quality measurement – clinical decision support harmonization proposal
Post on 23-Feb-2016
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Quality Measurement – Clinical Decision Support Harmonization
Proposal
Goal• Leverage existing relevant work to establish
modularized and harmonized standards that meet Quality-related business needs– Includes quality measurement and CDS
• Initial target timeframe: January 2014 ballot cycle– Work with TSC to extend ballot deadlines– Continue work past ballot submission
Proposed Approach
Foundational Components
Clinical data model Expression/logicDocument structureVocabularies Templates and meta-data
Quality Measurement-Specific Components
TBD, as needed
CDS-Specific Components
E.g., CDS usage context, such as CDS target = Spanish-speaking patient
Quality Measurement Standards
HQMF R2.X
CDS Standards
CDS Knowledge Artifact IG, DSS IG
Proposed Approach – DetailsObjective Jan. 2014 Ballot Strategy
(materials due in ~2 mo.)Long-Term Approach
Harmonize clinical data model, templates, and terminology for quality measurement and CDS
Modify vMR and templates as required to ensure encapsulation of QDM and QRDA semantics
1. Develop DMIM, templates, and “green” versions
2. Use FHIR and request enhancements
Separate out and harmonize expression logic
Separate out expression logic from HQMF
Develop common expression logic approach if possible
Develop common expression logic approach
Harmonize document specifications and implementation guides
Update existing specifications (HQMF, CDS KA IG, DSS IG ) to use common components
Update existing specifications to use common components
PSSs and Specifications (Jan. 2014)• vMR Logical Model update• vMR XML IG update• vMR Templates IG update• Expression Logic DAM and IG for Quality
Measurement & CDS• HQMF R2.X update• CDS Knowledge Artifact IG update• Decision Support Service IG update• Others updates as needed if QDM updated –
QRDA Cat. I/III, C-CDA
EXPRESSION LOGIC
The Foundation
• Clinical Quality is a data-centric problem– Quality measurement seeks to measure clinical indicators– Clinical decision support seeks to identify established patterns and
offer relevant guidance– Both these activities at their core involve set-based data processing– As such, they are most naturally and easily expressed in a data-
language• set-focused – deals with computation of sets of information (e.g.
encounters, medications, lab results, etc.)• expressive – express as naturally as possible the computation of
those sets (e.g. composable, reusable, flexible)• complete – provide mechanisms so that the computation can be
arbitrarily complex (e.g. computational, interval, set operations)
Operations
• Set Operations– Retrieve, Filter, Union, Intersect, Extend, Project, Join
• Computational– Comparison, Logical, String Manipulation, Arithmetic, etc.
• Interval– During, Between, Overlaps, Meets, etc.
• Aggregate– Count, Min, Max, First, Last, N
HQMF Operations• Data Criteria
– Retrieve– Filter w/ specific operations and attributes
• Temporally Related Information– Semi-join w/ temporal conditions
• Excerpt– Aggregate Computation
• Outbound Relationship– Semi-join w/out temporal conditions
• Grouper– Union and Intersection
• Population Criteria– Logical Operations (AND/OR/NAND/NOR/XOR)
• Measure Observations– Computation
An Approach to Harmonization
• Define the logical set of operations– Described above
• Define each of the HQMF constructs in terms of those operations– such that an existing HQMF document becomes a syntactic
short-hand for an equivalent underlying expression in terms of the foundational elements
• Note that the foundational elements are independent of any particular data model, but the syntactic short-hands need not be...
Data Criteria - Retrieval
Data Criteria – Value Filter
Data Criteria – Value Filter (cont)
Temporally Related Information
Excerpt
Outbound Relationship
• Same as temporally related information, but uses relationship definition as conditions instead of temporal operators
Grouper
Population Criteria
Measure Observation
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