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   Production Model Science & Theory Applied
    to a Service Industry
   Enables Balancing of Patient Care, Employee
    Wellbeing & Financial Stability in a Poor
    Economic Environment
   Production Model EMS Theory:
     Service Demands ARE Predictable
      ▪ Temporal (When is the Demand - Time of Day and Day
        of Week)
      ▪ Geospatial (Where is the Demand)
   Our “Product / Widget” is a Unit Hour
     Ambulance Available for One Hour
      ▪ Medical Staff
      ▪ Vehicles
      ▪ Supplies / Hardware
      ▪ Support Systems
      ▪ Administration
   Supply our Unit Hours Using Peak-Load
    Staffing to Meet Temporal Demand Curves
    Based on a Service Reliability Standard / Goal
Saturday Staffing Vs. Demand


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     0:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:0011:0012:0013:0014:0015:0016:0017:0018:0019:0020:0021:0022:0023:00

                            All Calls     Staffing june 07   New Bid w/o downtime      New Bid w downtime
   Efficiency & Effectiveness Drives Throughput
     Driven by Task Time / Call Segment Timeliness
      ▪   Call Processing Times
      ▪   Response Times
      ▪   On Scene Times
      ▪   Transport Times
      ▪   At Destination Times
     The Longer it Takes to Run an EMS Call The More
      Resources You Need to Meet a Service Reliability Standard
     The Shorter it Takes to Run an EMS Call the Less Resources
      You Need to Meet a Service Reliability Standard
   All Functions Performed Under a “Command &
    Control” Structure using “Push Engineering” vs
    “Pull Engineering”
     Controllers (Dispatchers) Make Key Process Decisions
      Regarding Resource Allocation and Usage and Collect
      Key Data for Metrics and Benchmarking
     Information Systems Used to Gauge Performance in
      Real Time
     Clinicians Make All Clinical and Pathway Decisions
     Very Different then Fire or PD Model (Location of
      Command & Control)
   Data Collected is Used to Improve Efficiency
    and Effectiveness for ALL Processes and Sub-
    Processes in the System and is “Re-assessed”
    Every 6 Months in Order to Adapt to Changes
    in Demand or Improvements in Efficiency
     Supply Chain Adjustments
      ▪ Temporal
      ▪ Geospatial
 Strong Similarities in Most Key Areas
 Strong Evidence That ER Demand is Predictable and
  Follows EMS Demand Curves
 Allows us to Hypothesize That Other Patient Service
  Demands are Also Predictable Based on ER Demand
  Patterns and Admitted Patient Census :
       Lab
       X-Ray / CT
       Consulting Medical Groups
       Food Services
       Housekeeping
 Substantial “Push” Based System Design Improvement
  Opportunities
 No Command & Control / Processes Siloed
   Patient Clinical Pathway Dictates Approach:
       ER Walk In/EMS Admission: Discharged from ED
       ER Walk In/EMS Admission: Admitted
       ED / Direct Patient Transfer: Admitted
       ED Patient Transfer: Discharged
   Pathway Processes
     Before Admission (Registration / ER)
        ▪ Highly Contained & Limited Span of Control
        ▪ Minimal Silo Effect
     After Admission (Admissions / Floor / Unit)
        ▪ Poorly Contained & Large Span of Control
        ▪ Substantial Silo Effect
   Before Admission Processes
       Triage
       Registration
       Waiting Queue
       Room Assignment
       Primary Assessment RN
       Primary Assessment MD / PA
       Testing
       Treatment
       Reassessment (More Treatment / Testing Possible)
       Disposition Decision (Discharge / Admit)
       Discharge Patient
   After Admission Processes
       Room Status / Availability / Cleanliness
       RN Report ED to Floor
       Patient Transport
       RN Assessment
       MD Assessment
       Orders
       Testing
       Nutrition
       Other Ancillary Services (Medical & Customer Service)
       Reassessment (MD / RN)
       Disposition Decision (Stay, Transfer, Discharge)
       Discharge Patient
   Adoptable Best Practices
       Setting Service Reliability Standards
       Temporal Demand Analysis
       Peak Load Staffing
       Centralized Command & Control
       Centralized Data Collection & Analysis
       Real-time System Reactivity
       Bi-annual Adjustments to Demand / Efficiency
       “Push Based” Systems Engineering of Practices
       Utilizing APL vs AVL Systems
   Benefits
     Dramatically Improved Throughput Using Same or
      Less Staffing
     Improved Customer Satisfaction
     Efficient and Effective Delivery of Care
     Improved Margins via Cost
      Reductions, Capitalizing on Lost Opportunity
      Revenue & Revenue Improvement Through
      Increased Patient Volumes
   Pitfalls
     Significant Change
     MD / RN Rejections of:
      ▪ Schedules
      ▪ Command & Control
      ▪ Perceived Loss of Control
     Must be Combined With Clinical Standards That
      Balance Competing Interests
     Capital Layouts
      ▪ Software & Hardware Must Be Created / Modified / Adapted
      ▪ Physical Plant Changes / Updates May be Necessary

