DataFinch

Supergood | DataFinch API

Alex Klarfeld

Alex Klarfeld

— 6 min read
Supergood | DataFinch API

Programmatically access ABA therapy data collection, skill targets, behavior events, session notes, and reporting in DataFinch with a stable REST API. Supergood builds and operates production-grade, unofficial DataFinch integrations so your team can automate key clinical documentation and analytics pipelines without heavy custom engineering.

In plain English: DataFinch (best known for its Catalyst platform) is software used by ABA practices to plan programs, collect trial data, track behaviors, visualize progress, and produce clinical notes. With an unofficial API, you could sync learners and staff, create sessions, log trial and behavior data, retrieve target mastery status and graphs, and move structured records into your EHR or data warehouse automatically.

If you’re a different tech company integrating with DataFinch—say an EHR, scheduling tool, billing platform, BI dashboard, or outcomes analytics vendor—you can pull clinical data (learners, programs, targets, data points, behaviors, notes) and push operational context (rosters, schedules, session metadata) to unlock features like authorization-aware scheduling, automated progress note generation, centralized reporting, and real-time QA dashboards.

If you’re an ABA clinic, provider group, or outcomes analytics team, integrating your tech stack with DataFinch unlocks concrete data flows and features:

  • Pull: Learner profiles, program/target catalogs, target status and mastery criteria, trial/probe data points, behavior definitions and recorded events, session notes, graph summaries
  • Push: New/updated learners and staff from your HR/EHR, scheduled sessions, session metadata, standardized notes, target phase updates (with audit trails)
  • Build: Real-time progress dashboards, automated note authoring based on data collection, behavior incident monitoring and alerts, target recommendation engines driven by historical performance

What is DataFinch?

DataFinch provides ABA practice software centered on clinical data collection and oversight. Its flagship product (Catalyst) helps BCBAs and technicians run treatment programs, capture trial-level data, log behaviors, visualize progress, and produce documentation that supports supervision and payer requirements. Common workflows include configuring skill acquisition and behavior reduction programs, collecting trials/probes at the point of care, monitoring mastery status against criteria, and generating session notes and reports.

Core product areas include:

  • ABA Data Collection (skill acquisition programs, targets, trials/probes)
  • Behavior Tracking (definitions, events, intensity/duration, ABC notes)
  • Session Management and Notes (start/end times, activities, SOAP/encounter notes)
  • Progress Visualization and Reporting (graphs, mastery status, trend analytics)
  • Rosters and Permissions (learners, technicians, supervisors)

Common data entities:

  • Learners (clients/patients receiving ABA services)
  • Staff (technicians/RBTs, BCBAs/supervisors)
  • Programs (skill acquisition and behavior reduction)
  • Targets (individual skills with phases like Baseline, Acquisition, Maintenance)
  • Data Points (trial/probe results, prompt level, response correctness)
  • Behaviors (definitions, functions, severity scales)
  • Behavior Events (occurrences with timestamps, duration, intensity, ABC context)
  • Sessions (scheduled or ad hoc encounters with notes and activities)
  • Notes and Reports (SOAP, supervision notes, progress summaries)

The DataFinch Integration Challenge

Organizations rely on DataFinch daily, but turning portal-based ABA workflows into automated pipelines is hard:

  • Limited official API access: Many users report a lack of open, public APIs; exports and reporting often happen via portal pages or batch files
  • Portal-first data capture: Trial-level data, graphs, and behavior events live behind web UIs, making headless automation brittle without careful reverse engineering
  • Complex permissions: Role-based access (technicians vs supervisors) and learner assignment rules require careful session handling
  • Data granularity: Trial/probe records, prompt hierarchies, and mastery criteria must be preserved precisely for clinical integrity
  • Scheduling and EHR silos: Clinics frequently request tighter scheduling, authorization, and billing integrations to eliminate double entry

How Supergood Creates DataFinch APIs

Supergood reverse-engineers authenticated browser flows, batch interfaces, and network interactions to deliver a resilient API endpoint layer.

