Capturing Provenance, Evolution and Modification of ... · An Ontology Based Scheme for Formal Care...
Transcript of Capturing Provenance, Evolution and Modification of ... · An Ontology Based Scheme for Formal Care...
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Capturing Provenance, Evolution and Modification of Clinical Protocols via a
Heterogeneous, Semantic Social Network
George Drosatos Nick Portokallidis, George Drosatos and Eleni Kaldoudi
School of Medicine, Democritus University of Thrace,
Alexandroupoli, Greece
This work was supported by eCP: Electronic Clinical Protocols project (MIS 375876), funded under the Greek National Programme Thales, co-funded by the European Commission.
Partially, this work was supported by the FP7-ICT project CARRE (No. 611140), co-funded by the European Commission.
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Aim
A novel approach to describe, organize, manage, trace, use and reuse clinical protocols, based on a heterogeneous semantic social network
• The proposed approach allows – Semantic tagging – Semantic enrichment
• Main advantages – Tracing protocol provenance, evolution and modifications – Protocol meta-description, irrespective of protocol source format – Interlinking to related scientific sources (e.g. scientific publications,
PHR, etc.) and bodies (e.g. protocol issuing bodies, hospitals, etc.)
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BACKGROUND
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Formal care plans
• Clinical guidelines Systematically developed recommendations to address various clinical problems
• Clinical protocols
Detailed algorithms on how to address a particular clinical problem (based on guidelines)
• Care pathways
Care algorithms integrating multidisciplinary tasks for patient care in and outside the hospital (based on guidelines)
• Other, e.g. clinical trial protocols, clinical practice guidelines, …
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Examples of formal care plans
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State of the art
• Protocol description languages GLIF, EON, Asbru, GUIDE, PROforma, PLAN, …
• Protocol execution engines and management platforms GLEE, SAGE, DeGeL, NewGuide, SpEM, Tallis, ArezzoTM, HeCaSe2, ...
• Current unmet needs
– Choose the right protocol – Choose the right modification of a protocol (to meet local set-up) – Trace protocol use and modification history – Trace to protocol provenance, including medical evidence and issuing body – Record outcomes of protocol clinical application (e.g. for protocol evaluation)
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Our contribution
• Formal protocol meta-description – eCP ontology
• Versatile protocol ‘meta-repository’ – Heterogeneous social network
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ECP ONTOLOGY Kaldoudi, E., Drosatos, G., Portokallidis, N. and Third, A., 2016. An Ontology Based Scheme for Formal Care Plan Meta-Description. In XIV Mediterranean Conference on Medical and Biological Engineering and Computing 2016 (pp. 785-790). Springer International Publishing.
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Conceptual model of care plan meta-description
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Conceptual model of care plan meta-description
formal care plan
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Conceptual model of care plan meta-description
formal care plan
title
genre type
related health issue
description
has
1…N
0…1
1 ge
nera
l de
scrip
tion
clas
sific
atio
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has
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Conceptual model of care plan meta-description
formal care plan
title
genre type
related health issue
description
has
1…N
0…1
1
issuing body evidence source
0…N
1
is issued by is endorsed by
1…N ge
nera
l de
scrip
tion
clas
sific
atio
n
has
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Conceptual model of care plan meta-description
formal care plan
title
genre type
related health issue
description
quality of evidence
low
very low
is a value of
has
0…1
1…N
0…1
1
has
issuing body evidence source
0…N
1
is issued by is endorsed by
1…N
strength of recommendation
high
moderate
strong weak
is a
valu
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nera
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Conceptual model of care plan meta-description
formal care plan
title
genre type
related health issue
description
quality of evidence
low
very low
is a value of
observable
observable condition
is part of
1…N
initiated by
has
1…N 0…1
1…N
0…1
1
has
issuing body evidence source
0…N
1
is issued by is endorsed by
1…N
strength of recommendation
high
moderate
strong weak
is a
valu
e of
ge
nera
l de
scrip
tion
clas
sific
atio
n
qual
ity &
leve
l of
reco
mm
enda
tion
has
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Conceptual model of care plan meta-description
formal care plan
title
genre type
related health issue
description
quality of evidence
low
very low
is a value of
observable
observable condition
is part of
1…N
initiated by
has
1…N 0…1
1…N
0…1
1
outcomes
has
1…N
issuing body evidence source
0…N
1
is issued by is endorsed by
1…N
strength of recommendation
high
moderate
strong weak
is a
valu
e of
resource requires
0…N
gene
ral
desc
riptio
n
clas
sific
atio
n
qual
ity &
leve
l of
reco
mm
enda
tion
has
has
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Conceptual model of care plan meta-description
formal care plan
title
genre type
related health issue
description
quality of evidence
low
very low
is a value of
observable
observable condition
is part of
1…N
initiated by
source file
format location
copyright
1…N
has
1…N 0…1
1…N
0…1
1
outcomes
has
1…N has
issuing body evidence source
0…N
1
is issued by is endorsed by
1…N
strength of recommendation
high
moderate
strong weak
has
is a
valu
e of
resource requires
0…N
gene
ral
desc
riptio
n
clas
sific
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n
qual
ity &
leve
l of
reco
mm
enda
tion
has
has
identifier
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Conceptual model of care plan meta-description
formal care plan
title
genre type
related health issue
description
quality of evidence
low
very low
is a value of
observable
observable condition
is part of
1…N
