Measure and Improve
Introducing PIQI
Patient Information Quality Improvement (PIQI) is an emerging open framework for evaluating the quality of electronic patient data. It aims to enhance the usability of shared patient information by ensuring it meets specific criteria for accuracy, conformity, availability, and plausibility. PIQI assesses data against a standard, such as USCDI v3, generates a scorecard, and provides insights into issues affecting the quality score. This feedback enables data sources to make necessary adjustments to meet quality requirements.
Evaluate and Elevate
The PIQI Design
1
Simplified Patient Data Model for Standard Processing
PIQI employs a minimal data model based on the US Core standard, tailored to the unique requirements of healthcare data. It assesses patient data regardless of the original message format.
2
Healthcare Data Quality Taxonomy for Issue Analysis
PIQI classifies issues into specific qualitative dimensions, which roll up into broad categories like accuracy, conformity, and availability. This taxonomy helps identify the root cause of data quality issues and offers insights for resolution at the source.
3
Modular and Shareable Assessment Approach
PIQI uses simple, pass-or-fail assessment modules with an encapsulated, extensible architecture. This modular design facilitates both basic and complex evaluations, fostering a shareable ecosystem that evolves with industry needs.
4
User-Configurable Implementation for Diverse Evaluation Needs
PIQI allows users to create customizable evaluation rubric, supporting various levels of data quality requirements. These rubrics can be tailored for standard and specialized use cases and shared across the PIQI community for broader application.
Resources
PIQI Framework Handbook v1.1 - May 5, 2025
PIQI Framework Message Format Implementation Guide Patient Clinical Data Model v1.1 - May 5, 2025
Download this guide for a structural overview of the PIQI Patient Clinical Data Model.
PIQI Framework SAM Guide v1.1 - May 5, 2025
Download this guide for an overview of the Simple Assessment Modules (SAMs) used in PIQI.
PIQI Framework Evaluation Rubric Guide v1.2 - July 24, 2025
Download this guide for an overview of the Evaluation Rubric Guides used in PIQI.
Data Quality in Healthcare: PIQI Framework
PIQI Alliance Confluence Site
Recent Updates
July 21, 2025
The PIQI Alliance has made a great deal of progress over the past several months. The purpose of the PIQI Alliance is to build a national, open-source framework to assess and improve patient data quality across EHRs, claims, encounters and lab data.
The PIQI Framework is advancing through the HL7 balloting process to become an informative specification standard. A public review period, including an opportunity to submit comments, is taking place over the next few months. We will keep you informed as this progresses. If you’re not currently an HL7 member and would like to participate in the voting process, visit their membership page.
What We’ve Accomplished to Date
- Formed in Fall 2024 as an informal working group in response to concerns raised by organizations including the VHA on the quality of data they were receiving from participating organizations.
- Released our vision at Health Datapalooza 2024: A Vision for Incrementally Improving Health Care Data Quality.
- The first version of the PIQI Framework was discussed at the ASTP Annual Meeting in December, 2024 and featured at both HIMSS, and ViVE 2025.
- Published the first version of the PIQI scorecard available under Resources.
- Finalized the PIQI Alliance Charter.
What’s Ahead
- We are currently developing evaluation rubrics leveraging the PIQI framework for US Core, CARIN IG for Blue Button, HEDIS, and CMS quality measures.
- The goal is to include those evaluation rubrics on every FHIR server in the country. Numerous organizations have stepped forward to be early adopters.
- In July, we’ll meet with CMS and NCQA to advocate for using the regulated FHIR APIs for clinical (US Core) and claims (CARIN IG for BB) with the PIQI scorecard to support reporting on digital quality measures.
- We’ve submitted coordinated responses to two recent RFIs on FHIR and digital quality measures.
- We’ll be seeking early adopter partners later this year to test and refine the PIQI framework in real-world settings.
Join the PIQI Alliance
Be a part of healthcare industry focused on improving the quality of patient data. Complete the form below to join a group of industry leaders working to create a higher level of trust and usability of patient data.