SUPPLEMENTARY INFORMATION:

Over the next several months, the Quality Workgroup will begin to gather information from a wide variety of stakeholders on the data infrastructure strategies—data aggregation including merging of data from multiple sources and measuring across episodes of care—that have been developed and implemented across the healthcare community.

The following questions are designed to draw out responses from industry members, regardless of size or implementation status, on real-time experiences with creating and/or implementing a data infrastructure strategy for quality measurement and reporting. The responses will be analyzed and summarized to help Quality Workgroup members understand the current challenges, successes, and best practices within the industry.

Questions

1. Please describe the process through which data is typically collected and aggregated, providing real-time examples and drawing from your experiences where possible. Please include the following key points:

• What business functions (e.g., transparency, payment, network creation, internal quality improvement, public reporting, disease management) are supported through aggregation of patient-level data?
• What financial models support the operational costs of aggregating patient-level data (e.g., internal costs, payers or employers paying a set fee, sale of data to third parties, grants, etc.)?
• In your experience, what types of data can be collected and merged together? For instance, can electronic health record data be merged with other data (claims, lab results, pharmacy)? What are the common barriers to merging data from multiple sources?
• What strategies can be used to help ensure that data that is generated by or stored in multiple systems within an organization can be collected and aggregated?
• What strategies could be employed to ensure that data can be aggregated from multiple organizations? What types of agreements and system changes are needed for this to occur?
• In your experience, when a single data element is accepted from multiple and distinct sources (e.g., claims data, electronic health records, lab results), from which sources is duplicate data typically accepted? What processes are needed to ensure that the data are comparable?
• What data would you like to collect but do not currently have access to or the ability to collect?
• Of the data that you can currently access, what data cannot be reasonably aggregated at a patient level with data from other systems due to technical, business or policy challenges: Please describe the challenges.
• What are some best practices or lessons learned that could be shared about collecting and aggregating data from multiple sources?
• Is your experience, is a centralized or distributed database (i.e., one with multiple storage sites) preferable? What are the pros and cons of using either approach?
• What factors should be considered when determining what type of entity should serve as the database host? Can you provide examples of the database host arrangements with which you have experience?
• What types of organizations need access to data form an aggregated database? Can you describe the types of data-sharing agreements that are needed to share data from an aggregated database?
• What privacy/security challenges are common when considering the collection and aggregation of data from multiple sources as well as the sharing of that data? What strategies can be used to overcome these challenges?

2. Can you please input on the strategies that should be used to develop a longitudinal view of patient data to evaluate clinical performance, providing real-time examples and drawing from your experiences where possible? Please focus on the following key points:

• What strategies can be used to link patient-level data to define an episode of care (e.g., commercial software vs. custom algorithms)?
• For what medical conditions is longitudinal measurement the most useful? Why?
• What data sources are needed (e.g. pharmacy, lab results, claims data, electronic health records, data from multiple organizations) to collect longitudinal data for episodic measurement? Can you describe initiatives where this has been done successfully?
• In your experience, how is an episode-of-care quality (and cost) measurement strategy influenced by data availability? Data reliability?
• What factors should be considered when determining what type of entity should serve as the database host for longitudinal data? Can you provide examples of hosting arrangements with which you have experience?
• What implementation barriers exist related to data collection and aggregation of longitudinal data? What strategies can be employed to overcome them?
• What outcome and process measures are best supported by an episode-of-care methodology? Can you provide specific examples using a methodology with which you are familiar?
• What feedback mechanisms are used or should be used to provide information back to providers or payers to help them better manage patient care? Are these methods retrospective, concurrent, or prospective? What are the barriers to providing concurrent or prospective feedback?
• What are some best practices or lessons learned that could be shared on longitudinal data management strategies?

The meeting will be available via internet access. For additional information, go to www.hhs.gov/​healthit/​ahic/​quality_​instruct.html.

Persons wishing to submit written testimony, please contact Michelle Murray via e-mail at michelle.murray@hhs.gov.

72 FR 32850