1. Principles for Flow Improvement #1: Understand, measure and achieve a balance between upstream and downstream demand

2. Basic Dynamic Door to doctor time Decision to admit to admit Ready to Tx to tx Decision to Dx to dx Length of Stay

3. System demand Look at all the streams of demand (all the kinds of work) into each step Different demand streams will have different units of measure Demand = volume of demand X LOS (time)+parking Look at the variation (volume, arrivals and handling time) of demand in each stream Look at the supply set aside against each demand stream both within the step and between demand streams (allocation) Supply is time of various converging components Measure the variation of supply Compare demand to all the supply- all lines need to balance

4. Measurement for Each Step Demand: Volume External/internal Who Where What Variation/range in volume, in arrivals and in handling time D= Volume X LOS (time) Supply: Volume Competing venues Variation/range Volume X Time Converging components Delay: How long Variation in delays

5. Metrics at each step Input Throughput Output Output for one step is input for the next step

9. Delay for the step: input In some steps, demand= arrivals so there is no delay (for ED) Between and within other steps, there is a delay (from ED to floor)

10. Delay within the step (throughput) ED cycle time Door to doctor time Each floor or service LOS Decision to discharge to discharge wasted capacity (defect) Throughput for a specific patient stream (CHF)

11. ED Hospital LOS Door To Doctor Time Length of Stay in ED Decision to Admit to Admission Lead Time in ED Cycle 1 Cycle 2 Cycle 3

12. ED Hospital LOS Admit Process Days in Hospital Decision to Discharge to Discharge Cycle 1Cycle 2Cycle 3 Day 1 Day 2Day 3

13. ED Lead time

15. LOS From 7/1/05 to 6/30/06 Top 10 DRG’s/specialty Calculated from Days > Benchmark TIMES volume Sum = 850 days/year

16. Within the step (throughput) Measures Length of Stay Diagnostic admission Time from presentation to w/u complete Time from order for diagnostic test to information Treatment admission Time from admission to treatment complete Time from arrival for pneumonia to first antibiotic start

17. Delay after the step: Output Measures Output for one step is input for the next ED: Decision to discharge to admit Flow: Decision to discharge to discharge

18. Delay after the step (output) ED decision to admit to admit Transfers or direct admits decision to admit to admit Each floor or service decision to discharge to discharge discharge appointment measures

19. Demand Measures

20. Emergency Department Demand 60 To 80

21. Emergency Department 60 To 80 Variation from 1 to 5 per hour Peak is at 6 PM

22. Emergency Department Hospital Demand FOR ED Demand FOR Hospital Eight to Ten Percent are Admitted

23. 0.4 to 0.6 Per hour From Noon To Midnight Emergency Department Hospital Demand FOR Hospital

24. Admit Pattern Within the Day

25. Scorecard of Key System Measures: Outcomes How well we match demand to supply (velocity) Bed turns Adjusted bed turns Potential bed turns Utilization LOS (throughput) LWBS and diversions (defects)

28. #2: Eliminate any backlogs of work Initial step into ED has no BL but all other steps have a BL (delayed workload) Stabilize the wait, then eliminate BL To stabilize the wait, reduce the variation Eliminating BL may move the workload and the wait time deeper into the system Use standard BL reduction strategies

29. #3: Reduce the queues from one entity to another Workload channeled into more and narrower queues increases the risk of adversity due to variation “Priority” is often a euphemism for more queues Priority  variation Segment/route for “different” queues Segment in front of the constraint, not beyond 

30. Reduce the Queues Concept: Bank and Grocery Store Are these appropriate queues? 1 line for each phlebotomist? “In-patients first” in Imaging? Preadmission unit? Discharge lounge? Separate OR for emergencies? “Fast Track” in ED?

31. Lab (Wait Time min) Banker’s Queue Implemented

32. #4: Develop contingency plans to manage variation Measure the variation Determine common from special cause Have a plan Use a tool or two

33. Variation Within Day Between Day

34. Measure Approach: Variation Natural/Unplanned Run Chart Statistical Process Control Queuing Formulas Artificial/Planned Run Chart Statistical Process Control Modeling

35. Tools and Theories to manage variation UK formula: low demand +80% of the variation Erlang’s formula Standard queuing models Demand-Capacity Tool

36. Wait Time Variability Compared to D/S ratio Demand /

37. Supply variation in surgery: the 5 Why's Bolus of elective admissions with a delay Surgeon(s) worked in clinic a lot Surgeon catching up after being away Had to catch up/make up “on call” first Generated immediate surgery Had to do operations now and did before leaving Call and surgery can’t wait Clinic waits Surgeon(s) does not fill block time Loses block time Back to office Generates workload and bolus

