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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
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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
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
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