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Mark Murray MD, MPA Mark Murray & Associates 2209 Capitol Ave Sacramento, CA 95816 916-441-3070 Fax 916-446-8009 murraytant@msn.com Big System Flow
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The problem ED overcrowding Hospital overcrowding Diversions—external and internal LWBS Cancellations, particularly of elective surgical cases Variable utilization Cost and revenue implications with the variation
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Introverted/introspection Flow system dynamics and gravity Customer flow- value stream Horizontal/vertical Effective, efficient and satisfying Demand, supply, activity, gap & variation System Optimize
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Basic Dynamic
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Demand/Supply Dynamic
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Variation
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Terms Demand: workload generated within a specified time frame Activity: work done within a specified time frame Supply: “worker” (person or machine) set aside to do the work within the specified time frame Backlog: work in progress, work waiting to be completed, wait list, queue, inventory, warehouse Constraint/bottleneck: rate-limiting step
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Why focus on delay? Delay results from a mismatch either temporary or permanent of demand and supply Delays lead to dissatisfaction Delays sub-optimize revenue Delays adversely effect clinical outcomes Delays cost money Delays represent system inefficiency We can only go as fast as the slowest step Perception that delay=lack of resource
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Why do queues form? Demand > Supply Variation Paradigm Buffer for revenue, for predictability and for assurance of 100% utilization (false productivity)
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Demand > capacity Time waiting numbers If Demand > Activity or Capacity
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Levels or types of variation Volume Arrivals Process time
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Variation Within Day Between Day
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Demand & capacity for breast clinic 0 20 40 60 Week Number 3 January 2000 22nd January 2001 Total number of patients referred Number of clinic slots available
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Sources of demand variation Variation in volume (between day variation) Random arrivals (within day variation) Randomness of clinical condition/acuity/time- handling time Randomness of internally generated demand (electives)
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Sources of supply variation Relative lack of any of the converging supply components Pattern of supply components Carve outs or priorities that restrict flexibility
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Moment of truth Even if the average demand = average supply The variation of demand + the variation of supply Will result in a queue Waiting times or delays inevitably result from system variation
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Walter A. Shewart -early 1920’s, Bell Laboratories While every process displays variation… some processes display controlled variation stable,consistent pattern of variation constant causes/ “chance” Common cause variation while others display uncontrolled variation pattern changes over time special cause variation/“assignable”
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2 ways to improve a process If uncontrolled variation: identify special causes (may be good or bad) process is unstable variation is extrinsic to process cause should be identified and “treated” If controlled variation: reduce variation, improve outcome process is stable variation is inherent to process therefore, process must be changed: reduce steps, increase reliability of each step
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Natural Variation: A Stable Process Upper process limit Mean Lower process limit
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Special Cause Variation
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Variation and Predictability Which demand stream is more variable- planned or unplanned? Which demand stream is more predictable planned or unplanned?
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Know and manage variation Natural/unplanned Results from the natural rate at which illness brings patients into the hospital Influenced by level of health, prevention, early detection Artificial/planned This pattern results from behavior of people, processes or systems This variation is theoretically controllable
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Vicious cycle Variation in demand or in supply create a delay The wait time creates a need to prioritize Prioritization leads to inflexibility and more variation More waits Assumption that demand is greater than supply Addition of more supply Adds more variation
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Variation Variation is ubiquitous Variation is not measured More variation in planned than unplanned Demand = Volume x LOS So variation has a long-term effect over days, not a single effect as a single incident
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What does the patient see?
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Linear Flow DDSDSDSDSDS Step 1Step 2Step 3Step 4Step 5 Delay
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What do we see?
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Vertical Flow Filter C A
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Appointment Template Filter New Return Consult Procedure Post-surgery Return-long Return-short New-long New-short Consult-long Consult-short
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Office Manager Filter OfficeORCallAdminOff
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What we see Today’s schedules of supply to match the various demand streams Response to the demand streams Waits for single isolated patients, not the sum of waits for that patient Waits after us, not in front of us
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What we don’t see The demand streams The wait in each of the demand streams The wait at each step The patients horizontal journey The three dimensional view
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Days Delay External Demand Delay PCSC Test/ Surgery Procedure Hospital Follow up A B C D A Supply lines that match demand stream Vertical/Horizontal Days
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Cancer Center flow-map Test SC Surgery Discharge External Demand PC Bed MDT Oncology Radiation Chemo Follow up Test Follow up Internal Demand Test MDT
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Medical Flow Test SC Hospital ED Post hospital venue Procedure PC ICU Return Test
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Surgery Flow Test SC Surgery ED Bed Internal Demand External Demand ICU PC Follow up Discharge
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What do we learn? The system is complex with at least 3 dimensions The patients move horizontally, we think vertically Supply allocation decisions, made on instinct, have huge system effects There is a great deal of variation in both demand and in supply at each step Variation is amplified as we move Queues are a result of a permanent or temporary mismatch of demand and supply
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What else do we learn? Patients move from one warehouse to another There is always a constraint We are blind at the intersections Carve out or priority makes the queues worse, not better Increasing supply does not always work, the delays remain but just get moved
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Process for Improvement Team Aim Map Change Measure - Principles -Strategies Measure again
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Our Task in Flow Improvement Flow map the customer flow process: input, throughput, output Use a process for improvement: team, aim, change and measure Use a set of change principles at & between each step Measure: delay for and at each step, DSA,variation Achieve a balance of demand and supply at every step with change strategies (change strategy: balance) Reduce the variation in both demand and supply at every step ( change strategy: contingency plans ) Identify common and special causes of variation Be flexible on the supply side Address the system constraint first Create the correct linkages
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Apply High Leverage Changes within and between each step Balance upstream and downstream demand and supply for all services Eliminate any backlogs of work Reduce the queues from one entity to another Develop contingency plans to address all variation Reduce demand Identify and manage each supply constraint Synchronize the work Predict and anticipate needs Optimize the environment: equipment, staff and space
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Change ideas Each step (node) needs to be optimized The interface between steps needs to be optimized Focus on the “system” flow constraint either between or within the steps Constraints will shift
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