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

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