1. Interoperability of Data and Knowledge in Healthcare Systems
A CAS-747 presentation by:
Reza Sherafat
March 28, 2006
Dept. Computing and Software
McMaster University
CAS 747: Software Architecture and Reverse Engineering

2. CAS 747: Software Architecture and Reverse Engineering Winter 2006
Agenda
Current trends in Healthcare
Clinical decision support systems
Data Interoperability problem
Data mining results as the source of knowledge
Knowledge interoperability
Integration of data mining results with clinical guidelines (plus some case studies)
Conclusion
References
CAS 747: Software Architecture and Reverse Engineering Winter 2006

3. Current trends in Healthcare
The Healthcare professionals are overwhelmed with information.
Preventable medical errors cause thousands of deaths each year and loss of billions of dollars.
Healthcare information systems are deployed for various purposes, telemedicine, patient care, Electronic Health Records and decision support.
A good start by many standards organizations to define and maintain healthcare standards.
HL-7 (most popular healthcare data standard)
In the Ontario provincial government has spent a total of $28.1 billion in Healthcare services [20] this reaches $142 billion throughout Canada [4].
CAS 747: Software Architecture and Reverse Engineering Winter 2006

4. Clinical decision support systems (CDSS)
Effectiveness of clinical decision support systems (a question to be answered)
Even a recommendation system should NOT to flood the practitioner with so many [irrelevant] cases and also should NOT ignore possible important cases.
Many different approaches to provide decision making support.
We focus on guideline-based CDSS that try to support “clinical best practices” at the point of care decision making.
Arden Syntax by HL-7
Guideline Interchange Format (GLIF)
CAS 747: Software Architecture and Reverse Engineering Winter 2006

5. CAS 747: Software Architecture and Reverse Engineering Winter 2006
Arden Syntax
The idea behind Arden Syntax is to have a simple, yet powerful enough procedural language that can encode the necessary logic for deciding upon a single problem.
Decision making knowledge is encoded as IF-THEN rules in separate Medical Logic Modules (MLM).
Each module is responsible for making a single decision and is run on an engine that can access the EHR systems. Based on the result of evaluation of the rules an action (an alert or reminder) is taken.
A library of modules
Modules have data sections that should be mapped to institution specific data repositories; the rest of the module is already ready to use.
CAS 747: Software Architecture and Reverse Engineering Winter 2006

6. CAS 747: Software Architecture and Reverse Engineering Winter 2006
Arden Syntax (Cont’d)
knowledge:
type: data_driven;;
data:
last_creat := read last {"Creatinine level"};
last_BUN := read last {"BUN level"}; ;;
evoke: ct_contrast_order;;
logic:
if last_creat is null and last_BUN is null then
alert_text := "No recent serum creatinine available. Consider
patient's kidney function before ordering contrast studies.";
conclude true;
elseif last_creat > 1.5 or last_BUN > 30 then
alert_text := "Consider impaired kidney function when
ordering contrast studies for this patient." ;
else conclude false;
endif;
action:
write alert_text || "\nLast creatinine: "||last_creat||" on: "||time of last_creat|| "\nLast BUN: "||last_BUN||" on: "||time of last_BUN ;
urgency: 50;;
end:
CAS 747: Software Architecture and Reverse Engineering Winter 2006

7. Guideline Interchange Format (GLIF)
Three different types are models are mentioned:
Guideline Models
Data models
Data mining models
A guidelines specification standard
Flowchart-like diagrams (Guideline Models)
3 levels of abstraction [3] :
Conceptual modeling
Computable level
Implementation details
CAS 747: Software Architecture and Reverse Engineering Winter 2006

8. Conceptual Modeling (Level 1)
The conceptual models have simple building elements (steps):
action step,
patient state step,
decision step,
branch step and
synchronization step
It is easy to build and understand models
Some steps may involve user interaction, access to a data source or triggering an event.
CAS 747: Software Architecture and Reverse Engineering Winter 2006

9. Second and third levels in GLIF
Computable level deals with encoding the decision making logic (expressions)
Implementation level is concerned with how to map and bind the variable to local (institution specific) medical records.
CAS 747: Software Architecture and Reverse Engineering Winter 2006

10. Data Interoperability
The semantics of the communication
The semantics convey the actual "meaning" of the message. The semantics is conveyed via a set of symbols contained within the communication. An external "dictionary", thesaurus, or terminology explains the meaning of the symbols as they occur.
A syntax for communication
The syntax defines the structure and layout of the communication. Common syntax representations include ASN.1, XML, X.12, HL7, IDL, etc.
Services to accomplish the communication
Examples include the post office, a telephone switchboard, SMTP, FTP, Telnet, RPC, ORB services, etc.
A channel to carry the communication
Examples of channels include written documents, telephones, network connections, satellite links, etc.
Source: [7]
CAS 747: Software Architecture and Reverse Engineering Winter 2006

