1. A Description Logics Approach to Clinical Guidelines and Protocols
Stefan Schulz Department of Med. Informatics Freiburg University Hospital Germany
Udo Hahn Text Knowledge Engineering Lab Freiburg University, Germany
As you see, the title is somewhat different

2. Formalization of CGP
Up until now: CGPs are treated as plans: actions, states, transition functions. Methodologies from the AI Planning & OR Scheduling community
Why not: Use Formal Ontology methodology to represent (at least, selected) aspects of CGPs in order to support consistency, fusion, and modulariziation of CGPs
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So what we propose is to perform an

3. Our Proposal
Ontological analysis of CGPs (cf. Gangemi, Guarino et al.)
Introduce basic categories (e.g. event, state,…)
Axiomatize foundational relations (e.g. is-a, …)
Classification of domain entities
Study interrelations between domain entities
Choose a logic framework for the formalization of the ontology
Representation: Description Logics (subset of predicate calculus)
Reasoning: Taxonomic Classifiers (e.g., FaCT, RACER)

4. Basic Categories Continuants vs. Occurrents (Events)
Physical Objects, Substances, Organisms, Body Parts
Processes, states, Actions, Courses of Diseases, Treatment Episodes
Individuals vs Concept Classes
my left Hand, Paul’s Diabetes, Appendectomy of Patient #230997
Hand, Diabetes, Appendectomy
There is mainly consensus on basic ontological foundations such as
How do CGPs fit into this framework ?

5. Guidelines and Episodes
Proposal: A Guideline G can be mapped to a set of classes of clinical episodes: E = {E1, E2,…, En}
The elements of E correspond to all allowed paths through a Guideline G
Each element of E represents - as a conceptual abstraction – a class of individual clinical episodes
We propose
As an example we take this quite simplified protocol

6. Simplified Chronic Cough Guideline
Chronic Cough [CC]
Phys.Exam
[PE]
Anamnesis [AN]
Clinical Episodes
E1 = (CC, AN, PE, SM, CS, NC)
E2 = (CC, AN, PE, SM, CS, CO, CX)
E3 = (CC, AN, PE, NS, CX)
E4 = (CC, PE, AN, SM, CS, NC)
E5 = (CC, PE, AN, SM, CS, CO, CX)
E6 = (CC, PE, AN, NS, CX)
Smoking
[SM]
Non Smoking [NS]
The following episodes can be compiled out fo this guideline
Cessation of Smoking[CS]
Temporal sequence of events
No Cough [NC]
Cough
[CO]
Chest X-Ray [CX]

7. Simplified Chronic Cough Guideline
Chronic Cough [CC]
Phys.Exam
[PE]
Anamnesis [AN]
Clinical Episodes
E1 = (CC, AN, PE, SM, CS, NC)
E2 = (CC, AN, PE, SM, CS, CO, CX)
E3 = (CC, AN, PE, NS, CX)
E4 = (CC, PE, AN, SM, CS, NC)
E5 = (CC, PE, AN, SM, CS, CO, CX)
E6 = (CC, PE, AN, NS, CX)
Smoking
[SM]
Non Smoking [NS]
Cessation of Smoking[CS]
Clinical event
No Cough [NC]
Cough
[CO]
Chest X-Ray [CX]
Temporal sequence of clinical events

8. Simplified Chronic Cough Guideline
Chronic Cough [CC]
Phys.Exam
[PE]
Anamnesis [AN]
Clinical Episodes E1 = (CC, AN, PE, SM, CS, NC)
E2 = (CC, AN, PE, SM, CS, CO, CX)
E3 = (CC, AN, PE, NS, CX)
E4 = (CC, PE, AN, SM, CS, NC)
E5 = (CC, PE, AN, SM, CS, CO, CX)
E6 = (CC, PE, AN, NS, CX)
Smoking
[SM]
Non Smoking [NS]
Which basic relations can be used to further describe this guideline
Cessation of Smoking[CS]
Temporal sequence of clinical events
No Cough [NC]
Cough
[CO]
Chest X-Ray [CX]

9. Basic Relations

10. Cessation of Smoking[CS]
Basic Relations
Taxonomic Order (is-a) relates classes of specific events to classes of general ones: is-a(CX, XR)  def x: CX(x)  XR(x)
Cough [CO]
Chronic Cough [CC]
Phys.Exam
[PE]
Anamnesis [AN]
Drug Abuse [DA]
Smoking
[SM]
Non Smoking [NS]
Cessation of Smoking[CS]
X-Ray [XR]
No Cough [NC]
Cough
[CO]
Chest X-Ray [CX]

