Faster referral response and appointment readiness.
Use this signal to validate whether the workflow improved after a guarded pilot.
Physical Therapy case playbook
Physical therapy workflow that turns referrals, authorization, documentation, billing, and recalls into reviewed clinic packets.
Representative playbook
This case study is a representative workflow playbook, not a fabricated client claim. It shows how a buyer can scope the workflow before committing to implementation.
Workflow breakdown
The right first pilot should make the workflow easier to review, not harder to trust.
Problem: Physical therapy teams move between calls, faxed referrals, online forms, EMR, practice management software, payer portals, documentation queues, claims, payments, SMS, and email while patients expect fast scheduling and clear next steps.
Automation: AI classifies referrals and new patient requests, prepares intake and eligibility context, drafts reviewed reminders, queues missing forms, assembles authorization and documentation inputs, and routes billing, outcomes, recall, or clinician review packets.
Guardrail: Clinical recommendations, treatment plans, plan-of-care language, final documentation, coding, claims, benefits interpretation, authorization commitments, billing changes, refunds, and compliance-sensitive patient messages remain clinician, biller, or manager-reviewed.
Outcome signals
A useful case study should name the operating signals to monitor before and after launch.
Use this signal to validate whether the workflow improved after a guarded pilot.
Use this signal to validate whether the workflow improved after a guarded pilot.
Use this signal to validate whether the workflow improved after a guarded pilot.
Next step
We will compare this playbook to your actual systems, owners, approval risks, and measurable baseline.