biospatial is a data analytics platform that integrates electronic patient care reports from Emergency Medical Services (EMS) with various healthcare data sources using proprietary artificial intelligence to identify trends and improve decision-making. The platform provides actionable insights for public sector and commercial healthcare entities, addressing challenges in emergency response, patient outcomes, and healthcare resource allocation.
Funding
$710K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Emergency Medical Services (EMS) generate vast amounts of data in electronic patient care reports (ePCRs), but these records are often siloed and difficult to integrate with broader healthcare datasets. This lack of integration limits the ability to identify trends, benchmark performance, and derive actionable insights for improving emergency response and patient outcomes.
Solution
biospatial is a data analytics platform that integrates ePCRs from a network of EMS providers with other electronic healthcare data sources, leveraging proprietary AI to identify trends and improve decision-making. The platform provides actionable insights for public sector and commercial healthcare entities, addressing challenges in emergency response, patient outcomes, and healthcare resource allocation. biospatial enables users to discover patterns, detect anomalies, and probabilistically link data across sources, even when data is noisy or incomplete. The platform supports use cases such as state and national EMS trend analysis, EMS market intelligence, interfacility transfer analysis, biosurveillance, substance abuse and overdose trend tracking, automotive safety analysis, and disaster response and recovery.
Target Audience
biospatial's primary customers include state EMS agencies, federal government entities, hospital systems, and behavioral health organizations.
Features
- Integration of EMS ePCRs with other electronic healthcare data sources
- Proprietary AI algorithms for pattern recognition, classification, trend analysis, and anomaly detection
- Probabilistic linking across disparate data sources
- Clustering of noisy and incomplete EMS data
- Benchmarking of EMS performance at the state and national levels
- Market intelligence reports for the EMS industry
- Interfacility transfer analysis tools
- COVID-19 tracking capabilities for state and federal agencies
- Biosurveillance applications
- Substance abuse and overdose trend analysis
- Automotive safety analysis
- Disaster response and recovery support