
Early-out self-pay AI lifts collections 29% at a 900-provider physician group
A national physician group was placing early-out self-pay accounts with agencies at 90 days because in-house outreach couldn't keep pace. pronix.ai deployed an agentic early-out program on voice, SMS and email with propensity-to-pay scoring, self-service payment plans and financial-assistance screening — collections lifted 29% and cost-to-collect dropped 38%.
Multi-specialty physician group, 900 providers across 6 states · Amazon Connect · Kore.ai Agent Platform · Athenahealth · Salesforce Health Cloud
- Client
- Multi-specialty physician group, 900 providers across 6 states
- Industry
- Healthcare Providers
- Platform
- Amazon Connect · Kore.ai Agent Platform · Athenahealth · Salesforce Health Cloud
*Representative outcome; results vary by client, scope and platform configuration.
The challenge
Self-pay balances after insurance had grown to 22% of AR and the in-house early-out team could only touch each account twice before agency placement. Patients wanted digital-first, self-serve options; regulators demanded strict TCPA, healthcare-privacy and state-collection compliance on every contact.
Our approach
Propensity-to-pay segmentation
A model scored each account for likelihood to self-resolve, best channel and best offer — high-propensity accounts went digital-first, hardship signals were routed to counselors before any collections contact.
Compliant multi-channel cadence
Voice, SMS and email orchestrated with consent, quiet-hours and frequency caps enforced by policy — every touch logged with script version and consent state for audit.
Self-service resolution
Patients could view a plain-English statement, split into a payment plan up to 24 months, apply for financial assistance or pay in full — all without agent contact, all inside a healthcare-safe portal.
Counselor copilot for exceptions
When patients called in, a counselor copilot surfaced account context, payer status, plan eligibility and prior offers — average handle time on collections calls fell 34%.
“We are collecting more, from more patients, with fewer complaints — and we placed 40% fewer accounts with agencies last quarter.”
Take this case study into your next steering committee.
One page: the business problem, the solution, the technical architecture and the measured outcomes — sized to drop straight into a board pack. Share your work email to unlock it; one form unlocks every gated download on this site.
Board-ready briefs covering the platform and industry behind this program. Free with a work email.
33% reduction in bad debt placement at a regional health system — compliant patient collections
Read →47% faster denial resolution at a multi-hospital system — RCM workqueue automation
Read →Unified patient-services concierge handles 52% of inquiries without a live agent
Read →Illustrative case study. Scenarios, metrics, quotes and client details are representative composites based on Pronix engagements and industry benchmarks unless a named client is shown with written consent. Outcomes vary by client, scope, data quality and platform configuration. Nothing on this page is a guarantee, warranty or professional advice. See our Terms of Use for the full disclaimer.
AWS, Salesforce, Microsoft, NICE, Genesys, Kore.ai, Google, ServiceNow, Amazon Connect and logos referenced on this site are trademarks of their respective owners. References are for descriptive purposes only and do not imply endorsement, sponsorship or partnership beyond stated partner relationships. See our Disclosures.
Talk to the team that shipped it.
Book a working session with a pronix.ai lead on this practice — we'll map the approach to your platform, industry and constraints.
Want a similar programme in your environment?
Four fields. Tell us the outcome and timeline, and the lead for this industry replies with indicative scope, team shape and commercial options.
industryHealthcare Providers — routed to this team