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High Performance EMS Concepts for Healthcare 2008

  • 1.
  • 2. Production Model Science & Theory Applied to a Service Industry  Enables Balancing of Patient Care, Employee Wellbeing & Financial Stability in a Poor Economic Environment  Production Model EMS Theory:  Service Demands ARE Predictable ▪ Temporal (When is the Demand - Time of Day and Day of Week) ▪ Geospatial (Where is the Demand)
  • 3. Our “Product / Widget” is a Unit Hour  Ambulance Available for One Hour ▪ Medical Staff ▪ Vehicles ▪ Supplies / Hardware ▪ Support Systems ▪ Administration  Supply our Unit Hours Using Peak-Load Staffing to Meet Temporal Demand Curves Based on a Service Reliability Standard / Goal
  • 4. Saturday Staffing Vs. Demand 26 24 22 20 18 16 14 12 10 8 6 4 2 0 0:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:0011:0012:0013:0014:0015:0016:0017:0018:0019:0020:0021:0022:0023:00 All Calls Staffing june 07 New Bid w/o downtime New Bid w downtime
  • 5. Efficiency & Effectiveness Drives Throughput  Driven by Task Time / Call Segment Timeliness ▪ Call Processing Times ▪ Response Times ▪ On Scene Times ▪ Transport Times ▪ At Destination Times  The Longer it Takes to Run an EMS Call The More Resources You Need to Meet a Service Reliability Standard  The Shorter it Takes to Run an EMS Call the Less Resources You Need to Meet a Service Reliability Standard
  • 6. All Functions Performed Under a “Command & Control” Structure using “Push Engineering” vs “Pull Engineering”  Controllers (Dispatchers) Make Key Process Decisions Regarding Resource Allocation and Usage and Collect Key Data for Metrics and Benchmarking  Information Systems Used to Gauge Performance in Real Time  Clinicians Make All Clinical and Pathway Decisions  Very Different then Fire or PD Model (Location of Command & Control)
  • 7. Data Collected is Used to Improve Efficiency and Effectiveness for ALL Processes and Sub- Processes in the System and is “Re-assessed” Every 6 Months in Order to Adapt to Changes in Demand or Improvements in Efficiency  Supply Chain Adjustments ▪ Temporal ▪ Geospatial
  • 8.  Strong Similarities in Most Key Areas  Strong Evidence That ER Demand is Predictable and Follows EMS Demand Curves  Allows us to Hypothesize That Other Patient Service Demands are Also Predictable Based on ER Demand Patterns and Admitted Patient Census :  Lab  X-Ray / CT  Consulting Medical Groups  Food Services  Housekeeping  Substantial “Push” Based System Design Improvement Opportunities  No Command & Control / Processes Siloed
  • 9. Patient Clinical Pathway Dictates Approach:  ER Walk In/EMS Admission: Discharged from ED  ER Walk In/EMS Admission: Admitted  ED / Direct Patient Transfer: Admitted  ED Patient Transfer: Discharged  Pathway Processes  Before Admission (Registration / ER) ▪ Highly Contained & Limited Span of Control ▪ Minimal Silo Effect  After Admission (Admissions / Floor / Unit) ▪ Poorly Contained & Large Span of Control ▪ Substantial Silo Effect
  • 10. Before Admission Processes  Triage  Registration  Waiting Queue  Room Assignment  Primary Assessment RN  Primary Assessment MD / PA  Testing  Treatment  Reassessment (More Treatment / Testing Possible)  Disposition Decision (Discharge / Admit)  Discharge Patient
  • 11. After Admission Processes  Room Status / Availability / Cleanliness  RN Report ED to Floor  Patient Transport  RN Assessment  MD Assessment  Orders  Testing  Nutrition  Other Ancillary Services (Medical & Customer Service)  Reassessment (MD / RN)  Disposition Decision (Stay, Transfer, Discharge)  Discharge Patient
  • 12. Adoptable Best Practices  Setting Service Reliability Standards  Temporal Demand Analysis  Peak Load Staffing  Centralized Command & Control  Centralized Data Collection & Analysis  Real-time System Reactivity  Bi-annual Adjustments to Demand / Efficiency  “Push Based” Systems Engineering of Practices  Utilizing APL vs AVL Systems
  • 13. Benefits  Dramatically Improved Throughput Using Same or Less Staffing  Improved Customer Satisfaction  Efficient and Effective Delivery of Care  Improved Margins via Cost Reductions, Capitalizing on Lost Opportunity Revenue & Revenue Improvement Through Increased Patient Volumes
  • 14. Pitfalls  Significant Change  MD / RN Rejections of: ▪ Schedules ▪ Command & Control ▪ Perceived Loss of Control  Must be Combined With Clinical Standards That Balance Competing Interests  Capital Layouts ▪ Software & Hardware Must Be Created / Modified / Adapted ▪ Physical Plant Changes / Updates May be Necessary