SMART Emergency Medical and First Response Multiteam Systems

SMART Emergency Medical and First Response Multiteam Systems
SMART Emergency Medical
Team Organizations	Fairfax Fire & Rescue Inova Fairfax Hospital George Mason University Inflow Interactive Newport News VA ASC Consulting USPHS
Team Leaders	Brenda Bannan Hemant Purohit Jeff Segall
Participating Municipalities	FairFax County VA
Status	Launched
Document	None

Description

SMART Emergency Medical Teams will help inter-disciplinary teams improve transition-of-care quality, promote situational awareness, and enhance the efficacy of simulation debriefing.

• Simulation-based Team Training in medical contexts
• Patient hand-off or transitions between sub-teams
• Interaction among interdisciplinary roles/team
• Wearable sensors
• Enhanced debrief –visualization/display/feedback
• Collaborative reflection, situation awareness and experiential learning

Challenges

• Instrumentation of IoT sensors for data capture, validation
• Synchronous integration of sensors, video, audio and medical simulation device data to usable instructor interface
• Blended analytics/visualizations of proximity and performance data: Data extract-transform-load (ETL) from source systems

Major Requirements

• Build network of design and implementation expertise from diverse fields
• Define use case from different medical teams’ perspectives, surface and facilitate common goals: Successful 2015 GCC project/tools as baseline
• Minimum viable product (MVP) performance support tools to enable provider capabilities - in context
• Data-driven learning designs to support evidence-based medicine

Performance Targets

Key Performance Indicators (KPIs)	Measurement Methods
Improve systemic transition-of-care performance measures 10% via time-based analytics and video observation Promote individual and team-based situational awareness of EMS and ED teams Reduce preparation time 20% via instructor’s scenario app and improve efficacy and quality of medical team debriefings	Instructor’s design app and field checklist time-stamped Existing system metrics (EHR’, PCR, 911), plus IoT sensor and performance support data streams Data collection – time, location, behavior Pre/post assessment of team debrief – without/with enhanced visualization of real time data Augment with qualitative assessments of debriefing of medical intra-team and inter-team (cross) trainings

Standards, Replicability, Scalability, and Sustainability

• xAPI (Experience API) experiential learning data standards from international Advanced Distributed Learning (ADL) specifications for REST API and data storage
• FHIR medical data interoperability standards from international HL7 specifications for REST API and data storage
• Standardized emergency medical procedures are not unique to cities or regions. The SMART analytics model can be replicated across localities, and data gathered cost-effectively via a cloud-based SAAS system.
• The system will initially rely on support from major partners and grant funding. As adoption grows, the system will develop its own member subscription model to enable ongoing development and support.

Impacts

• Baseline for improving emergency medical system-wide performance
• Directly impacts performance of mobile first responders, disaster recovery teams, hospital based teams
• Long-term benefits to citizens in distress, local and national governments, medical providers and payers
• Advances in simulation debriefing may apply across multiple high-performance fields

Demonstration/Deployment

Phase I Pilot/Demonstration:

1. Intra-team focus
2. Rapid prototype pilot for select use case(s)
3. Refine metrics and data collection
4. Final demonstration, with visual analytics

Phase II Deployment:

1. Stakeholder approvals
2. Select test cohort(s), simulation scenarios
3. Intra- and Inter-team focus
4. Implement test deployment, measure, report