Standard Data Fields for HEDIS Measures

©️ 2024 Kaiser Foundation Health Plan, Inc.

This resource is part of the Data Quality & Reporting Implementation Guide, offering steps and activities to ensure your practice is capable of reporting valid and reliable data for selected population health measures. It is the first in the “Building the Foundation” series of implementation guides.

This document defines where standardized internal data is needed for the calculation of core HEDIS measures for PHMI. It also outlines processes for the capture and submission of all relevant data.

The utility of performance measures depends upon accurate data that reflects the care and services patients receive. Through the Population Health Management Initiative (PHMI), community health centers (CHCs) are expected to compile and extract all internal data needed for reporting, to ensure no gaps in data. This resource provides definitions of the standard data and measure fields with guidelines to assist CHCs with measure reporting.

CHCs can use this resource in conjunction with their practice coach and subject matter experts (SMEs) to determine:

• Where data are needed.
• Whether the CHC is adequately utilizing all data sources.
• Whether information is being captured/stored in inconsistent locations that would not be reflected in calculated rates.

This should be a starting point for quality improvement related to data capture and proper coding (see Data Quality and Reporting Resource 5: Documentation and Coding Playbook for more information related to proper coding for each measure).

To accurately capture data from a patient’s medical record, store data in structured fields according to a standard file layout. This requires:

• The availability of those fields within the medical record with information stored in a structured way.
• Consistent and accurate use of those fields by all providers of care.

If standard fields are not available or not used properly and consistently, the care and services provided by the CHC may not be reflected in performance rates, and CHCs may not be able to report rates by sub-populations. A large-scale, repeated effort to cull data from unstructured fields would be needed to accurately reflect the care patients are receiving.

With their practice coach and SMEs, CHCs should follow the below steps to identify standard data fields, determine how information should be stored, assess current use of those fields and define steps going forward to ensure standard capture of data. This process can be tailored for each CHC based on their specific factors, such as electronic health record (EHR) system used, and includes the following steps:

Step 1: Review list of needed fields and how information should be entered/stored.

The following sections of this document specify the types of data fields needed for population-level and measure-specific standard data capture. Using that information:

• Practice coaches and SMEs should guide CHCs in understanding which fields are needed and how information should be consistently stored within these fields.
• CHCs should identify relevant contacts to guide and participate in this work, including an IT lead, clinic lead and data governance staff.
• CHCs should put standard processes in place to ensure the consistent entry of information into these fields by all relevant clinic staff.

Step 2: Determine which specific fields within the CHC’s EHR align with these fields.

There are two parts of this process which include:

• Obtain and assess field specifications: There are several ways to approach this including:
  • Data structure, fields and EHR mapping for common EHR systems (e.g., NextGen, eClinicalWorks) are available to the PHMI project through the technology proof of concept workstream that can be used to ensure efficiency.
  • Field specifications not available through the proof of concept would be individually obtained.
  • User groups based on EHR can be utilized to gain efficiencies across CHCs. Specific follow-up steps can be tailored to individual CHC use cases as needed.
  • Each EHR user group (or CHC, if relevant) should review the obtained field specifications.
• Create a standard data fields “crosswalk” with the CHC’s EHR: Practice coaches and SMEs should work with user groups/CHCs to populate a crosswalk of standard data fields with EHR-specific fields. The crosswalk should be in a standardized Word or Excel format used across all CHCs and include information such as the data field, a description, the core HEDIS measure for PHMI, and the status of the denominator, numerator, and/or exclusions, and it should be mapped to the EHR field specifications.

Step 3: Assess standard data field usage.

• Staff interviews/discussion with each CHC would be conducted to determine whether this field is used, variation in how it is used, and how data is inputted/ stored for that standard data need (whether within the standard field or elsewhere).
• Each user group/CHC would develop the needed specifications and process documents to run a report to determine usage/completeness of the field, including file layouts, processes for secure information transfer as needed, etc.
• Assess the overall report for discrepancies/disparities in clinicians, sites, patient demographics, etc. to determine where gaps exist. Assess for:
  • Correct formatting.
  • Mistakes and incorrect data (e.g. text in numeric fields, inappropriate values).
  • Missing data (e.g. gaps).

Step 4: Determine need for improvement with an action plan.

Based on the results of the field usage assessment, each CHC should develop an action plan for improvement. An action plan may include the following steps:

• Development of standard processes for data capture.
• Staff reeducation.
• Processes for continued oversight of data fields.
• Remediation steps to clean data currently stored in fields.

Step 5: Develop and solidify an ongoing process for standard data review.

• Develop standardized file submission process, submission tool, and cadence of pull that leverage relevant EHR user groups.
• Develop process for review of data/gaps listing and remediation steps (e.g., clinician outreach to discuss service gaps, conduct reeducation).
• Develop policies and procedures as needed to ensure sustainability of ongoing process.

Step 6: Determine steps needed for (short-term) capture of data stored in alternate locations.

• As inconsistencies in use of standard data fields are identified, CHCs may discover that information is stored in alternate forms (e.g., screening or lab data may be stored in PDFs uploaded to the chart rather than in structured data fields).
• Practice coaches and SMEs should help determine the timeline for ensuring reliability of standard data fields and short-term steps that may be needed to access information from nonstandard sources (e.g., supplemental data).

All performance measures depend upon the accurate capture of demographic data stored consistently in standardized data fields. These data form the basis for CHCs to identify the eligible population for each measure. These data are also necessary to ensure that CHCs can calculate measures by sub-population (e.g., race and ethnicity) to ensure accurate monitoring of disparities in care. Table 1 below is a checklist to track population-based fields by location in the EHR and its usage and parameters.

FIGURE 4.1: CHECKLIST FOR POPULATION-BASED DATA FIELDS