The AI Engine Behind Collaborative Intelligence™
AI that covers more, gets more right, and never decides alone.
Prodigy is MRO’s enhanced-abstraction AI engine. It works inside the abstractor’s existing workflow, covering 60% of data elements at 97%+ accuracy — while clinical experts retain authority over every decision.
60%
data element coverage
97%+
accuracy rate across all data elements
1,000+
clinical data experts working alongside Prodigy every day
The Problem
Abstraction is too important to automate alone, and too slow to do by hand.
Eighty percent of clinical data is unstructured. Abstractors interpret it line by line for registries, quality measures, and research. All this work drives reimbursement, accreditation, and patient outcomes.
Pure automation puts that work at risk. Pure manual review can’t keep pace with the data healthcare now produces.
Prodigy is built for the space in between: a clinical AI engine that does the heavy pattern recognition so abstractors can focus on improving judgment, nuance, and defensibility.
How it Works
Built into the workflow, not bolted on.
Prodigy lives within Q-Apps®, the same environment MRO’s clinical data experts already use. It activates as abstractors move through cases, surfacing evidence, suggesting values, and flagging inconsistencies — and it learns from every decision.
Surfaces evidence
Prodigy reads the unstructured chart — notes, reports, results — and points the abstractor to the source text that supports each data element. The exact passage from the chart appears alongside the suggestion, so the abstractor can verify reasoning in seconds instead of hunting through a 400-page record for one timestamp.
- Unstructured chart parsing
- Source-linked evidence
Suggests values with a confidence rating
For supported fields, Prodigy proposes an answer grounded in evidence and shows how confident it is. A clear High / Medium / Low confidence rating tells the abstractor whether the suggestion is well-supported or worth a closer look. The abstractor accepts, modifies, or rejects — and that decision feeds continuous learning.
- High
- Medium
- Low
Explains its reasoning
Every suggestion is paired with a plain-language explanation of how Prodigy arrived at it. The reasoning panel, confidence rating, and source excerpt appear together in Q-Apps — so the abstractor sees the why alongside the what, without leaving the workflow.
- Plain-language reasoning
- No black boxes
Flags inconsistencies
Prodigy compares values across the case and across the registry, surfacing conflicts the human eye might miss on case number 47 of the day. The abstractor sees the flag and makes the call.
- Cross-case comparison
- Registry-aware checks
Prodigy does not
- Submit data without expert review
- Replace clinical judgment on contested fields
- Operate outside Q-Apps or MRO’s quality system
- Hide its reasoning — ever
What Every Suggestion Shows You
Three things, every time. No exceptions.
Every value Prodigy suggests appears alongside three pieces of context, visible to the abstractor inside Q-Apps before any decision is made.
This is what “no black boxes” looks like in practice. Reasoning, confidence, and source are not optional features. They appear on every suggestion, every time — because a clinical expert can’t be accountable for a decision they can’t trace.
01
AI reasoning
A plain-language explanation of how Prodigy arrived at the suggested value. Not a model score. An actual sentence the abstractor can read and evaluate.
02
Confidence rating
A clear High, Medium, or Low rating telling the abstractor how well-supported the suggestion is. Low-confidence flags slow down. High-confidence suggestions move faster.
03
Source excerpt
The exact passage from the chart, with page reference, that Prodigy used to form its suggestion. The abstractor can verify the source in one click.
What Makes Prodigy Work
Prodigy is more than a model. It’s where three forces meet.
Each force does what it does best. Together they produce more than the sum of their parts.
Together these forces produce more than the sum of their parts. That combined effect is what we call Collaborative Intelligence™ — MRO’s framework for healthcare AI.
Trust
The principles Collaborative Intelligence is built on — and how Prodigy delivers each.
These aren’t positioning statements. They’re architecture decisions visible in every suggestion Prodigy makes.
AI-Native Environment
Prodigy is not a feature bolted onto legacy abstraction software. It is built into the foundation of MRO’s curation work — covering up to 60% more data elements and delivering 18% higher accuracy than other AI solutions in the market.
Shared Learning
Every accept, modify, and reject decision feeds Prodigy’s improvement. Working in partnership with the largest team of clinical experts in the nation, Prodigy gets better at the cases your organization, your registries, and your specialties produce.
Human Oversight
Every Prodigy suggestion comes with a written explanation, a confidence rating, and the chart excerpt it was based on. Every decision improving the next. Every output that leaves MRO has been reviewed and approved by a credentialed clinical expert.
Resilience
Automation empowers a diverse team to adapt to disruption, remove routine burdens, and level the playing field — so the work continues reliably at scale, across registries, service lines, and client environments.
It’s not replacing what I do. It surfaces the evidence so I can spend my time on the calls that actually require judgment, not hunting through records for timestamps.
—Clinical Data Abstractor, MRO
10+ years registry experience
Infrastructure
Prodigy is only as good as the data it sees.
AI without infrastructure is a demo. AI on the right infrastructure is a system.
Prodigy runs on MRO’s Clinical Data Exchange Platform (CDXP) — a FHIR-native interoperability framework that ingests clinical data in whatever format the source produces and structures it for downstream use.
The CDXP is why Prodigy can be deployed across registries, service lines, and client environments without rebuilding the pipeline each time.
Clinical Data Exchange Platform (CDXP)
The foundation Prodigy runs on.
Proprietary, FHIR-native interoperability that ingests any data format and structures it for AI-powered curation across every registry and service line.
- FHIR-native — 233+ EHR connections
- Ingests clinical data in any source format
- SOC 2 + HITRUST CSF certified
- Deployable across registries without rebuilding pipelines
- Scales from 1 facility to 150+
See Prodigy in the workflow.
A 30-minute walkthrough is the fastest way to understand how Collaborative Intelligence works in practice — and what 60% more coverage at 18% higher accuracy could mean for your program.