38. #5: Reduce demand Some volume of demand can be reduced by correct routing ( error proofing) Impact of volume of demand can be reduced by Service Agreements Demand can be reduced by reduction of LOS

39. Admit the Right Patients

40. Other way to Decrease Demand Increase reliability: Take on Clinical Care VA ICU Collaborative Increase safety and reliability Decrease those patients off service: One study shows mortality increases 25% for patients “off service”. Hospital within a hospital

41. Hospitalist Hospitalist Change And Joint N-P Rounds Yearly savings estimated at 300 bed-days of care!

42. Decreasing Demand by Shortening LOS Have a senior clinician review each admission critically to have a clear workup or treatment plan and timeline Multidisciplinary Rounds Daily Round twice a day Rounds checklist Plan discharge at time of admit Eliminate waits for any ancillary services

43. #6: Increase supply If there is a D- S mismatch, then add supply- permanently or temporarily with flex Can “add” supply by subtraction TOC: identify supply constraint in entire flow and at each step in the flow and take away the “unnecessary” workload

44. Supply Components Patient Provider of care Staff Beds Information Equipment Supplies

45. Increase Supply Link admissions to discharges Do a “wasted inpatient bed” study Snapshot measure Physically confront each bed Note if bed empty of full Note reason for empty bed Tabulate % of time bed wasted Track over time

46. Reasons for Inpatient Bed Not in Productive Use Reasons for Unused Bed# 1. Pt. receiving care (elsewhere) (OK) 2. Pt. in discharge process (OK) 3. Pt. disch complete, waiting to go 4. Bed needs to be cleaned 5. Bed held for surgical 6. Bed held for admission/transfer 7. Bed contains a body 8. Bed out of service (why?) 9. Bed empty. No demand today

47. One Hospital Results Hospital had high turns and high utilization Looked closer at capacity Found 25% of capacity was “wasted” (bottom 7 of 9 reasons on study) Most common reason pt. waiting to go home Second: Bed waiting to be cleaned Third: Held for surgical

48. Identify the System Constraint The constraint is the rate limiting step Can only go as fast as slowest step or the slowest step within the step Any step or service that is 100% full to capacity will be the constraint This is the last place where there is a system delay This is where there is a demand–supply mismatch and a delay Take work away from the constraint Balance at the constraint (may have to reduce demand, increase supply or improve the process delay) The constraint shifts

49. Potential Constraints Dependent on the specific patient flow map Rate limiting step in that specific flow Last place where there is a significant delay Examples: surgery, test/procedure, ICU, hospital bed, office appointment, ED The constraint moves

50. Example: Surgery OR

51. Supply at Surgery A.Surgeon B.Room C.Equipment D.Technician E.Anesthesiologist F.Hospital Bed A B C D E F D S Harmonic convergence of components

52. Surgeon as Constraint Value stream for customer Competing venues for surgeon/dilution Decision about venues Limit the demand/enhance the supply at each competing venue

53. OR Itself Hours of operation OR utilization during those hours Percent utilization Block time Industrial models (85%) Downstream constraint (bed) may make OR appear to be the constraint or increase wait to OR

54. Big System Flow/Cancer Test SC Surgery Discharge External Demand PC Bed MDT Oncology Radiation Chemo Follow up Test Follow up Internal Demand Test MDT

55. C 1-7 day variable wait

56. Findings The constraint was not surgery The octanes at SC office were very poor creating an office anti-dilutional effect Surgeon not in the OR Long wait for surgery OR’s open MDT caused 2 delays

57. Changes Used principles Changed MDT ( false demand + timing) Looked at value: Surgery Moved surgeons to the OR Identified constraint (front door) Changed octanes Initial/total Surgery/initial Created linkage

58. Other Potential Constraints ED (wait time to get out, wait time to get in) ICU ( wait time to get in, wait time to get out) Beds ( wait time to get in, wait time to get out) Dependencies Discharge venues ( wait time to get in)

59. #7: Synchronization of all supply components to the demand

60. Synchronize the Work What is synchronization? “Gap” between possible and actual time of occurrence of: Admission- Tests Discharge- Procedure Rounds- Operation Medicine Passes

61. Increase Supply Story of Freddie Problem: “Discharge by 11 is absurd. It assumes everyone is out there with their nose pressed to the glass wanting to come in at 11, which is absurd.” - IHI Faculty