initiated by
source file
format location
copyright
1…N
has
1…N 0…1
1…N
0…1
1
outcomes
has
1…N has
issuing body evidence source
is a deviation of
0…N
1
is issued by is endorsed by
1…N
strength of recommendation
high
moderate
strong weak
has
is a
valu
e of
resource requires
0…N
gene
ral
desc
riptio
n
clas
sific
atio
n
qual
ity &
leve
l of
reco
mm
enda
tion
has
has
identifier
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Ontology implementation
• Implemented with OWL2 using Protégé
• Integrated with commonly used standards and controlled vocabularies: – ICD-10, SNOMED-CT, QUDT, UO, GRADE and UMLS
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Ontology implementation
Available online in: http://purl.bioontology.org/ontology/ECP
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E-CLINPRO: CLINICAL PROTOCOL MANAGEMENT SYSTEM
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Social networks
Connections and relationships among humans
CarePages
on line digital content, resources, concepts…
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Object centered social networks
People interacting on a common social object
ResearchGate
Academia
PatientsLikeMe
on line digital content, resources, concepts…
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Heterogeneous social networks
Human and non-human entities are all treated alike, as actors
on line digital content, resources, concepts…
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patients formal care plans
medical evidence
health units
procedures medical conditions
observables
infrastructure
people
medical practice
information
issuing bodies
e-ClinPro heterogeneous network
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Clinical protocol provenance, evolution and modification
• Provenance – Issuing bodies – Clinical practice guidelines – Scientific evidence sources
• Evolution – Update of a previous version, e.g. due to new evidence
• Modification – Infrastructure limitations, e.g. lack of a diagnostic equipment – Clinical restrictions, e.g. due to concurrent clinical protocols – Patient choices and objections, e.g. due to religion – Insurance policy constraints, e.g. to firstly perform a lower cost procedure – Adaptation to local settings, e.g. different language – Restrictions due to comorbidities
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Example of clinical protocols’ relationships in the semantic social network
Acute kidney injury
(Guideline)
Acute coronary syndrome (Pathway)
Blood pressure in CKD
(Guideline)
NICE
KDIGO
University General Hospital
of Alexandroupolis
School of Medicine (DUTh)
Acute kidney injury (Protocol)
Issuing bodies Health units
Care plans
Hospital of Komotini "Sismanogleio"
Acute kidney injury (Protocol) - Greek
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Semantic tagging and interlinking
• Profile of clinical protocol based on the eCP ontology1
• Entry point: observables and observable condition described via the CARRE ontology2
• Issuing bodies and healthcare units are described following the SWRC ontology3
• Semantic tagging of medical terms with external resources via ICD-10 and SNOMED
• Medical evidence description based on the Bibliographic Ontology (via PubMed identifier and DOI)
1Kaldoudi, E., Drosatos, G., Portokallidis, N. and Third, A., 2016. An Ontology Based Scheme for Formal Care Plan Meta-Description. In XIV Mediterranean Conference on Medical and Biological Engineering and Computing 2016 (pp. 785-790). Springer International Publishing.
2Third, A., Kaldoudi, E., Gotsis, G., Roumeliotis, S., Pafili, K. and Domingue, J., 2015. Capturing scientific knowledge on medical risk factors. In K-CAP2015: 8th International Conference on Knowledge Capture. ACM. 3Sure, Y., Bloehdorn, S., Haase, P., Hartmann, J. and Oberle, D., 2005. The SWRC ontology–semantic web for research communities. In Portuguese Conference on Artificial Intelligence (pp. 218-231). Springer Berlin Heidelberg.
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Semantic tagging and interlinking
General Information
Evolution
Exit Points
Clinical Care Plan
Technical Information
eCP
Entry Point
CARRE
Issuing body
SWRC
Health Unit
observables conditions
resources
ICD10, SNOMED-CT
Evidence Source
Bibliographic Ontology (PubMed ID & DOI)
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E-CLINPRO: IMPLEMENTATION
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e-ClinPro implementation
• Backend – Server: NodeJS – API: LoopBack framework – Database: MongoDB
• Frontend – Visual Interface: AngularJS – Graph visualizations: Vis.JS
• Integration with – NCBO BioPortal API – PubMed API
• Available online in: http://iris.med.duth.gr/research/ecp
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E-ClinPro: Login
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E-ClinPro: Dashboard
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E-ClinPro: Visualizations
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E-ClinPro: Care plans list
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E-ClinPro: Care plan profile
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E-ClinPro: Edit care plan
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E-ClinPro: Initial condition builder
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CONCLUSION
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Work in progress
• Extensive ontology and system evaluation Structured interviews and focus groups of different types of system users, including experts, nurses, residents, and medical students
• Support relationships between doctors, patients, and protocols for clinical protocol evaluation based on the assessment of – The extent of clinical protocol use – Type and number of clinical protocol modifications – Outcomes of protocol clinical application
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THANK YOU Any questions?
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Acknowledgement
This work was financially supported by the projects
CARRE Project: Personalized patient empowerment and shared decision support for cardiorenal disease and comorbidities, Grant no. 611140, FP7-ICT (http://www.carre-project.eu/)
eCP: Development of electronic clinical protocols, (MIS 375876), the Greek National Programme Thales
both co-funded by the European Commission.