Trusted by teams turning documents into production data
Healthcare
Prior authorization forms request payer approval for procedures, medications, or equipment before services are rendered. Every payer uses a different form layout. Sensible converts PA data into structured JSON for utilization management, workflow automation, and denial tracking.
Validated JSON
Schema-enforced output; every field matches your contract
Source coordinates
Every value links back to page + bounding box for audit
Per-document pricing
Predictable cost. No token-volatility surprises
Trusted by teams turning documents into production data
Payer layouts differ, clinical justifications run free-form, and medication and procedure detail has to be exact. We read the mixed fields and validate the codes against standard sets.
01
UnitedHealthcare, Aetna, Cigna: each designs PA forms with different field arrangements, required sections, and response formats. The extraction adapts to each payer's form while outputting a standard authorization schema.
02
Free-text clinical justification sections describe medical necessity in narrative form. LLM parsing extracts the key clinical details (diagnosis, failed treatments, clinical rationale) from unstructured text that rule-based parsers cannot handle.
03
Drug names, NDC codes, dosages, CPT codes, quantities: each requires precise extraction. Validation rules check format compliance on every field, because a wrong NDC code means a rejected authorization.
Managed services
Solutions engineers handle plan, build, deploy, and adjust on your behalf. You see clean JSON in your API response. Same engine as self-serve, just with the configuration work outsourced.
What's included
01Plan.Engineers review your samples and pick the right method
02Build.SenseML configs written from your samples
03Deploy.Same engine as self-serve, ready for production
04Adjust.We update configs when formats shift or new edge cases appear
05Integrate.Help with custom integration into your downstream systems
Every prior auth form is different, so we build the config around your exact schema rather than a fixed list. These are the fields UM teams request most; we map whatever else your prior-auth tracking workflow needs.
01
Patient and provider
Patient name, DOB, member ID, group number, requesting provider name, NPI, facility name, payer name, plan type
02
Clinical detail
Primary diagnosis (ICD-10), secondary diagnoses, requested procedure (CPT), requested medication (NDC/drug name/dosage), clinical justification
03
Authorization tracking
PA request number, submission date, urgency (standard/expedited), requested service dates, units requested, estimated cost
config.json
SenseML
{ /* SenseML: prior authorization form extraction */
"fields": [
{
"method": {
"id": "queryGroup",
"queries": [
{ "id": "patient_name", "description": "patient name, member name, subscriber" },
{ "id": "auth_number", "description": "authorization number, PA number, auth #, reference number" },
{ "id": "requested_service", "description": "requested procedure, requested medication, drug name, CPT code" },
{ "id": "auth_status", "description": "authorization decision, status, approved, denied, pending" }
// + more fields, mapped to your schema
]
}
}
]
}Sensible processes PA forms from any commercial payer, Medicare, Medicaid, and PBMs. The hybrid approach handles both the structured fields and the free-text clinical sections.
UnitedHealthcare, Anthem, Aetna, Cigna, Humana, BCBS affiliates, regional health plans
Medicare (MAC-specific), Medicaid (state-specific), Part D, CVS Caremark, Express Scripts, OptumRx
Answers about payer form support, clinical justification parsing, and PA tracking.
By default Sensible captures requesting provider name, NPI, practice name, phone, fax, servicing facility details, plus patient information like member ID and group number. The field set is configuration, so you can add or drop fields to match what your intake or routing systems expect.
Yes. The default config reads payer name, plan type, authorization number, required documentation checklist, peer-to-peer review requirements, and appeal deadlines. What you capture is defined in configuration and can be reshaped for the payers and plan types you handle most.
Sensible reads the requested medication with dosage, frequency, quantity, and NDC code, or the requested procedure with CPT code, diagnosis codes, and clinical rationale. These are the defaults; the extraction logic is configuration, so you extend it to whatever clinical detail your authorization workflow needs.
Yes. Sensible captures the authorization decision (approved, denied, pending), effective dates, authorized units or duration, and any conditions or restrictions.
Yes. Sensible sends extraction results to your webhook endpoint when processing completes. You can also poll the API for status.
Yes. Sensible flags extractions with low confidence for human review. You can configure review thresholds and workflows.
Sensible is SOC 2 Type II certified and HIPAA compliant. Data is encrypted in transit and at rest.
Document data is stored indefinitely by default. Custom retention policies are available and can be configured for same-day deletion if needed.
Yes. Sensible offers a 14-day free trial on the Growth plan. No credit card required to start.
Sensible uses per-document pricing for predictable costs. No token-based billing or usage surprises. Volume discounts are available for higher throughput.
Sensible provides REST APIs and SDKs for Python and Node.js. Most integrations take a few hours. Webhooks, Zapier, and direct API calls are all supported.
Sensible processes PDFs (native or scanned), Microsoft Word (DOC, DOCX), spreadsheets (XLSX, XLS, CSV), single-page images (JPEG, PNG), multi-page images (TIFF), and email bodies with attachments.
Accuracy depends on document quality and configuration. Most production deployments achieve 95%+ accuracy with proper validation rules and confidence signals.
Processing speed depends on document size, page count, OCR requirements, and which extraction methods are used. Simple single-page documents process in seconds. Larger or more complex documents that use LLM-based extraction take longer.
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