epis3: a semantically interoperable social network for syndromic surveillance and disease control...
TRANSCRIPT
EpiS3: a semantically interoperable social network for syndromic surveillance and disease control
Luciana Tricai Cavalini and Timothy Wayne CookNational Institute of Science and Technology – Medicine Assisted by Scientific Computing
Summary
• The problem• The current solution• Remaining challenges• A new approach• Implementation• Future steps
THE PROBLEMSyndromic Surveillance:
First cases detectedIndex case
Problem 1: Detecting Cases
Fever?Bleeding? Jaundice?
Problem 2: Decision Making
THE CURRENT SOLUTIONSyndromic Surveillance:
Current solution: Standardize the data model
The Current Solution: Issues
• Top-down data models– Risk of inaccurate or incomplete data
• Hospital/clinic centered applications– No records from uncovered populations
• Incipient Decision Support Systems (DSS)– Mostly academic projects in internal medicine
REMAINING ISSUESSyndromic Surveillance:
Problem is: Accuracy or Utility?Problem is: Accuracy or Utility?
Remaining Questions• How to collect data in the most opportune
moment?– At the point of care– In the household
• How to get data with proper…– ...accuracy...– ...granularity...
• ...that will allow implementation of useful DSS for syndromic surveillance?
Dr. Cool
Your patient: Jane
Updated her problem liston Apr 29, 2014 5:33pm- Fever: YES- Bleeding: YES- Location: Nose
Suspicious case of Acute Febrile
Hemorrhagic Syndrome
What to do
How to get...
...without creating another
data silo?
A NEW APPROACHSyndromic Surveillance:
Fever?Bleeding? Jaundice?
Harmonization
Multilevel Model-Driven Approach
Minimalistic,XML-based
MMD technology
MLHIM-based implementation
MedWeb 3.0 Plugin Suite
AFJHS appRabies
prophylaxis app
Hospital infection control
appBioterrorism
appPoisonous
animals appAnd so on…
IMPLEMENTATIONEpidemiological Surveillance Support System (EpiS3):
Acute Febrile Jaundice Hemorrhagic Syndrome (AFJHS) App
> 1 y/oFever 0-3 wks
Jaundice
AFJS
> 1 y/oFever 0-3 wksBleeding signs
AFHS
> 1 y/oFever 0-3 wks
Jaundice and Bleeding
AFJHS
Malaria blood smear test
Positive Negative
Treat malaria
Evaluate current epidemiological profile of the territory
HepatitisYellow FeverLeptospirosis
SepsisTyphoid Fever
AFJSDengueSepsis
MeningococcemiaTyphoid Fever
HantavirusOther Arbovirosis
AFHSHepatitis
Yellow FeverLeptospirosis
SepsisTyphoid Fever
AFJHS
ConceptConstraintDefinition
ReferenceModel
Concept Constraint Definition Generator (CCD-Gen)
www.ccdgen.com
CCD Library on CCD-Gen
www.ccdgen.com/ccdlib
AFJHS App Form on CCD-Gen
AFJHS App: CCD Schema
AFJHS App: Sample Data Instances
AFHS with spontaneous
bleeding
AFJHS App: Sample Data Instances
AFHS with tourniquet test
positive
AFJHS App: Sample Data Instances
AFJS with mucosa jaundice
Already Implemented:16 AFJHS simulated cases (all possible classifications)AFHS
- Spontaneous bleeding
- Tourniquet test +
AFJHS
- Mucosa- Skin- Both
AFJS - Spontaneous + mucosa
- Spontaneous + skin- Spontaneous +
both- Tourniquet +
mucosa- Tourniquet + skin- Tourniquet + both- Malaria
Negative
- Age- Fever- Fever duration- No signs + a R library that converts
the XML data instances into R data frames
FUTURE STEPSEpidemiological Surveillance Support System (EpiS3):
EpiS3: Future Steps
• App User Interface– Desktop and mHealth versions
• DSS Algorithms– Clinical evaluation– Messaging– Reporting
• EpiInfo Form Builder for MLHIM data
