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Section 1h: Cross-paradigm/Domain Analysis Models

HL7 Informative Document: Patient Information Quality Improvement (PIQI) Framework, Edition 1

DESCRIPTION

Patient Information Quality Improvement (PIQI) is an industry initiative to improve healthcare data quality. The HL7 Cross Paradigm PIQI Framework provides a standardized, computable, and representation-agnostic approach for assessing the quality of patient-centric healthcare information. The framework establishes a common methodology for evaluating healthcare data at the structural and data-element level, regardless of whether the information is exchanged as HL7 FHIR resources, CDA documents, HL7 Version 2 messages or other data standards.PIQI assesses data quality against established healthcare data standards. The system then produces scorecards that show healthcare professionals whether their data meets quality requirements for specific uses.

PIQI was created to help organizations determine whether healthcare data is "fit for purpose" by applying predefined and reusable JSON based artifacts for defining evaluation criteria. Rather than focusing solely on data syntax, PIQI focuses on the availability, accuracy, conformity, and plausibility of the information being exchanged.

The framework supports the assessment of individual data payloads and generates standardized quality scores and scorecards that can be used to identify data quality issues, track quality trends, and improve trust in healthcare information exchange.

ALTERNATIVE NAMES

HL7 Informative Document: Patient Information Quality Improvement (PIQI) Framework, Edition 1 may also go by the following names or acronyms:

"HL7 Guidance: Implementing the PIQI Framework, E1",,PIQI, PIQI Framework

BENEFITS

  • Improved Trust in Healthcare Data
    • By providing transparent scoring and evaluation criteria, PIQI helps stakeholders better understand the strengths and limitations of exchanged healthcare information.
  • Support for Data Quality Improvement
    • PIQI provides a common, repeatable methodology for assessing healthcare data quality, reducing variation in how organizations evaluate the usability of healthcare information. Standardized approaches, scorecards and measurements enable organizations to identify root causes of data quality issues and target improvements and specific remediations more effectively.
  • Foundation for Automation
    • The framework promotes computable quality rules, allowing automated assessment and scalable quality monitoring across large healthcare ecosystems.
  • Cross-Platform and Cross-Standard Consistency
    • The framework is designed to work across multiple HL7 product families and healthcare data formats, enabling organizations to assess quality consistently regardless of the underlying representation.
  • Reusable Assessment Components
    • PIQI supports modular assessment logic, reusable evaluation rubrics, and shared quality criteria that can be applied across multiple use cases and implementations.

IMPLEMENTATIONS/CASE STUDIES

The following organizations have participated in past PIQI connectathons, the PIQI Alliance, or other implementation activities:

  • Clinical Architecture
  • Cognizant
  • Council for Affordable Quality Healthcare (CAQH)
  • CVS / Aetna
  • Deloitte
  • Drummond Group
  • Leavitt Partners
  • MITRE
  • Nava
  • National Committee for Quality Assurance (NCQA)
  • Onyx
  • Optum
  • U.S. Department of Veterans Affairs (VA)

DEVELOPMENT BACKGROUND

The HL7 Cross-Group Project (CGP) sponsored the PIQI Framework as a two-phased project. An informative document is the first phase, in which the PIQI Framework, its components and approach to data quality evaluation are described. The second phase will produce a Cross-Paradigm implementation guide (standard for trial use) that includes artifacts for PIQI implementation and conformance criteria.

RELATED DOCUMENTS

HL7 Informative Document: Patient Information Quality Improvement (PIQI) Framework, Edition 1

TOPIC

  • Data Usability

BALLOT TYPE

  • Informative

STATUS DATE

2026-08-26

RESPONSIBLE WORK GROUP

Cross-Group Projects

PRODUCT TYPE

  • White Paper

STAKEHOLDERS

  • Clinical and Public Health Laboratories
  • Clinical Decision Support Systems Vendors
  • EHR, PHR Vendors
  • Health Care IT Vendors
  • Healthcare Institutions
  • HIS Vendors
  • Immunization Registries
  • Lab Vendors
  • Local and State Departments of Health
  • Payors
  • Pharmaceutical Vendors
  • Quality Reporting Agencies
  • Regulatory Agency

FAMILY

  • Cross-paradigm

CURRENT STATE

  • Active

REALM

  • Universal