DATA QUALITY
Get one answer to who your people are and what your data means
Duplicate person records and mismatched clinical terms leave every team working from a different picture. Rhapsody links those records and standardizes terminology across your systems, so everyone can rely on the same data.
DATA QUALITY SOLUTIONS
Person identity and clinical terminology, working together
Rhapsody Identity with Autopilot
Link every record for the same person across your systems, with AI that adapts to your population and resolves identities automatically.
Rhapsody Semantic
Give every application and tool a way to link to a common clinical vocabulary, with standard content libraries and automated mappings that keep your data ready for exchange.
The challenge
Fragmented records carry into every decision that follows
Records that don’t match, codes that don’t agree, and teams reviewing it all by hand add up. Organizations report spending $1.3M per year on identity resolution, and $1,950 per inpatient stay when records for the same person don’t match.
Common signs your data quality needs attention:
- Support queues that keep growing
- Implementations slowed by data complexity
- Analytics and AI results your teams second-guess
See all nine signs in our guide: From Data Chaos to Clean Identity →
Health information leaders
You’re working through record-review queues that grow faster than the team can clear them, and you need every match to be right.
Analytics & AI leaders
Your models and dashboards are only as reliable as the identity and terminology data behind them.
Technology leaders
Every new file brings different patient identifiers and semantic inconsistency. Reconciling differences pulls engineering time away from your roadmap.
Our point of view
Trusted data takes more than a one-time cleanup
Merging duplicates and reconciling codes solves the problem for now, but every new system and merger brings it back. Rhapsody keeps your records and codes consistent as your data changes, so you aren’t starting over each time.
build the infrastructure
The same records and terms across every system
Records for the same person are linked across your systems, and every team keeps its own vocabulary while sharing a consistent understanding of clinical terms.
AUTOMATE the work
Matching that keeps up on its own
AI that adapts to your population learns your data quality standards and resolves person identities automatically.
- Match review
- One record
- Autopilot
- One meaning
Swipe to compare all three systems →
| Compare | EHRMRN 48221 | CRMCRM-20957 | Regional HIEHIE-83472 |
|---|---|---|---|
| First name | Jamie | Jamie | Jaimie |
| Last name | Sample | Sampel | Sample |
| Date of birth | 01/01/1990 | 01/01/1990 | 01/01/1990 |
| Phone | (555) 555-0142 | (555) 555-0142 | (555) 555-0142 |
| Address | 123 Example St | 123 Example Street, Apt 2 | 123 Example St. |
| ID (last 4) | •••• 0142 | •••• 0142 | •••• 0142 |
Autopilot proposal: same person across all three systems · 98.8% match confidence · differences highlighted
Link recordsMark uniqueStart every decision from data you can count on
See how Rhapsody Identity links records for the same person and Rhapsody Semantic puts every system on a shared clinical vocabulary.
Why rhapsody
- Proven enterprise person data management
- Standards libraries maintained for you
- Feeds analytics, AI, and agentic workflows
Proof
Measured where it matters
90%+
Match rate improvement with EMPI
1,900+
Healthcare organizations worldwide
40+ yrs
Healthcare only, always
63
Net Promoter Score
“Clinicians get a timely, accurate, complete view of everything that happened previously with that individual.”
Geisinger ran automatic matching enterprise-wide, cutting the cost of resolving fragmented records by 90% and freeing 5 people for higher-value work.
Kim Chaundy
VP, Applications and Interoperability
Geisinger
“This is the shift you want: from babysitting duplicates to tackling higher-order data quality problems.”
Rochester’s RHIO cleans identity data faster than manual review ever could, freeing the team to work its data needs more granularly.
Michael Frey
CIO
Rochester Regional Health Information Organization
- Great Lakes Medical Imaging: 1,400 records reconciled monthly, 30% more order volume
- KeyHIE: 743 hours saved monthly, 12 million records resolved into single identifiers
- San Mateo County Health: unresolved records from 6% to under 1%, across four EHRs
- Zephyr AI: production-ready AI models in under 30 days with Semantic
See what changes when every system agrees on your data
Get a live look at how records are matched and terms stay consistent across your systems.
Integration →
Move trusted data anywhere it needs to go.
AI Governance →
Govern how AI agents and APIs reach your data.
Axon AI →
AI that work best on data they can trust.