62. VA FY ’05 # Admits/Discharges by Time of Day

64. Multidisciplinary Rounds: Where?

65. Multidisciplinary Rounds Outcomes Reduced mortality Improve clinical care Vent days, infections, readmits, decubiti ulcers, prevent DVT, Improved Efficiency Reduced length of stay/increase throughput Increase patient/staff satisfaction

66. Daily Goals Sheet MTWTHFSa Pain? Test/Proc? Activity? Med Chg? Lines/tube s? Spiritual? Nutrition? Disch Plans?

67. #8: Predict and anticipate needs Communication strategies Command Center Philosophy Tools/Information System Allows view of workload flow retrospectively and in real time Allows for a required interventions Czar or Czarina

68. Flow system scorecard Retrospective data Monitors ongoing performance Can be converted to run charts and SPC graphs Explicit focus on delay: input, throughput and output Additional focus on matching and velocity measures

71. Predicted Orthopedics Demand Common and Special Cause Variation BY DAY (Tuesday)

72. Demand/Supply Tool

74. Key to D/S Tool: Interventions (Contingencies) Created by the front line team Exist for every single box/criteria Impact of intervention determined by escalating color criteria Thresholds for criteria set by SPC, common and special cause variation Have the same level of impact across all “departments” Continually updated and developed Allow a standard response to change in workloads Often result in “buddy” departments

77. #9: Optimize environment

78. Optimize the Environment Lean

79. Big system flow: special issues Linkages and formulas Intersections

80. Formula Demand for OR time = Supply of the OR time The delay is thus stabilized Patients per month x octane (surgical cases per 100 patients) = OR time per month/OR time per case Adjust by 85% (myth of 100% utilization)

81. Linkage or Ratio of Schedule C A 4 : 4 : 1 : 1

82. Linkage of Ratios Why?

83. Work Backwards to Office Stabilize the wait time in the OR ( the constraint) Work backwards to the office Three variables: Days in office Appointment lengths/ types Octane

84. Octanes Initial(new):initial+return Returns : surgery Surgical cases:new(initial Surgical Yield Goals High Low High

85. Linkage Formula OR sessions/week X cases per OR session = Office sessions per week X appointments per session X octane (surgical yield) (adjusted to 85%)

86. Links surgery (ultimate value and constraint) to office that feeds the constraint Allows measurement and monitoring Allows earlier identification of problems

87. Linkage Surgery to office Procedure to office Test to office Bed to ED ICU to surgery Bed to ICU Other dependent services

88. Big System Flow/Intersections Test SC Surgery Discharge External Demand PC Bed MDT Oncology Radiation Chemo Follow up Test Follow up Internal Demand Test MDT

89. Intersections Radiation Oncology Demand External.internal Stratification into who, what, where in each stream Variation within each stream Supply What is the constraint Machine Technician Physician Process Delay For all competing components Decisions Who goes first

90. Intersections Intersections of demand streams are common Demand is competing The competitors are blind Demand and supply are matched but what is the model? How are decisions made What is the true constraint

91. Lesson 1 Value stream Delay is key We must measure demand and variation at each step Do not confuse activity with demand Variation creates queues Do not use averages Constraints governs the speed

92. Lesson 2 Aiming for 100% utilization and setting the supply at average demand will result in waits and a waiting list Set supply at minimum demand + 80% of the variation

93. Lesson 3 Demand/supply Use principles at each step The system is linked Carve-outs worsen system performance Extra capacity comes from process redesign May have to increase actual resource but only after measurement We may solve a problem but if it is not the right problem we just move the wait

94. High Leverage Changes at 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

95. Ten Flow Rules 1) Follow the customer (patient). 2) The goal is to eliminate all wait and delay. 3) The patient ’ s journey through the system is often complex but at its core is a series of value steps interspersed with long waits. 4) Each step is a demand-supply matching step. 5) The perspective of the customer (demand) is different than the perspective of the supply (resource) : the patient experiences a series of waits while the resource sees single isolated waits. 6) Queues (wait times) result from: a) demand-supply mismatch which has to be solved by reducing demand or enhancing supply b) queues are formed by system design which requires redesign, or c) queues are formed by variation which needs to be measured and addressed 7) Measurement of demand, supply, activity, wait time and variation in demand and supply at each step is crucial 8) Involve all staff in measurement at each step. 9) Look at steps beyond the constraint to improve flow. 10) There are a set of principles that, if applied appropriately at each step, will reduce the waits.