Clinical Quality Workgroup Call Summary

The HIT Standards Clinical Quality Workgroup met today.  We were tasked by the HITSC with responding to certain sections of the Meaningful Use Stage 3 Request for Comments.

On Retiring Certain Meaningful Use Measures:
The workgroup seemed to be in agreement that after 80%, we should start looking at measures that reflect the use of data captured, rather than just testing for data capture.

On Care Plans:
We should look for use of certain basic data elements in care plans, and continue to promote standardization of care plan data elements.

On Clinical Quality Measures (CQMs):
We should consider redevelopment of quality measures that work with the information models and clinical data that is required under meaningful use, rather than simple retooling of existing quality measures.  We should also consider using HQMF Release 2.0.

On Technology for CQMs:
Data models are incredibly important.  We need to have a consistent data model across Health IT.  One speaker noted differences between the Health eDecisions work and the HQMF work (which was my principle complaint about it).

On having a Core set of CQM's:
This is rather challenging for specialty providers.  One speaker suggested that while we might want to focus on something that gives us big bang for the buck, it might not be applicable to every provider.  We didn't come to consensus on our position on this call.

On getting input for the HITPC and its workgroups:
Attending meetings in DC is rather limiting, should also consider getting input at other venues.  For patients, HITPC needs to go to them, not expect them to come to HITPC.

On use of Patient sourced data in CQMs:
Yes, but... the standards are still under development.  We agreed that it important to annotate the source of data.

On Process vs. Outcome Measures
Not an either/or question, rather an and/both.  There was agreement that measure suites containing related process and outcome measures would be quite valuable.

On Measure Development
It is important to support consistent use of data elements, models, vocabulary and value sets.  We need a measure of quality for quality measures.

That's about as far as we were able to get.  There were some 30 items we were tasked to address, and we were able to discuss almost all of them in the two hourse before we needed to finish the call.