How a Prehospital SDOH Platform Reduced ER Visits by 67% by Turning Social Health Data into Clinical Action

An EMS-focused clinical platform needed social and environmental data captured at every encounter and put in front of practitioners. We built the full platform in eight months. It now runs in production across a multi-company EMS network.

Walk Through the Architecture
Customer Focus

EMS providers and payers running prehospital care across a multi-company network.

Scope

Full platform: three-tier hierarchy, Super Admin dashboard, Patient Snapshot, scheduling with reminders, partner API layer.

Stack

Survey APIs, multi-tenant access control, appointment scheduling, automated reminders, external partner APIs, patient data management.

Status

Live in production across a multi-company EMS and payer network. Built in eight months.

Outcomes

Social context that reaches the encounter

For enrolled patient populations, ER visits fell 67%. SDOH data collection is now standardized across the practitioner network through one survey system.

67%

reduction in ER visits for enrolled patient populations

8

months from build start to live production across a multi-company EMS network

3

access tiers, Super Admin, Company Admin and Practitioner, with per-organization data boundaries

The Problem

Prehospital records capture what happened, not why

EMS providers and payers knew social conditions drive repeat emergencies. They had no platform to collect SDOH data at every encounter and put it in front of practitioners in a workflow that fits how EMS care is delivered.

01
No tool captured the social context

A respiratory distress call gets symptoms, vitals and treatment on the record. The housing situation, the mold exposure and the weeks of environmental triggers before the call do not, so the pattern repeats at the next encounter.

02
SDOH data resists normalization

Social, economic and environmental factors vary by patient, by geography and by the factor being measured. The survey system had to absorb that variation and stay usable for practitioners in the field.

03
Many companies on one shared platform

Each EMS organization has its own practitioner roster, administrative settings and patient data. Access controls had to keep every organization's records separated on shared infrastructure.

04
Risk arrives in combinations

Housing instability, substance use, environmental exposure and employment status often appear together. Their clinical significance is not the sum of each flag, so single-variable thresholds either miss real alerts or fire false ones.

What We Built

Data model first, practitioner tools second, integrations third

A three-tier hierarchy with boundaries set in the data model

We built the organizational structure first: Super Admin, Company Admin and Practitioner. Each tier sees what its role needs and nothing outside it. The hard part was the boundary between Company Admin and Super Admin access, where an organization's data ends and the platform's aggregate view begins. We defined those boundaries in the data model so they cannot drift as new companies join.

  • Super Admins manage every organization and see aggregate performance metrics
  • Company Admins manage practitioners and settings inside their own organization only
  • Practitioners run surveys, collect SDOH data, document encounters and track patient progress
  • Adding an organization or practitioner never expands access beyond its authorized scope

Building a population health or EMS platform where SDOH data has to drive clinical workflows?

We can walk you through how the survey data model connects to the practitioner workflow and the external analytics integrations.

Walk Through the Architecture

Let’s #Transform Healthcare,# Together.

Partner with us to design, build, and scale digital solutions that drive better outcomes.

Location

Global Tech Teams LLC, 525 Washington Blvd, Industrious at Newport Tower, Jersey City, NJ 07310, United States.

Contact

+1 408 786 5974
contact@mindbowser.com
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