Dr. Luciana Cavalini's short presentation at the International Workshop on e-Health in Emerging Economies - IWEEE - in 2010.
See: http://www.mlhim.org http://gplus.to/MLHIM and http://gplus.to/MLHIMComm for more information about semantic interoperability in healthcare.
#mlhim #semantic_interoperability #health_informatics
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
Short presentation IWEEE 2010
1. Healthcare Knowledge Modelling
Projects for Multilevel-Based
Information Systems
Dra. Luciana Tricai Cavalini, MD, MSc, PhD
“Multilevel Healthcare Information Modeling”
Laboratory – Associated to INCT-MACC
UFF/UERJ
2. What do the citizens want?
• “How do you provide to me: • And better still:
▫ Safe ▫ Prevent me getting ill
▫ Effective ▫ And don’t harm me in the
▫ Reproducible process”
▫ State-of-the-art
▫ 21st Century medicine
▫ Wherever I am
▫ Whatever the time
▫ Whatever is wrong with me
16. Brazilian Healthcare Card
Investment:
•Federal Budget (until 2009) = R$327 million
•Unesco = R$74,3 million
•Total (until 2009) = R$401 million
Equivalent the the Aeolian Park in Bahia:
•90MW (it illuminates a 400,000 inhab city)
•Annual profit estimated in R$41 million
17. “A Unique Health Identifier alone won't prevent duplicate creation.
Make sure your strategy includes a focus on data quality and
data governance, too.”
Alex Paris, “Why a Unique Health Identifier Falls Short”
24. Single-Level Modelling Issues
Information is modelled in a way that “serves” the current needs of the healthcare system
The addition of new concepts or the change of existing concepts implies in re-factoring the whole
system (re-modelling, re-implementation, re-test, re-distribution)
High cost, slowness in the integration of new knowledge to the systems etc.
26. The MLHIM and openEHR Specifications
• Multilevel (or dual) Modelling: software development and
knowledge modelling are separated
• The Reference Model is implemented in software
• The knowledge is modelled in Concept Constraint
Definitions - CCDs (“archetypes” in the openEHR specs)
27. MLHIM and openEHR Models
Your application (EHR, CPOE etc)
MLHIM and openEHR
Knowledge Modelling
specifications
(CCDs or Archetypes)
Reference Model
28. FLOSS Available Tools (1)
• Implementations of the Reference Model:
▫ 2 Java Implementations by the openEHR Foundation
▫ 1 Grails implementation by Pablo Pazos (Uruguay)
▫ 1 Python Implementation by the MLHIM Laboratory
▫ 1 Ruby Implementation in course by a collaboration between a Japanese
research group and the MLHIM Laboratory
▫ 2 other implementation projects by the MLHIm Laboratory:
Lua
C++
33. FLOSS Available Tools (2)
• Archetype Editors (in ADL):
▫ Ocean Archetype Editor (Windows-only)
▫ LinkEHR (source code by request, there are bugs)
▫ LiU Archetype Editor (outdated)
• Templates Editors (in OET, OPT):
▫ None (only the proprietary Ocean Template Designer)
• Constraint Definition Designer Project (in XML):
▫ Only full-FLOSS and multiplatform tool
▫ Combined CCD and Template editor
▫ Baseado on Freemind, Plone and other ideas
35. FLOSS Available Tools (3)
• Archetype Repository:
▫ None (openEHR Foundation’s CKM is proprietary)
• The Healthcare Knowledge Component Repository Project:
▫ Repository of the XML Schemas of CCDs
▫ Based on Plone 4
▫ Functionalities:
All the famous Plone’s CMS and WFM features
XML Schema validation
API to CDD, OSHIP and the Multilevel Authoring for Guidelines (MAG)
38. FLOSS Available Tools (4)
• Terminology and Vocabulary Servers:
▫ LexGrid (http://www.lexgrid.org)
▫ LexBIG (http://preview.tinyurl.com/29ybeuf)
▫ Unified Medical Language System (UMLS)
(http://www.nlm.nih.gov/research/umls)
42. Knowledge Modelling (1)
• Our governance model proposes:
▫ Openness and transparency in decision making and operational
procedures
▫ Deliberative systems based on universal suffrage and
representativensess
▫ Cost-effective financing models, based on equitable and public
distribution of resources, including direct funding, collaborative work,
research and education projects etc.
▫ Coordinated and federation principles-based decentralization
43. Knowledge Modelling(2)
• Our governance model proposes :
▫ Preference for the use of validated instruments (including their
translations) for the development of CCDs
▫ Preferential use of knowledge modelling strategies derived from the
collaborative computing (web based or presential)
▫ Knowledge modelling might be based on expert panels in exceptional
situations
▫ Publication of the knowledge modelling artifacts on a public, open access,
FLOSS-based repository, maintained by the healthcare system
manager in each one of the three levels of government
44. My Conclusions
• I think that the path for the development of citizen-centered, longitudinal, semantic
coherent healthcare information systems is based on this tripod:
▫ Multilevel modelling
▫ Adoption of standardized terminologies
▫ Adoption of a Unique Citizen Identifier
• Emerging countries have some competitive advantages in healthcare IT:
▫ Usually, the Big Customer is just one (the government)
▫ We are starting almost from scratch
▫ Emerging countries are much more FLOSS-friendly
▫ All needed tools are available or being developen in FLOSS
• What’s next:
▫ Invite more partners to participate (government, academy, industry, third sector, FLOSS
community)
▫ Go to work!
45. Special Thanks to:
Tim Cook
Mike Bainbridge
Thank you! Sergio Freire
lutricav@vm.uff.br
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