Data Quality and Reporting Guide

Before reporting, measures must be validated. This means that each measure is verified to be an accurate, reliable reflection of the care that has been delivered or of the outcomes a patient has experienced. You should have a validation process in place to ensure the accuracy of measurement and reporting, which should include:

• A process for validation of internal data.
• An additional process to reconcile practice-produced core measures with MCP Pay for Performance (P4P) reports where core measures are used and a process to update data in the practice EHR when differences are identified.
• A process for ongoing reconciliation of practice and MCP data.

Process for Internal Data Validation

Data validation is the act of reviewing and confirming that data from your practice used to calculate PHMI core measures is of a minimum acceptable level of quality and accuracy. Depending on the analytics platform and process used to report each measure, validation can be an automated or a manual process or a combination of both. Having a systematic process with clear and specific steps to validate internal data will increase the level of confidence in the accuracy of the data reported for the core measures, and yield better decisions regarding performance improvement interventions and ongoing monitoring.

Data validation can occur at each step in the calculation process of a measure to ensure the accuracy of that specific component. Validation includes overall checks to confirm the final rate (e.g., do the numerator and denominator make sense?), reasonable breakdowns by subpopulations, and specific checks to confirm that a service or visit was correctly coded on a member level.

The Data Validation Process resource delineates an overall approach for basic data validation, describing key steps you can perform to validate your performance rates for PHMI core measures. These include general steps applicable across all measures (e.g., validating eligible population and stratified populations), as well as steps specific to each core measure, when relevant.

This data validation approach can be applied to other quality measures, including supplemental measures, other P4P measures, and is ideally part of a broader data governance program.

Process for Validation and Reconciliation of MCP Data

Reconciliation against MCP rates is critical to the PHMI data validation process because:

• The MCPs are producing similar rates through their P4P programs for an overlapping subset of measures that offer an important comparison opportunity.
• It ensures MCP P4P rates are an accurate reflection of the care provided and outcomes achieved.
• It ensures practices have accurate and reliable rates for improved care coordination and ongoing quality improvement.

The Validation and Reconciliation of MCP Data resource lays out a process to compare your practice and MCP measurement rates. For the PHMI measures that overlap with MCP P4P, practice rates are an opportunity to cross-check the validity of MCP rates and ensure optimal performance.

Reconciliation is a multistep process. To compare and analyze practice and MCP rates, it is important to know the steps, sources and criteria that the MCPs used to calculate their rates, which can be found in P4P manuals. You’ll need to identify any variation in measure calculation methodologies, such as differences in measure specifications and time frames for the reporting period, as well as any differences in determining the eligible population or subpopulations. Data from the MCP, such as patient-level detail or gaps in care reports, will be needed to facilitate reconciliation. The resource includes a checklist to assist in the reconciliation of the core measures, and you can work with your coach and SMEs to maximize the efficiency of engaging MCPs in tandem with other practices.