1. A Semantic Approach to Health Care Quality Reporting
Chris Pierce (CCF)
Chris Deaton (Cycorp)
Brian Beck (EmCee Partners)
Chimezie Ogbuji (CCF)
Semantic Technology Conference
15 June 2009
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2. Outline Demands and complexity health care quality reporting
Current approaches to reporting
A semantic approach
Two different methods of semantic reporting
Evaluations

3. Health Care Quality Reporting
Government and Industry Groups
CMS
Leapfrog
National Quality Forum (NQF)
National Databases
STS Cardiac & Thoracic Surgery Databases
ACC National Cardiovascular Data Registries
ACS National Surgical Quality Improvement Program
3rd Party Payors (Insurance Companies)
Blue Cross Blue Shield
United Health
Anthem
Private Quality Tracking Groups
US News and World Report
Health Grades
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4. Increasing Reporting Obligations

5. Reporting Complexities Smoking/Tobacco Use History
STS Adult Cardiac Surgery Database
Present
Any tobacco use history
Used < 1 mo. of surgery
Current or recent cigarette smoker < 1 year of surgery
STS General Thoracic Surgery Database
2009 -
Chew user
Cigarette user
Pipe user
Other tobacco user
Days quit before surgery
History of cigarette smoking
Never
Quit > 1 mo. of surgery
Smoked < 1 mo. of surgery
ACC NCDR CathPCI Registry
History of tobacco use
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Question or Objectives
Population
Results
Summary
Conclusions

6. Reporting Complexities Surgical Site Infection
STS Adult Cardiac Surgery Database
All of: Wound reoperation (I&D)
Positive culture
Treated with antibiotics
STS General Thoracic Surgery Database
Two of: Wound reoperation (I&D)
ACS National Surgical Improvement Program
One of: Purulent drainage
Wound reop or dehisces
Abscess/other sign of infect
Diagnosis by physician
The “divider” may be used to divide portions of your presentation:
Question or Objectives
Population
Results
Summary
Conclusions

7. Typical Reporting Process

8. Problems with Typical Approach
Redundant and costly
Same data collected multiple times
Managing multiple databases with overlapping content plus separate databases for research
Inconsistent
Same measures may be collected differently in separate databases
Potential for reporting different results for same measures
Low data reusability for research
Changing definitions
Different definitions

9. A Semantic Approach

10. Semantic Reporting Requirements
Performance
Scalable
Fast
Automatable
Maintainability
Declarative
Reusable
Currency
Responsive to data changes
Responsive to logic changes

11. Overview of Semantic Approach

12. Smoking/Tobacco use History
Core Clinical Facts
Smoking/Tobacco use History
Any history of tobacco use
Date-time of data source
If tobacco used
What was used (cigs, cigar, chew, etc.)
Date quit
Date-time of procedure
Date-time of hospital admit

13. Surgical Site Infection
Core Clinical Facts
Surgical Site Infection
Surgical wound I&D procedure performed
Date-time of procedure
Positive culture
Culture results; Date-time of culture sample taken
Treatment with antibiotics
Antibiotic taken; Date antibiotic started and stopped
Purulent drainage, abscess or other sign
Sign; Date-time sign began
Diagnosis of a surgical site infection
Date-time of diagnosis
Fever >38 degrees C
Date-time of fever onset

14. Federation with SemanticDB™
A Semi-structured content management system
Supports:
Extensible RDF data model and OWL ontology
Automated, model-driven dual data representation in XML and RDF
Manual data entry via dynamically generated user interfaces
Electronic data import using a variety of protocols
Rich XML and RDF processing

15. Inferential Report Derivation
Ontological and Rule-based derivation of report variables and values from core clinical facts
Forward reasoning of selected entailments into expanded RDF graphs
Backward reasoning of additional entailments, if necessary, through queries at run time