11. Heart Auscul tation [HA] Cessation of Smoking[CS]
Basic Relations
Taxonomic Order (is-a) relates classes of specific events to classes of general ones: is-a(CX, XR)  def x: CX(x)  XR(x)
Mereologic Order (has-part) relates classes of events to classes of subevents x: PE(x)  y: HA(y)  has-subevent(x,y)
Cough [CO]
Chronic Cough [CC]
Phys.Exam
[PE]
Anamnesis [AN]
Drug Abuse [DA]
Smoking
[SM]
Non Smoking [NS]
Heart Auscul tation [HA]
Social Anamn esis [AN]
Cessation of Smoking[CS]
X-Ray [XR]
No Cough [NC]
Cough
[CO]
Chest X-Ray [CX]

12. Heart Auscul tation [HA] Cessation of Smoking[CS]
Basic Relations
Taxonomic Order (is-a) relates classes of specific events to classes of general ones: is-a(CX, XR)  def x: CX(x)  XR(x)
Mereologic Order (has-part) relates classes of events classes of subevents x: PE(x)  y: HA(y)  has-subevent(x,y)
Temporal Order (follows / precedes) relates classes of events in terms of temporal succession
x: NSCCGL(x)  y: CXCCGL(y)  follows(y,x)
Cough [CO]
Chronic Cough [CC]
Phys.Exam
[PE]
Anamnesis [AN]
Drug Abuse [DA]
Smoking
[SM]
Non Smoking [NS]
Heart Auscul tation [HA]
Social Anamn esis [AN]
Cessation of Smoking[CS]
X-Ray [XR]
No Cough [NC]
Cough
[CO]
Chest X-Ray [CX]

13. Modelling Pattern K L T S transitive relations event concepts
 has-subevent
 precedes
is-a

14. Modelling Pattern K L T S U KU LU transitive relations
event concepts definition of U U KU LU
transitive relations
 has-subevent
 precedes
is-a

15. Modelling Pattern K L T S U KU E UE LU SE transitive relations
event concepts definition of U
definition of E U KU E UE LU SE
transitive relations
 has-subevent
 precedes
is-a

16. Modelling Pattern K L T S U KU LU E UE KU LU SE transitive relations
event concepts definition of U
definition of E UE inherits properties of U U KU LU E UE KU LU SE
transitive relations
 has-subevent
 precedes
is-a

17. Modelling Pattern K L T S U KU LU E UE KU LU SE F transitive relations
event concepts definition of U
definition of E UE inherits properties of U definition of F as a subconcept of E U KU LU E UE KU LU SE F
transitive relations
 has-subevent
 precedes
is-a

18. Modelling Pattern K L T S U KU LU E KU LU UE SE F UE KU LU SE
event concepts definition of U
definition of E UE inherits properties of U definition of F as a subconcept of E F inherits properties of E U KU LU E KU LU UE SE F UE KU
transitive relations
 has-subevent LU SE
 precedes
is-a

19. Modelling Pattern K L T S U KU LU E KU LU UE SE F UE KU TF LU SE
event concepts definition of U
definition of E UE inherits properties of U definition of F as a subconcept of E F inherits properties of E F, additionally, has a T which occurs between U and S U KU LU E KU LU UE SE F UE KU TF
transitive relations
 has-subevent LU SE
 precedes
is-a

20. Modelling Pattern K L T S U KU LU E KU LU UE SE F UE KU TF LU SE
event concepts definition of U
definition of E UE inherits properties of U definition of F as a subconcept of E F inherits properties of E F, additionally, has a T which occurs between U and S inferences / constraints (formalization see paper) U KU LU E KU LU UE SE F UE KU TF
transitive relations
 has-subevent LU SE
 precedes
is-a

21. Modelling Pattern K L T S U KU LU E KU LU UE SE F UE KU TF LU SE
event concepts definition of U
definition of E UE inherits properties of U definition of F as a subconcept of E F inherits properties of E F, additionally, has a T which occurs between U and S inferences / constraints (formalization in Desciption Logics - see paper) U KU LU E KU LU UE SE F UE KU TF
transitive relations
 has-subevent LU SE
 precedes
is-a

22. Benefits
Description Logics implementations allow taxonomic classification and instance recognition.
Checking of logical integrity in the management, cooperative development and fusion of CGPs
Detecting redundancies and inconsistencies, e.g., conflicting orders when applying several CGPs simultaneously to one clinical case (multimorbidty, proliferation of CGPs)
Auditing of concrete instances (cases) from the Electronic Patient Record for CGPs compliance

23. Discussion First sketch of a beginning research project
Based on Description Logics (not necessarily)
Up until now, not all (temporal) inferencing capabilities are supported
Needs to be validated
Recommended for further investigation
Tool: OilED Knowledge editor (oiled.man.ac.uk) with built-in FaCT classifier
Theory: Baader et al (eds.) The Description Logics Handbook

24. Thank You ! Stefan Schulz
Department of Medical Informatics Freiburg University Hospital
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