11. Data Interoperability (Cont’d)
Three different types are models are mentioned:
Guideline Models
Data models
Data mining models
THE KEY IDEA: Through standardization
HL-7 has built a standard Reference Information Model (RIM)
RIM is in the form of a large class diagram that model the healthcare domain.
Some other XML based standards like Clinical Document Architecture (CDA) use RIM as their main data model.
CAS 747: Software Architecture and Reverse Engineering Winter 2006

12. Data Interoperability (Cont’d) RIM
Services
Stake holder
Organization
Person
Patient
Clinical Observation
CAS 747: Software Architecture and Reverse Engineering Winter 2006

13. Data mining results as the source of knowledge
Three different types are models are mentioned:
Guideline Models
Data models
Data mining models
Data mining research has been active in building models that can describe or predict.
Applications of data mining studies:
Likelihood of coincidence of particular diseases
Adverse drug usage
Diagnosis
Patient clustering based on risk factors
Verification of known medical knowledge
CAS 747: Software Architecture and Reverse Engineering Winter 2006

14. Knowledge interoperability
THE KEY IDEA: Through standards
Use standards for knowledge sharing and exchange
The mined knowledge should be incorporated into the guideline model to be used for decision making at the decision steps.
PMML: data mining knowledge is encoded using the PMML standard.
GLIF3: Medical knowledge is encoded in guideline models
CAS 747: Software Architecture and Reverse Engineering Winter 2006

15. Framework for interoperability of mined knowledge
CAS 747: Software Architecture and Reverse Engineering Winter 2006

16. Framework for interoperability of mined knowledge (Cont’d)
Three phases:
Knowledge preparation
Mining the patients data
Interoperation
To make both data and mined knowledge available at the point of care through use of standard
Interpretation
Access the knowledge base with the patient data that needs decision making
CAS 747: Software Architecture and Reverse Engineering Winter 2006

17. Integration of data mining results with clinical guidelines
Guideline Execution
Guideline modeling
Knowledge Extraction
CAS 747: Software Architecture and Reverse Engineering Winter 2006

18. Integration of data mining results with clinical guidelines (Cont’d)
Knowledge extraction
Building data mining models on [usually] large data warehouses
Guideline modeling
Building guideline models
PMML encoding
Institution specific data bounding
Guideline Execution
Execution engine will follow the flow defined in the guideline model
Accessing patient data from EMR systems
Interact with the healthcare personnel
Alert, recommend or remind
CAS 747: Software Architecture and Reverse Engineering Winter 2006

19. Integration of data mining results with clinical guidelines (Cont’d)
CAS 747: Software Architecture and Reverse Engineering Winter 2006

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Implementation
Extending Guideline Interchange Format3 (GLIF3) constructs
To support the new functionality needed for the data mining models
Guideline Execution Environment (GEE)
To execute the guideline models, and access/interpret the data mining models
Provision of the mined knowledge as webservices when the knowledge base is not available locally
Very helpful for small devices; e.g. handheld computers
CAS 747: Software Architecture and Reverse Engineering Winter 2006

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Case study
A decision tree classifier
For melanoma skin cancer diagnosis [6]
CAS 747: Software Architecture and Reverse Engineering Winter 2006

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Case study (Cont’d)
CAS 747: Software Architecture and Reverse Engineering Winter 2006

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Guideline Execution Environment
The guideline execution environment widget
Guideline selection
list
Different flows within a
guideline in execution
CAS 747: Software Architecture and Reverse Engineering Winter 2006

24. CAS 747: Software Architecture and Reverse Engineering Winter 2006
Guideline’s Meta Model
Data mining decision nodes
as an ontology class
Data mining decision nodes
slots
CAS 747: Software Architecture and Reverse Engineering Winter 2006

25. CAS 747: Software Architecture and Reverse Engineering Winter 2006
Guideline modeling
Slot widget to
specify the new
attributes of a
data mining
decision node
CAS 747: Software Architecture and Reverse Engineering Winter 2006

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Conclusion
We described:
A knowledge management framework to for data mining results;
The environment in which the framework can be deployed;
How to integrate data mining results in clinical guidelines;
How knowledge interoperability is achieved.
CAS 747: Software Architecture and Reverse Engineering Winter 2006

27. CAS 747: Software Architecture and Reverse Engineering Winter 2006
References
Incorporating Data Mining Applications into Clinical Guidelines, R. Sherafat, K. Sartipi, The 19th IEEE International Symposium on Computer-Based Medical Systems, 2006
Data and Knowledge Interoperability in Distributed Healthcare Systems, R. Sherafat, K. Sartipi, The 13th Annual International Workshop on Software Technology and Engineering Practice, 2005
Guideline Interchange Format 3 (GLIF3),
Health Level-7 (HL-7),
Arden Syntax,
Data Management Group (DMG),
Rules for melanoma skin cancer diagnosis,
Version 3 Intermediate Tutorial - Working the HL7 Version 3 Methodology, George W. Beeler,
CAS 747: Software Architecture and Reverse Engineering Winter 2006

28. CAS 747: Software Architecture and Reverse Engineering Winter 2006
Questions ?
CAS 747: Software Architecture and Reverse Engineering Winter 2006