Daily Rules, Proposed Rules, and Notices of the Federal Government
Health information technology (IT), such as, electronic health records (EHR) which may include clinical decision support and health information exchange, has seen a tremendous increase in adoption in recent years. Some institutions have successfully used health IT to generate health IT-enabled quality measures which may be retooled versions of established paper-based or administrative data-driven quality measures or (preferably) they are “de novo” quality measures that were developed with the capabilities of health IT in mind. These new health IT-enabled quality measures seek to leverage the use of electronic clinical data capture, analysis and reporting to measure and report electronically enabled quality measures in order to facilitate improvements in the quality of care provided. AHRQ supports research to improve health care quality through enhancements in the safety, efficiency, and effectiveness of health care available to all Americans. Through this RFI, AHRQ is seeking information related to successful strategies and/or remaining challenges encountered regarding the development of health IT-enabled quality measure development and reporting.
Health IT has the potential to advance quality measurement and reporting through the use of efficient automated data collection, analysis, processing, and its ability to facilitate information exchange among and across care settings, providers, and patients. Quality measurement enabled by health IT, referred to as health IT-enabled quality measurement, is an emerging field. There are numerous perspectives on how to achieve the future state of quality measurement. These varied perspectives sometimes include competing choices and challenges: (1) Underdeveloped or unavailable infrastructure (e.g., whether the measure set should be extensive or parsimonious); (2) incompleteness of the measure set (e.g., developing measures that matter to consumers, how to measure value); and (3) technology
In preparation for the development of this RFI, AHRQ generated a high-level overview of the current state of quality measurement through health IT, challenges facing the advancement of quality measurement enabled by health IT, a partial catalog of current efforts seeking to address those challenges, and, possibilities for the next generation of health IT-enabled quality measurement. This report, “An environmental snapshot — Quality Measurement Enabled by Health IT: Overview, Possibilities, and Challenges” can be found at
AHRQ is committed to garnering further insight in order to facilitate meaningful advancements in the next generation of quality measurement. Through this Request for Information AHRQ is seeking information on the building blocks of health IT-enabled quality measurement in terms of perspectives, practicalities, and priorities. Responses will be used in conjunction with deliberative activities to inform the development of a summary report to be released to the public approximately in summer 2013.
Respondents should note that this Request for Information is completely voluntary; respondents are welcome to address as many of the questions posed as they wish.
AHRQ would appreciate if you clearly indicate the number of the question area to which you are providing a response. This RFI is for planning purposes only. Responses to this are not offers, cannot be accepted by the Government to form a binding contract, and are not intended to influence regulation.
1. Briefly describe what motivates your interest in clinically-informed quality measures through health information technology. To what extent is your interest informed by a particular role (e.g., provider, payer, government, vendor, quality measure developer, quality improvement organization, standards organization, consumer advocate) in this area?
2. Whose voices are not being heard or effectively engaged at the crucial intersection of health IT and quality measurement? What non-regulatory approaches could facilitate enhanced engagement of these parties?
3. Some quality measures of interest have been more difficult to generate, such as measures of greater interest to consumers, measures to assess value, specialty-specific measures, measures across care settings (i.e., measures enabled by health information exchange), and measures that take into account variations in risk. Describe the infrastructure that would be needed to ensure development of such measures.
4. What health IT-enabled quality measures, communication channels, and/or technologies are needed to better engage consumers either as contributors of quality information or as users of quality information?
5. How do we motivate measure developers to create new health IT-enabled quality measures (which are distinct from existing measures which were retooled into electronically-produced quality measures) that leverage the unique data available through health IT? Please provide examples of where this has been successfully. What new measures are in the pipeline to leverage data available through health IT?
6. Describe how quality measurement and “real-time” reporting could inform clinical activity, and the extent to which it could be considered synonymous with clinical decision support.
7. Among health IT-enabled quality measures you are seeking to generate in a reliable fashion, including the currently proposed Meaningful Use Stage 2 measure set, what types of advances and/or strategies for e-measure generation if pursued, would support more efficient generation of quality measures?
8. Many EHR, HIE, and other health IT vendors are developing software code to support measures. Tools such as the Measure Authoring Tool (MAT) were created to improve efficiencies in the process of creating and implementing eMeasures. What additional approaches might be used to enable consistent, accurate, and efficient quality measurement when using health IT?
9. How do you see the establishment and adoption of data standards impacting the future of health IT-enabled quality measurement? For what types of quality measures should a combination of natural language processing and structured data be considered?
10. Much support has been voiced for the need of longitudinal data in quality measurement. What are the strengths and weaknesses of different information architectures and technologies to support health IT-enabled quality measurement across time and care settings? How can data reuse (capture once, use many times) be supported in different models? What examples might you provide of successful longitudinal health IT-enabled quality measurement (across time and/or across multiples care settings)?
11. What are the most effective means by which to educate providers on the importance of health IT-enabled quality measurement and how clinical information is used to support health IT-enabled quality measurement and reporting? How can providers be better engaged in the health IT-enabled quality measurement process?
12. What is the best way to facilitate bi-directional communication between vendors and measure developers to facilitate collaboration in health IT-enabled measure development?
13. To what extent do you anticipate adopting payment models that use quality measurement informed by electronic clinical records (as opposed to exclusively using claims data)? What strategies are you pursuing to gain access to clinical data and test the reliability of health IT-enabled clinical outcome measures? How do you anticipate sharing quality measure results with consumers and other stakeholders?
14. What tools, systems, and/or strategies has your organization been using to aggregate information from various EHRs and other health IT for use in quality measurement? What strategies is your organization pursuing to move toward greater automation in quality measurement?
15. Please describe scalable programs, demonstrations, or solutions (domestic or internationally) that show material progress toward quality measurement enabled by health IT.