were corrected Most useful in calculating First Pass Yield First pass yield (FPY) Rolled Throughput Yield (RTY) Proportion of units that, on average, go through a process first time without defects. It is calculated as follows: FPY = e − DPU FPY for the Med Error process is thus: FPY = e −0.0016 = 0.9984 Probability that a unit can pass through a process without defects Calculation – product of yield at each step Example: suppose a process has six steps, and each step has a yield defined by yi RTY = y1 * y2 * y3 * ... * yn Does not account for rework, since corrected items are included as part of the yield calculation Medical bills created per day in a medical practice – two physicians Day Defects Scrap Rework Units DPU FPY RTY 1 10 5 5 100 0.100 0.905 0.905 2 12 5 7 95 0.126 0.881 0.797 3 8 0 8 90 0.089 0.915 0.730 4 10 5 5 90 0.111 0.895 0.653 5 5 1 4 85 0.059 0.943 0.616 460 0.485 Totals 45 0.616 Measurement of process capability Relates number of defects (DPMO) to the statistical measurement of process effectiveness Calculation: • Calculate DPMO • Determine sigma level from table Sigma levels can be used to compare dissimilar processes, establish priorities Defects per 100 31 27 24 21 18 16 14 12 10 8 7 6 5 4 3 2 2 1 1 1 Defects Defects per per Success rate 10,000 1,000,000 3,090 309,000 69.1% 2,740 274,000 72.6% 2,420 242,000 75.8% 2,120 212,000 78.8% 1,840 184,000 81.6% 1,590 159,000 84.1% 1,360 136,000 86.4% 1,150 115,000 88.5% 968 96,800 90.32% 808 80,800 91.92% 668 66,800 93.32% 548 54,800 94.52% 446 44,600 95.54% 359 35,900 96.41% 287 28,700 97.13% 228 22,800 97.72% 179 17,900 98.21% 139 13,900 98.61% 107 10,700 98.93% 8,200 99.18% 82 Sigma Value 2.0 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 3.0 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 Defects per 100 1 Defects per 10,000 62 47 35 26 19 14 10 7 5 3 2 2 1 1 Defects per 1,000,000 6,210 4,660 3,470 2,560 1,870 1,350 968 687 483 337 233 159 108 72 48 32 21 13 9 5 3.4 Success rate 99.379% 99.534% 99.653% 99.744% 99.813% 99.865% 99.903% 99.931% 99.952% 99.966% 99.9767% 99.9841% 99.9892% 99.9928% 99.9952% 99.9968% 99.9979% 99.9987% 99.9991% 99.9995% 99.99966% Sigma Value 4.0 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 5.0 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 6.0 Four major areas under study for improvement: Nutritional services Lab Imaging Pharmacy Studied each unit for one month, statistics gathered on defects per week Average Total Total defects/ units/week week Business unit Performance Total scrap Total rework DPMO DPU FPY RTY Sigma level Nutritional services (meal units served) 1495 38 18 20 25418 0.012 0.988032 0.912 3.5 Lab (clinical tests performed) 2948 42 32 10 14247 0.011 0.989204 0.831 3.7 Imaging (planar x-rays performed) 1874 29 12 17 15475 0.006 0.993617 0.942 3.7 Pharmacy (prescriptions/orders filled) 1539 84 31 53 54581 0.020 0.980059 0.928 3.2 Sigma Levels for Business Unit Processes 3.8 3.6 3.4 3.2 3 2.8 Nutritional services Lab Imaging Pharmacy How to establish priorities? What other data needed? Who should be involved in analysis and decisions? How should the final decision be made?
