Domain

Healthcare Data & Clinical Automation

Platform

AI-Driven Diagnostic Platform

Services

  • Clinical Workflow Modeling Digitization
  • Structured Assessment Engine Development
  • AI-Based Clinical Report Generation
  • Offline-First Sync Architecture Engineering
  • HL7/FHIR-Ready API Data Architecture

Overview

A leading diagnostic provider in South Florida set out to modernize its digital swallowing assessment workflow—traditionally driven by paper forms, manual scoring, and time-consuming report creation. Dash Technologies partnered with the organization to design a clinician-friendly, AI-enabled platform that supports assessment scheduling, structured digital forms, offline functionality, and automated clinical reporting powered by ChatGPT.

The result is a cross-device diagnostic software (Windows executable + tablet app) that functions as an offline-enabled healthcare app, streamlining assessments end-to-end, improving documentation quality, and establishing a modern foundation ready for EHR/FHIR interoperability.

About the Client 

A South Florida–based dysphagia evaluation provider offering portable diagnostic services and office-based assessments, including MBSS and FEES. As a mobile healthcare diagnostics organization, they support multiple facilities and a large geriatric population with timely, on-site evaluations to reduce aspiration risks.

A fragmented, paper-driven dysphagia workflow was re-engineered into a structured, AI-operable clinical system.

Business Challenges

The client needed to modernize a paper-heavy, multi-facility workflow that slowed clinicians, limited scalability, and created documentation inconsistencies across mobile diagnostic teams.

  • Manual, Paper-Based Assessments

    Slowed evaluations and created inconsistent clinical documentation.

  • Lengthy, Manual Report Writing

    Clinicians spent excessive time converting notes into structured reports.

  • Disconnected Scheduling & Patient Records

    Lack of a unified system led to duplication and operational delays across facilities.

  • No Offline or Cross-Device Support

    Connectivity issues and device limitations disrupted on-site assessments.

Offline-first architecture ensures uninterrupted diagnostics across mobile and low-connectivity environments.

Solution

Dash shaped the engagement as a structured, multi-phase journey—ensuring clinical accuracy, reliable offline performance, and seamless AI integration while building toward a scalable diagnostic platform. Each phase delivered tangible value for clinicians and set the foundation for long-term interoperability.
Phase 1 - Discovery, UX Mapping & Technical Architecture

Objectives

Clarify real-world clinical workflows, digitize paper assessments without disrupting practice patterns, and establish a FHIR-ready software design for an offline-capable, cross-device platform.

Key Workstreams

  • Mapped MBSS/FEES workflows, including assessment phases, consistencies, and PAS scoring.
  • Converted paper-based templates into structured digital schemas aligned with clinician terminology.
  • Conducted iterative UX prototyping sessions to deliver a clinician-first UX design optimized for tablets and Windows environments.
  • Defined an interoperable healthcare architecture supporting offline operation and future EHR/FHIR integration.

Technical Decisions & Rationale

  • Flutter Web: Single codebase packaged as a Windows executable and tablet-ready app.
  • Auth0 RBAC: Ensured robust identity, session control, and role permissions across mobile teams.
  • Offline-first design: Local caching, conflict handling, and background synchronization.
  • Structured assessment architecture: JSON-driven forms allow rapid configuration and future scale.

Outcome

  • A clinically intuitive, offline-capable framework that mirrors real-world assessment flow while preparing the platform for advanced automation.
Phase 2 - Core Feature Build, AI Reporting & Workflow Automation

Objectives

Build the operational backbone of the platform—scheduling, assessments, patient records—and introduce AI-powered clinical report generation using ChatGPT.

Key Workstreams

  • Developed a centralized, multi-facility scheduling system supporting clinicians, facilities, and mobile teams.
  • Engineered a structured assessment engine to capture phases, consistencies, scoring, and clinical observations.
  • Integrated ChatGPT clinical reporting to convert structured inputs into polished, standardized reports.
  • Implemented PDF export and SMTP-based secure email delivery for rapid report sharing.
  • Added dashboards, notifications, and audit logs for operational oversight.

Technical Foundations

  • AI integration pattern: Structured data → clinical prompt → ChatGPT → templated report → PDF.
  • Backend logic: PHP service orchestration, message queues, and standardized reporting templates for consistency.
  • Auditability: Each assessment step logged for traceability and compliance.

Outcome

  • Clinicians’ complete assessments digitally and generate standardized reports in minutes—dramatically reducing administrative burden through automated dysphagia reporting.
Phase 3 - Deployment, Optimization & Scale Enablement

Objectives

Ensure seamless adoption in field environments, optimize performance for on-site diagnostics, and prepare the platform for future integrations.

Key Workstreams

  • Packaged the Flutter Web application as Windows diagnostic software, optimized for tablet use.
  • Ran performance tuning on offline sync cycles, file handling, and load times in low-connectivity conditions.
  • Delivered clinician training and support workflows to ensure rapid adoption.
  • Implemented data archival, enhanced caching, and improved routing logic for multi-facility scheduling.

Technical Enhancements

  • Sync optimization: Reduced conflicts and improved background reconciliation times.
  • PWA techniques: Faster startup, caching strategies, and smoother offline transitions.
  • Scalability improvements: Prepared APIs for HL7/FHIR modules in future phases.

Outcome

  • A production-ready, clinician-tested platform deployed across devices—capable of supporting high-volume assessments with consistent performance and room to scale.

FHIR-ready foundations were built early, avoiding costly rework as interoperability requirements evolve.

Business Impact

Estimated outcomes based on workflow analysis and field feedback:

  • 50% estimated reduction in reporting time with AI-driven clinical report generation

  • 45% improvement in assessment turnaround, particularly across mobile teams and multi-facility schedules.

  • Zero paper dependency, eliminating manual errors, and lost documentation.

  • Higher clinician satisfaction due to intuitive UX and dramatically reduced administrative workload.

  • Improved data consistency from structured, standardized assessments.

  • Immediate scalability, allowing the organization to expand to new facilities with minimal onboarding.

The Dash Difference

Deep healthcare & MedTech expertise ensures accurate mapping of complex swallowing assessment workflows.
HL7/FHIR-ready architecture future-proofed the platform for EHR integrations.
Clinician-first UX reduced friction and supported immediate adoption.
AI-driven workflow automation cut reporting effort dramatically.
Offline-first engineering ensures reliability in low-connectivity environments.
Secure, modern infrastructure with Auth0, audit logs, and role-based permissions.
Agile, collaborative delivery enables rapid prototyping, testing, and refinement.
End-to-end ownership from discovery to deployment ensures continuity and quality

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