  • Handles username/password, SSO/OAuth, and MFA (SMS, email, TOTP) securely
  • Maintains session continuity with automated refresh and change detection
  • Normalizes learners, programs/targets, sessions, trials, and behavior objects so you can integrate once across your tools
  • Aligns with customer entitlements and licensing constraints to ensure compliant access
  • Bridges portal exports and batch/report downloads with signed URL retrieval and delivery

Use Cases

EHR-to-ABA Data Synchronization

  • Push learner and staff rosters from your EHR/HRIS into DataFinch
  • Create sessions automatically from your scheduling system with assigned technician and location
  • Maintain a single source of truth for demographics and care team assignments

Target and Behavior Lifecycle Management

  • Pull program and target catalogs with mastery criteria and current phase
  • Post trial/probe data points programmatically from mobile or custom workflows
  • Track behavior events and surface trends for supervisor review

Automated Notes and QA

  • Assemble session notes based on collected data and activities
  • Flag missing trials, inconsistent prompts, or outlier behavior events
  • Route QA tasks to supervisors with linked evidence and audit trails

Outcomes and Reporting

  • Retrieve graph-ready aggregates for targets and behaviors
  • Feed BI tools with near real-time data for cohort KPIs, mastery velocity, and intervention effectiveness
  • Align reporting with payer and supervision documentation requirements

Available Endpoints

Authentication

POST /sessions: Establish a session using credentials. Supergood manages MFA (SMS, email, TOTP) and SSO/OAuth when enabled. Returns a short-lived auth token maintained by the platform.

curl --request POST \
  --url https://api.supergood.ai/integrations/<integration_id>/sessions \
  --header 'Authorization: Basic <Base64 encoded token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "username": "[email protected]",
    "password": "<password>",
    "mfa": {
      "type": "totp",
      "code": "123456"
    }
  }'

Example response

{
  "authToken": "eyJhbGciOi...",
  "expiresIn": 3600,
  "user": {
    "id": "u_18fd72",
    "name": "BCBA Supervisor",
    "roles": ["supervisor", "reporting"],
    "entitlements": ["learners", "programs", "sessions", "behavior"]
  }
}

Learners

GET /learners: Retrieve learner profiles with demographics, assignments, and basic clinical context. Use filters to scope to subsets.

Query parameters

  • search: string (name or MRN)
  • active: boolean
  • supervisorId: string
  • technicianId: string
  • updatedSince: ISO 8601 timestamp

Example response

{
  "items": [
    {
      "learnerId": "lrn_92c0a1",
      "firstName": "Aiden",
      "lastName": "Nguyen",
      "dateOfBirth": "2017-06-12",
      "mrn": "MRN-001245",
      "active": true,
      "diagnoses": ["F84.0"],
      "supervisorId": "u_18fd72",
      "technicianIds": ["u_90ab13", "u_31cfe9"],
      "funders": ["BlueCross PPO"],
      "updatedAt": "2026-01-18T21:45:03Z"
    }
  ],
  "page": 1,
  "pageSize": 50,
  "total": 1
}

Skill Targets and Data Points

GET /targets: List skill acquisition targets and their current phase, mastery criteria, and performance summary.

Query parameters

  • learnerId: string (required)
  • programName: string
  • phase: string (Baseline|Acquisition|Maintenance|Mastered|Closed)
  • active: boolean

Example response

{
  "items": [
    {
      "targetId": "tgt_b4ea21",
      "learnerId": "lrn_92c0a1",
      "program": "Receptive Labels",
      "name": "Identify Colors",
      "phase": "Acquisition",
      "masteryCriteria": {
        "requiredCorrect": 8,
        "trialsPerSession": 10,
        "consecutiveSessions": 3
      },
      "status": "in_progress",
      "lastSessionDate": "2026-01-19",
      "performanceSummary": {
        "correctRate30d": 0.72,
        "promptLevelTrend": "decreasing"
      }
    }
  ],
  "page": 1,
  "pageSize": 50,
  "total": 1
}

POST /targets/{targetId}/data-points: Create a trial/probe record for a target. Supports prompt level, correctness, and notes with audit trails.

curl --request POST \
  --url https://api.supergood.ai/integrations/<integration_id>/targets/tgt_b4ea21/data-points \
  --header 'Authorization: Bearer <authToken>' \
  --header 'Content-Type: application/json' \
  --data '{
    "sessionId": "ses_78c831",
    "timestamp": "2026-01-19T14:22:11Z",
    "trialNumber": 3,
    "promptLevel": "least_to_most",
    "response": "correct",
    "latencyMs": 2100,
    "notes": "Required minimal gestural prompt."
  }'

