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Mobile Wireless EMS: Case Study on Network and Service Growth

Mobile Wireless EMS: Case Study on Network and Service Growth. Thomas A. Horan, Ph.D. Associate Professor Claremont Graduate University Visiting Scholar Humphrey Institute University of Minnesota. Study Objectives.

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Mobile Wireless EMS: Case Study on Network and Service Growth

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  1. Mobile Wireless EMS: Case Study on Network and Service Growth Thomas A. Horan, Ph.D. Associate Professor Claremont Graduate University Visiting Scholar Humphrey Institute University of Minnesota

  2. Study Objectives • Investigate the relationship between technical and institutional constraints to seamless inter-organizational performance on wireless EMS services • Devise an architecture for considering policy and market actions • Consider as case example for adaptive technological system

  3. Methodology and Tasks • Embedded Case Study of MN EMS System • Devising Architecture for Assessing Rural EMS Services • Conducting Case Studies in Minnesota and Benchmarking to Other Localities • Devising Knowledge Acquisition System to Track Development • Analyzing Relative to Principles of Adaptive Systems

  4. Nature of Systems Growth

  5. Emergence of New Service Form

  6. Emergency Medical Services: Time Drivers • Over 40,000 highway deaths each year Most deaths occur within few hours of crash • 30% of deaths occur within minutes of crash - Mayday systems • 50% of deaths occur prior to arrival at a hospital - Computer aided dispatch and, providing pre-arrival data • 70% of deaths occur within 2 hours of crash • Automatic Crash Notification (provide pre-arrival data to responders) (source Comcare Alliance)

  7. And What is That Service and Linkages Therein? Primary Call Center: ARTIC/TOCC -Verify Emergency -Exact Location -Screen for Duplication -Call-back Number -Make & Model of Vehicle MSP

  8. A Nested Complex System LAYERS • Communication • Transportation • Institutional

  9. The Case: Northeast Rural Minnesota • Large Predominately Rural Region • Significant Weather Variations • Mix of Travelers (Commercial, Recreational, Local)

  10. Most crashes are rural 54% of all crashes 56% of injuries 87% of fatalities Winter Snow, icy roads & bridges Stranded motorists Spring Flooding Fishing opener Work zones Summer Work zones Large events (sports/concerts) Weekend exodus to lakes Fog (Duluth) Fall Seasonal weather changes Grain hauling Hunting opener Work zones Rural Minnesota …“the local context”

  11. Life in “Greater” Minnesota

  12. Artic e-911 Technological Program • (Now),2002 (Then) 1995

  13. Case Study Findings • Technical • Recently implemented technology has reduced response times and increased agency efficiency • Technology for effective and efficient system exists • CAD is being used by PSAPs, will be used by TOCCs • GPS and wireless data works (MDT’s and comm ct., fleet location) • Cell phone coverage area is inadequate • Coverage exists along main highways but not along many of the more “rural” highways

  14. Case Study Findings • Technical • GPS and data transmission is cost prohibitive • Virginia TOCC discontinued Satellite service • However, wireless data and GPS still planned for State TOCCs • Software not yet ready for Transit collaboration

  15. A Minor Adaptation….

  16. Case Study Findings • Organizational • MnDOT and MSP established successful cooperative partnership • Created efficiencies through sharing resources (cut costs) • Reduced incident response times • A need for further interorganizational cooperation and consistency • Rural EMS necessitates partnerships and these may vary in nature and degree of success.

  17. Case Study Findings • Policy • MNDOT drive to statewide deployment of TOCCs (9 centers, $30 million) will drive system from supply perspective. • Linkages Should Exist to Telecommunications Policy that will help ensure adequate coverage and scalability? • New Centers provide policy opportunity to develop customer centric services in rural areas.

  18. Thief River Falls Virginia Detroit Lakes Baxter Duluth St. Cloud Marshall Rochester Mankato TOCC DeploymentTransportation Operation Communications Centers • Nine CommCenters • MSP / DOT / Transit • Day-to-day operations / dispatch • related to incident management • response and coordination

  19. Toward Adaptive Systems Framework:Use of Knowledge Acquisitions Software

  20. Linking to Complex Systems Principals • Dis-equilibrium is the norm • Comment: EMS Systems are highly unstable”hours of boredom interrupted by minutes of terror” • Agents drive process • How travelers behave on the system is fundamental to the performance; it is very demand driven and spontaneous.

  21. Linking to Complex Systems Principals • Complex process affected by small change • A relatively minor incident (fire, stalled car) can ripple into a major EMS situation. • Complex systems resist reductionism • Need to understand EMS within context of 911, rural transportation needs and organizational (especially State Patrol) partners

  22. Linking to Complex Systems Principals • Patterns are emergent from simple rules • Quick response commitment drives service • Systems exhibit self organizing characteristics • There may be many partnerships possible for rural transportation services, including EMS

  23. Preliminary Management Implications • Planning: Linkages Between Technical Availability ( Coverage Gaps) and Service Growth • Services: Call-in use from travelers may facilitate de facto transportation customer service. • Management: Emergent Partnerships Facilitate inter-organizational collaboration and culture with State Patrol, Health Care Providers and PSAPS

  24. Works in Progress • Horan, T. Bringing the Consumer to Infrastructure Management, 2002 (IRMA) • Horan, T, and Schooley, B. Interorganizational Information Systems Frontiers, 2002 (under review) • Horan, T., Schooley, B. and Dadabayeva, N., Case Study of Wireless EMS in Small Town and Rural Environments, TRB Meeting, 2003 (Accepted) • Horan, T. and Sparrow, R. Management Issues in Information Technology for Infrastructure Management, 2002 (Routledge, 2003)

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