Healthcare Domain Expertise

Revenue Cycle AI

Downstream RCM tools are getting better at processing what they receive—that problem is increasingly solved. The unsolved problem is upstream: clinical documentation, coding specificity, medical necessity alignment, and payer policy mismatch. We build the intelligence layer that fixes revenue at the source.

$20M+

Verified ROI

45→28

Days in A/R

12%→4%

Denial Rate

200-300

bps EBITDA

The Problem

Every denial costs $25–$118 to rework. Providers blow past alerts.

McKinsey estimates that AI enablement of healthcare revenue cycle could cut cost to collect by 30–60%. Nearly 20% of claims are denied on average; as many as 60% of those are never appealed—representing millions in preventable lost revenue.

Upstream

Quality Gap

Clinical documentation, coding specificity, and medical necessity alignment are where revenue is lost—before a claim is ever submitted.

Disconnect

Clinical ↔ Financial

A physician ordering a procedure doesn’t know the denial rate for that order with that specific payer. Clinical decisions and financial consequences live in separate systems.

Fatigue

Alert Overload

Providers dismiss alerts because they create friction without providing value. The better path has to be the easier path—or adoption will never happen.

Our Approach

Three layers, one system.

We don’t bolt AI onto your existing RCM stack. We build an intelligence layer that learns your specific payer mix, fights your specific denial patterns, and becomes an institutional capability you own.

Start Here 1

Data Audit

Map where leakage happens. Pareto analysis of denial drivers by denied dollars—not count. Quantified, prioritized foundation for every decision that follows.

See the Revenue Integrity Audit →
2

Data Engineering

Clean and connect inputs so claims start cleaner before anyone touches them. Patient identity, eligibility, authorization linkage, payer rules. Fix the plumbing—denials disappear.

3

Workflow Intelligence

Surface contextual insights to providers at point of work. Light touch: supporting evidence, no hard stops. Providers adopt it because it makes work easier, not harder.

See it for yourself

The Model Hospital walkthrough.

The Model Hospital is a live, interactive simulation of a financially constrained hospital. Built so revenue-cycle leaders can see how AI prioritization changes the recovery curve, without anyone sharing real patient or financial data. Walk through it in 5 to 7 minutes, then bring your own data to a Deployment Assessment.

3,847

Open claims

320

Daily collector touches

120

Day horizon

Holdout

Measurement baseline

Model Hospital simulation: Recovery Intelligence view comparing prioritization workflow to aging-only baseline across 120 day horizon
Interactive Simulation

Open the Model Hospital

Walk through the prioritization workflow, the recovery curve, and the learning dashboard. 5 to 7 minutes.

Open in a new tab →
In the walkthrough

What you will see

  • Why aging-only worklists leave recoverable dollars on the table
  • How prioritization changes the recovery curve over a 120 day horizon
  • How a holdout group lets you measure lift against a real baseline
  • How payer patterns and rejection reasons feed back into the model

The simulation is the visualization of the operating model. The Deployment Assessment finds your version of it.

Philosophy

Light touch, provider-driven.

Make the better path the easier path

Reduce cognitive load, not add it

Let providers validate and own changes

Documentation–to–revenue visibility

Use subtle organizational incentives

Peer benchmarking, RVU alignment

Never get in the way of patient care

Contextual, non-interruptive, trust-building

AI Frameworks

The intelligence layers, productized.

The Model Hospital demonstrates the operating model. These are the productized intelligence layers Digital Scientists has built across hospital and post-acute revenue cycle. Each links to a deeper guide.

Integration

Works with your existing systems

Revenue cycle AI requires deep integration with billing systems, EHRs, and clearinghouses. We have production experience with the platforms you use.

Practice Management

Integration with PM systems for claims, patient demographics, and payment posting.

EHR Systems

PointClickCare, Epic, Gehrimed, Elation—bidirectional data flows for clinical context.

Clearinghouses

Claims submission, status tracking, 835 ERA processing, and denial feed ingestion.

Payer Portals

Automated eligibility checks, prior auth status, plan-level coverage rules, and claims inquiry.

EHR Integrations is the supporting capability that runs underneath every healthcare domain at DS. See the production EHR integration backbone →

Our Process

We don’t just build and hand off. We operate, support, and stand behind our work.

Phase I

Discover

01

Data Foundation — Ingest 12–18 months of claims + remittance data, map denial patterns

02

Solution Design — Revenue Integrity Audit, Pareto analysis, opportunity ranking by denied dollars

Phase II

Experiment

03

Hypothesis & Scope — Target highest-ROI denial bucket with pilot intelligence layer

04

Build & Validate — Working AI tested on real claims data with operational feedback

Phase III

Engineer

05

Agile Development — Iterative sprints with RCM team feedback

06

Systems Integration — EHR, clearinghouse, and payer portal connections

07

Change Management — Provider training, workflow adoption

08

Production Deploy — Phased rollout with monitoring

Phase IV

Optimize

09

KPI Accountability — Revenue impact validated by independent financial analyst

10

Continuous Improvement — Model retraining, payer policy updates, ongoing support

FAQ

Frequently Asked Questions

Common questions about AI-powered revenue cycle management for healthcare organizations.

Revenue Cycle Intelligence Series

Five posts. One argument. Build your own intelligence.

From upstream revenue leakage to a four-phase AI roadmap your CFO will approve — the complete case for payer-aware intelligence that your organization owns.

Ready to quantify your upstream revenue opportunity?

Start with a Revenue Integrity Audit. 2–4 weeks. We’ll show you exactly where revenue is leaking and what AI can recover.

Or call: 404.654.3855

Engagement Models

DS works as a Professional Services build partner or as a Venture Studio with equity-aligned partnerships, accelerators, and operator-founder programs. The right model depends on whether you own the IP, share it, or license ours.

See all engagement models →
DS Capabilities

The DS practice behind this

Revenue cycle AI is built on healthcare-specific AI engineering, validated through fast MVP cycles, and grounded in DS’s broader AI practice.