The Agency for Healthcare Research and Quality (AHRQ) within the U.S. Department of Health and Human Services (HHS) has issued a Request for Information (RFI), “seeking ideas and input from the public … on successful strategies and remaining challenges in the creation of health IT-enabled quality measure development and reporting.” Comments are due by Aug. 20th.
Among the questions regarding quality measurement enabled by health IT being posed in the RFI are (following the link):
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 … in this area?
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?
15. Please describe scalable programs, demonstrations, or solutions (domestic or internationally) that show material progress toward quality measurement enabled by health IT.
To learn more, check out the complete RFI.
(Contributed by Erwin Gianchandani, CCC Director)