16. Ontological Forward Reasoning
STS Adult Cardiac Surgery Variable 2410 OCarCong – Congenital Defect Repair
<owl:Class rdf:about="&sts;CongenitalDefectRepair">
<rdfs:subClassOf rdf:resource="&sts;MajorProcedure"/>
<owl:intersectionOf rdf:parseType="Collection">
<owl:Class>
<owl:complementOf>
<owl:unionOf rdf:parseType="Collection">
<rdf:Description rdf:about="&sts;VSDRepair"/>
<rdf:Description rdf:about="&sts;ASDRepair"/>
</owl:unionOf>
</owl:Class>
</owl:complementOf>
<rdf:Description rdf:about="&ptrec;SurgicalProcedure_congenital_heart_procedure"/>
</owl:intersectionOf>
<skos:definition>Indicate whether the patient had a congenital defect repair either in
conjunction with, or as the primary surgical procedure.</skos:definition>
<skos:prefLabel>OCarCong</skos:prefLabel>

17. Rule-Based Forward Reasoning
Derivation of hasHospitalization and PostOpInHospitalEvent in Notation 3 rules
{ ?HOSP a ptrec:Event_encounter_hospitalization;
dnode:contains ?HOSP_START_DATE, ?HOSP_STOP_DATE.
?HOSP_START_DATE a ptrec:EventStartDate; ptrec:hasDateTimeMin ?ENCOUNTER_START.
?HOSP_STOP_DATE a ptrec:EventStopDate; ptrec:hasDateTimeMax ?ENCOUNTER_STOP.
?EVT_DATE a ptrec:EventStartDate; ptrec:hasDateTimeMin ?EVT_START_MIN .
?EVT dnode:contains ?EVT_DATE ; a ?EVT_KIND .
?EVT_KIND log:notEqualTo ptrec:Event_encounter_hospitalization .
?EVT log:notEqualTo ?HOSP .
?EVT_START_MIN str:lessThanOrEqualTo ?ENCOUNTER_STOP.
?EVT_START_MIN str:greaterThanOrEqualTo ?ENCOUNTER_START } => { ?EVT csqr:hasHospitalization ?HOSP } .
{ ?IDX_OP a csqr:QualifyingOperation;
csqr:hasHospitalization ?HOSP.
?EVENT csqr:hasHospitalization ?HOSP;
cyc:startsAfterStartingOf ?IDX_OP } => { ?EVENT a csqr:PostOpInHospitalEvent } .

18. Rule-Based Forward Reasoning
Derivation of STS-ACS variable 2740 COpReGft – Reop for graft occlusion
{ ?OPERATION a csqr:PostOpInHospitalEvent;
cyc:startsAfterStartingOf ?MORBIDITY;
dnode:contains ?CABG.
?CABG a ptrec:SurgicalProcedure_vascular_coronary_artery_bypass .
?MORBIDITY a csqr:PostOpInHospitalEvent;
a ptrec:Event_morbidity_coronary_artery_bypass_graft_occlusion } => { ?OPERATION a sts:ReopForGraftOcclusion } .

19. Approaches to Semantic Reporting
Two methods being developed and evaluated
“Triple Store” approach
Stores expanded RDF graphs in relational triple store
Uses Cyc to query store and generate reports variable by variable
“In Memory” approach
Expands and queries individual graphs in memory to generate reports record by record on the fly

20. “Triple Store” Reporting

21. “In Memory” Reporting

22. Evaluating the Approaches
“Triple Store”
“In Memory”
Scalability ? +
Speed
Automation
Declarative
Reusable
Current Data -
Current Logic

23. Benefits of Semantic Reporting
Cost savings
Eliminate redundant data collection
Reduce data management costs
Reporting consistency
Guarantee reporting of same values for same measures
Data reusability
Same core data usable for reporting, research, marketing, etc.

24. Challenges of Semantic Reporting
Availability of structured data
EMRs often store data as narrative
Requires manual abstraction or text mining
Impact of temporal fuzziness on reasoning
Timing of medical events can be fuzzy or ambiguous
Requires careful rule construction and checks for missed cases
Agency requirements at odds
Requirements implement quality control through specific data collection UI requirements
Need to allow quality control with derivation logic

25. Acknowledgements Funding: CCF Growth Board
CCF Heart and Vascular Institute
Sponsorship:
Dr. Eugene Blackstone