1. HQMF Change Review
Februrary 17th, 2017

2. Agenda Feedback Requests Measure Calculation Flows
Nested Library References
Terminology Section
Patient Context Guidance
Ratio and Composite Measure Examples

3. Feedback Requests Are the flow diagrams correct/useful?
Are the calculation narratives correct/useful?
Which approach is more useful for nested library references in the Human Readable?
Is the terminology section in the Human Readable correct?
Is the guidance on Patient context clear?
Do you have any specifications or worked examples of ratio measures?
Do you have any specifications or worked examples of composite measures?

4. Calculation Flow Diagrams
These diagrams depict per-patient calculation flow for HQMF eMeasures
For non-patient-based measures, the flow is repeated for each case for each patient
There is a diagram for each measure scoring type
Decision points (diamonds) correspond to the named population criteria types defined for HQMF
For consistency, decisions are always depicted with a Yes exiting to the right, and a No exiting down
The storage elements (inverted triangles) labelled “In” indicate that a patient is considered in a particular population

5. Calculation Narratives
The following calculation narratives are from the measure blueprint with a few changes that have been submitted back to the measure blueprint as comments.

6. Calculation Narratives - Proportion
Initial population (IPOP): Identify those cases that meet the IPOP criteria.
Denominator (DENOM): Identify that subset of the IPOP that meet the DENOM criteria.
Denominator exclusion (DENEX): Identify that subset of the DENOM that meet the DENEX criteria. There are cases that should be removed from the denominator as exclusion. Once these cases are removed, the subset remaining would reflect the denominator per criteria.
Numerator (NUMER): Identify those cases in the DENOM and NOT in the DENEX that meet the NUMER criteria. In proportion measures, the numerator criteria are the processes or outcomes expected for each patient, procedure, or other unit of measurement defined in the denominator.
Numerator exclusion (NUMEX): Identify that subset of the NUMER that meet the NUMEX criteria. Numerator Exclusion is used only in ratio eMeasures to define instances that should not be included in the numerator data.
Denominator exception (DENEXCEP): Identify those in the DENOM and NOT in the DENEX and NOT in the NUMER that meet the DENEXCEP criteria.

7. Calculation Narratives - Ratio
Initial population (IPOP): Identify those cases that meet the IPOP criteria. (Some ratio measures will require multiple initial populations, one for the numerator, and one for the denominator.)
Denominator (DENOM): Identify that subset of the IPOP that meet the DENOM criteria.
Denominator exclusion (DENEX): Identify that subset of the DENOM that meet the DENEX criteria.
Numerator (NUMER): Identify that subset of the IPOP that meet the NUMER criteria.
Numerator exclusion (NUMEX): Identify that subset of the NUMER that meet the NUMEX criteria.

8. Calculation Narratives - Continuous Variable
Initial population (IPOP): Identify those cases that meet the IPOP criteria.
Measure population (MSRPOPL): Identify that subset of the IPOP that meet the MSRPOPL criteria.
Measure population exclusion (MSRPOPLEX): Identify that subset of the MSRPOPL that meet the MSRPOPLEX criteria.

9. Calculation Narratives - Cohort
Initial population (IPOP): Identify those cases that meet the IPOP criteria.

10. Calculation Narratives - Individual Observations
For Ratio Measures:
For each case in the DENOM and not in the DENEX, determine the individual DENOM observations.
For each case in the NUMER and not in the NUMEX, determine the individual NUMER observations.
For Continuous Variable Measures:
For each case in the MSRPOPL and not in the MSRPOPLEX.

11. Calculation Narratives - Proportion Measure Rate
Proportion Measures
The “performance rate” is a ratio of patients meeting NUMER criteria, divided by patients in the DENOM (accounting for exclusion and exception). Performance rate can be calculated using this formula:
Performance rate = (NUMER - NUMEX) / (DENOM – DENEX – DENEXCEP)

12. Calculation Narratives - Measure Aggregates
Ratio Measures
Using individual observations for all cases in the DENOM and not in the DENEX, calculate the aggregate DENOM.
Using individual observations for all cases in the NUMER and not in the NUMEX, calculate the aggregate NUMER.
Ratio = aggregate NUMER / aggregate DENOM
Continuous Variable Measures
Using individual observations for all cases in the MSRPOPL and not in the MSRPOPLEX, calculate the aggregate MSRPOPL.
Score = aggregate MSRPOPL

13. Calculation Narratives - Stratification
When a measure definition includes stratification, each population in the measure definition should be reported both without stratification, and stratified by each stratification criteria. Specific programs may require reporting of performance rates. The performance rate is defined as
Performance rate = (NUMER - NUMEX) / (DENOM – DENEX – DENEXCEP)
For measures with multiple numerators and/or strata, each patient/episode must be scored for inclusion/exclusion to every population. For example if a measure has 3 numerators, and the patient is included in the first numerator, the patient should be scored for inclusion/exclusion from the populations related to the other numerators as well.

14. Shared Libraries
When an expression in a measure references an element from another library, the CQL will use the local library identifier as a qualifier:

15. Shared Libraries - Human Readable
Strawman:
Terminology components are included in the Human Readable (with a library qualifier if they are from a nested library). Logic definitions (functions and expressions) are not included, only referenced with a link to an html rendering of the CQL (same formatting and functionality as the primary library Human Readable, but focused on the functions and expressions)

16. Shared Libraries - Terminology in the HQMF
Should the terminologies from nested libraries be included in the HQMF?
If the intent of having the terminologies in the HQMF is backwards compatibility, then the answer should be yes, but we’re already breaking backwards compatibility (i.e. existing tooling cannot reliably reason about terminology use in a measure by looking at new HQMF) by adding direct-reference codes and changing terminology representation in the HQMF to use the valueset
Strawman:
Terminologies are included from all libraries in the HQMF, whether the primary measure library, or a nested library, recursively.

17. Shared Libraries - Include versions
When referencing a library, should we allow wildcards?
Simplest case is what tooling currently supports, specific match
Library A, version 1.0.0
Include A version 1.0.0
Include A, gets “latest” version
Highest version number
Strawman:
Current support is based on exact match versioning, unless the version is unspecified, in which case you get the latest version available in a given environment

18. Terminology in the Human Readable
Currently, terminologies are part of the QDM Data Criteria Section:

19. Proposed Terminology Section (w/ Default Profile)
Default profile entry is created based on analysis of the HQMF. If all valueset versions use the same profile, a default profile entry is created in the Human Readable
Note the direct-reference code example here is shown as defined in a shared library, so the “in Common” clause is used to differentiate

20. Proposed Terminology Section (w/o default profile)

21. Impact on Other Sections

22. Patient Context Guidance
Note that CQL allows both Patient and Population context expressions to be defined. For the purposes of measure definition with HQMF, population criteria expressions are required to be Patient context. The Population context is used here to illustrate the measure scoring calculation as applied to the populations, but the criteria expressions are always Patient context.

23. Measure Examples
To ensure adequacy of the HQMF and CQL-Based HQMF IG specifications for use with ratio and composite measures, we need specific examples of each of these types of measures.
We are requesting examples that, ideally, could be included as examples as part of the CQL-Based HQMF IG.
If IP concerns are an issue, we are also happy to keep the examples private but still use them to make sure the specifications are valid.