Example response

{
  "dataPointId": "dp_5d1f90",
  "targetId": "tgt_b4ea21",
  "sessionId": "ses_78c831",
  "response": "correct",
  "createdAt": "2026-01-19T14:22:12Z",
  "targetStatus": {
    "phase": "Acquisition",
    "masteryProgress": {
      "sessionsMet": 1,
      "sessionsRequired": 3
    }
  }
}

Sessions and Notes

POST /sessions: Create or update an ABA session with assigned staff, timing, activities, and note content. Attachments and location metadata are supported.

curl --request POST \
  --url https://api.supergood.ai/integrations/<integration_id>/sessions \
  --header 'Authorization: Bearer <authToken>' \
  --header 'Content-Type: application/json' \
  --data '{
    "learnerId": "lrn_92c0a1",
    "technicianId": "u_90ab13",
    "supervisorId": "u_18fd72",
    "startTime": "2026-01-19T13:58:00Z",
    "endTime": "2026-01-19T15:02:00Z",
    "location": {"type": "home", "lat": 33.7489, "lng": -84.3881},
    "activities": ["DTT", "Natural Environment Teaching"],
    "note": {
      "type": "SOAP",
      "subjective": "Caregiver reports improved color identification.",
      "objective": "10 trials administered, 8 correct with minimal prompt.",
      "assessment": "Trend improving; decrease prompt next session.",
      "plan": "Advance to reduced prompt; add generalization tasks."
    },
    "referenceId": "ehr-schedule-10841"
  }'

Example response

{
  "sessionId": "ses_78c831",
  "status": "saved",
  "createdAt": "2026-01-19T15:03:10Z",
  "referenceId": "ehr-schedule-10841"
}

Get full API Specs →

Technical Specifications

  • Authentication: Username/password with MFA (SMS, email, TOTP) and SSO/OAuth where enabled; supports service accounts or customer-managed credentials
  • Response format: JSON with consistent resource schemas and pagination
  • Rate limits: Tuned for enterprise throughput while honoring licensing and usage controls
  • Session management: Automatic reauth and cookie/session rotation with health checks
  • Data freshness: Near real-time retrieval of sessions, targets, behavior events, and graph artifacts
  • Security: Encrypted transport, scoped tokens, and audit logging; respects DataFinch entitlements and compliance requirements
  • Webhooks: Optional asynchronous delivery for session saves, target updates, and behavior event notifications

Performance Characteristics

  • Latency: Sub-second responses for list/detail queries under normal load
  • Throughput: Designed for high-volume trial/behavior event pipelines and reporting extracts
  • Reliability: Retry logic, backoff, and idempotency keys minimize duplicate actions
  • Adaptation: Continuous monitoring for UI/API changes with rapid adapter updates

Getting Started

  1. Schedule Integration Assessment

Book a 30-minute session to confirm your DataFinch product mix, licensing, and authentication model.

  1. Supergood Builds and Validates Your API

We deliver a hardened DataFinch adapter tailored to your workflows and entitlements.

  1. Deploy with Monitoring

Go live with continuous monitoring and automatic adjustments as DataFinch evolves.

Schedule Integration Call →

Frequently Asked Questions

Q: Which DataFinch products can this integration cover?

Supergood supports workflows commonly used in DataFinch’s ABA data collection stack (e.g., learners, programs/targets, trials, behavior events, sessions/notes), subject to your licensing and entitlements. We scope coverage during integration assessment.

Q: How are MFA, SSO, and batch interfaces handled for automation?

We support username/password + MFA (SMS, email, TOTP) and can operate behind SSO/OAuth when enabled. For batch/report flows, we manage timing windows, generate normalized exports, and retrieve signed URLs or delivery confirmations programmatically.

Q: Can I author notes or retrieve graphs programmatically?

Yes. You can create structured session notes and pull graph-ready aggregates for targets and behaviors. We preserve clinical granularity (trial-level details, prompt hierarchies, mastery criteria) with audit trails.

Ready to automate your DataFinch workflows?

Supergood can have your DataFinch integration live in days with no ongoing engineering maintenance.

Get Started →

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