Qualified Clinical Data Registries a Data Intermediary Model

1. Qualified Clinical Data Registries a Data Intermediary Model May 3, 2013 Data Intermediary Tiger Team

2. ATRA 2012 and Qualified Clinical Data Registries (QCDR) SATISFACTORY PARTICIPATION IN A QUALIFIED CLINICAL DATA REGISTRY.— • “For 2014 and subsequent years, the Secretary shall treat an eligible professional as satisfactorily submitting data on quality measures under subparagraph (A) if, in lieu of reporting measures under subsection (k)(2)(C), the eligible professional is satisfactorily participating, as determined by the Secretary, in a qualified clinical data registry” • Secretary must recognize physicians that are “satisfactorily participating”  in “qualified” clinical data registries for payment programs • Requires the Secretary to establish how to recognize a registry as qualified and suggests the following attributes: • ‘(I) has mechanisms for the transparency of data elements and specifications, risk  models, and measures; • ‘‘(II) requires the submission of data from participants with respect to multiple payers; • ‘‘(III) provides timely performance reports to  participants at the individual participant level; and • ‘‘(IV) supports quality improvement initiatives for participants.

3. CMS RFI on QCDR 2013 • Reporting entity requirements for qualified registry under the PQRS for 2014 and subsequent years or the EHR Incentive Program • What types of entities should be eligible to submit quality measures data on behalf of eligible professionals for PQRS and the EHR Incentive Program? Examples might include medical board registries, specialty society registries, regional quality collaboratives or other entities. • What qualification requirements should be applicable to such entities?

4. CMS RFI on QCDR 2013 • Measure Selection for PQRS and EHR Incentive Program • Should we require that a certain proportion of submitted measures have particular characteristics such as being NQF-endorsed or outcome-based? • Should QCDRs have to apply to some entity for measure oversight? (HITPC described interest in measure quality) • Should measures be required to cover all 6 NQS domains? Or at least 3? • Participation Reporting Criteria • How many measures should an eligible professional be required to report on? • Should there be any requirement that the QCDR be able to report on both proprietary measures and eCQM from MU?

5. DITT Tasks Contribute recommendations on what additional attributes related to: 1. Privacy and Security 2. Data quality (completeness, timeliness, etc) 3. CEHRT Standards alignment (consume/produce CCDA or QRDA Level 3) 4. Business Rules (Do or Do Not Share Data, Do or Do Not Sale Data, etc)

6. Guiding Principles for QCDRS (from QMWG) Define Registry Broadly Maximize Interoperability Manage Data Innovate on e-Measurement

7. Requirements for QCDR(from QMWG) • Definition: • Start with AHRQ “an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes.”1 • Should be an entity that may include but also may be independent from societies • May be as flexible as an algorithm or software Gliklich RE, Dreyer NA, eds. Registries for Evaluating Patient Outcomes: A User's Guide. (Prepared by Outcome DEcIDE Center [Outcome Sciences, Inc. dba Outcome] under Contract No. 290-2005-0035-I.) AHRQ Publication No. 07-EHC001-1. Rockville, MD: Agency for Healthcare Research and Quality. April 2007.

8. Requirements for QCDR(from QMWG) • Analyze: Ensure data quality and integrity • Registries must ensure that data from EHRs are accurate, credible, and timely • Able to prove compliance and to pass data and process audits for data quality • Measure specifications are expressed in HQMF, value sets are valid and codes are up to date • Export: • Able to import/calculate/export QRDA cat 1&3 for 2014 eCQMs

9. Requirements for QCDR(from QMWG) • Accept Data from CEHRT: Able to comply with standard for MU (e.g. 2014 SCC for eCQM CEHRT module) • EHR must allow “automatic” export of  relevant data to registries • Registry able to accept CEHRT outputs (Consolidated CDA, QRDA cat 1&3) • Registries should be able to accommodate multisource data ( human abstracted, claims, clinical, administrative) data • Able to accept and incorporate PRO data into measures (e.g. at least one measure with a PRO data element) • Able to attest to and pass audits for industry standards of data privacy and security • How can we balance standardization with innovation? • How do we handle “measures” that don’t fit to our current concept?

10. Requirements for QCDR(provide reaction) • Role: Design Quality Measures and Perform Analytics • Measure quality: How can we be sure that measures are of high quality? Should they be NQF endorsed? • Innovation and Interoperability: e-Measures must use value set and logic that are consistent with HHS standards • Ability to import/calculate/export should monitored via Certification • Ability to risk adjust measure performance (some experince form Orix vendors in this space) • Role: Reporting data and results • Measure/Data Interoperability: Submit data to CMS (?and commercial payers) via QRDA or the appropriate SCC Standard • Publically reports all measures, numerator, denominator, exclusions and rationale • Should provider be afforded opportunity to review all reports prior to publication? • Should there be some standardized electronic format for reports that allow an API or web developer to use, analyze and dissemanate the data as well? • How should feedback on data quality be reported to physicians? • Should the registry be able to report back to the EHR?

11. Additional Questions Are there other roles will be required for EHRs to exchange useful data to QCDR? What other roles are required for QCDR? What level of verification is appropriate for each? Attestation, Certification, Auditing?

12. Framework Framework Payers Intermediaries Clinical Data Sources