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Specifications, Standards and Informatics

The Specifications, Standards and Informatics team is responsible for the development and maintenance of technical specifications for quality measures developed by the AMA-convened Physician Consortium for Performance Improvement® (PCPI®).

Technical specifications are developed in standardized formats useful to providers and electronic health record (EHR) vendors to ensure:

  1. A standardized way of communicating performance measures
  2. The use of standards that permit structured, encoded performance measure information while preserving the clinical intent of the performance measure
  3. Improvement of the performance measure update and maintenance process for EHR vendors

Definition of Terms Used in EHR Specifications

The PCPI has defined some of the terms that are used in the Health Information Technology and Quality Measure arenas to describe quality measure specifications.

Electronic Specification (eSpecification), EHR specification
Generic terms used to describe a performance measure specification that includes information to facilitate the integration and interpretation of performance measures in EHRs.

eMeasure
The translation of an eSpecification in a computer readable format (XML) that has a specification in accordance with the HQMF (Health Quality Measure Format), an HL7 Draft Standard for Trial Use (DSTU).

PCPI-Branded eSpecification
A type of eSpecification developed by the PCPI that includes the following:

  • Test description
  • Data elements (including constraints and attributes)
  • Visual representation of the measure logic
  • Mathematical expression to calculate the measure performance and exception rates
  • Relevant value sets

The PCPI-Branded eSpecification is "human readable" and usable by anyone wishing to understand how the data elements for a measure are constructed and combined to calculate quality measure performance and exception rates. It can be used by a software developer to translate the quality measure specification into the HQMF eMeasure format.

PCPI intends the PCPI Branded eSpecification to serve as the basis from which the HQMF eMeasure is developed. It will help ensure that the intent of the PCPI measure is preserved when translated into the eMeasure format.

Technical Specifications for Different Data Sources

Technical specifications are developed for multiple data sources, including:

  • EHR data
  • Electronic administrative data (claims), which may include specifications for:
    • Prospective claims-based reporting (using Current Procedural Terminology (CPT®) Category II codes)
    • Retrospective claims analysis
  • Expanded (multiple source) administrative data
  • Paper medical record data/data collection flowsheet

For each measure developed by the PCPI, we recommend what data source(s) are appropriate for it and the corresponding rationale. These recommendations are found in the technical specifications section of the measure documents.

It is important to understand that not all measures are feasible for collection and reporting from all data sources.

EHR Data

Specification of performance measures by PCPI is critical to ensure that the intent of the measure is accurately represented prior to integration with an EHR. Complete PCPI-Branded eSpecifications will be developed once the measures are finalized by the PCPI measure development workgroup.

Meaningful, accurate and reliable performance measures can be computed by relying on EHR data. We recognize that not all EHRs in use have the functionalities to support all data elements required for these measures and, in some cases, such functionalities are available but are not being used. Thus, we will prioritize measures for EHR integration in order to provide a roadmap for EHR developers and users of EHR systems.

Electronic Administrative Data (Claims)

Electronic Administrative Data are typically used for reporting to third-party payers any clinical services (including diagnosis and service/procedure [CPT Category I] codes) provided to the patient by the physician, physician group practice and other qualified health care professionals. In some cases, this information can be analyzed to provide quality-of-care information.

Supplemental tracking codes (CPT Category II) are developed for performance measurement collection and reporting through a prospective claims-based reporting system. CPT Category II codes are optional tracking codes that can be included on the claim for quality measure reporting, but they are not required to process the claim for reimbursement.

The calculation of performance measure information may be determined by the claim form composition. Some claims will solely include reimbursement codes and others will include a combination of reimbursement and supplemental tracking codes. Some performance measures do not require that supplemental tracking codes be present on the claim form in order for the measure to be calculated.

Until expanded and linked administrative databases, or EHR systems, are more widely utilized, various pay-for-performance and pay-for-reporting programs (including the Physician Quality Reporting System of the Centers for Medicare and Medicaid Services [CMS]) continue to rely on this type of claims data.

Expanded (Multiple Source) Administrative Data

Expanded administrative data are routinely captured during the course of care delivery through either payment or care documentation. These data are accessible through large electronic databases. Multiple organizations gather such data, including health plans (e.g., medical claims), health systems (e.g., patient registries) and large data aggregators or warehouses.

In addition to provider claims data (as described above), these databases may aggregate data from multiple care settings (e.g., outpatient, inpatient, emergency department and other sites of care) and may include data elements not typically available on physician claims (e.g., pharmacy and laboratory data).

While this data source enables use of large data sets that can be joined and analyzed through complex, programmed algorithms, most data are currently confined to coded diagnosis and procedural claims and they typically do not include more robust clinical detail.

Paper Medical Record Data/Data Collection Flowsheet

Information from the paper medical record can be abstracted by prospective or retrospective manual review of clinical encounter information. Medical record data, despite being more expensive to collect, can provide much richer clinical information usually not available in electronic transactional data.