Transcript Incorporating a Fingerprinting System into the

Incorporating a Fingerprinting
System into the Western Kenya
Health and Demographic
Surveillance System, 2009
Ezekiel Chiteri, Wilfred Ijaa
Frank Odhiambo, Marta Ackers, Allen Hightower, James Kwach,
Kayla Laserson
INDEPTH CONFERENCE
27th October 2009
KEMRI/CDC Research and Public Health Collaboration
Kisumu, Kenya
Background(1)
• KEMRI/CDC has multiple projects – Health and demographic
surveillance System (HDSS), malaria, TB and HIV research
• Projects assign their participants unique study IDs
– Some projects distribute ID cards
• Projects operate in same study area, same study pop
• Individuals can enroll in one or more projects
– Some projects do not allow cross-study participation
• Health facility (HF) surveillance conducted as follows
– In-patient conducted in 1 hospital
– Out-patient conducted in 3 clinics
– HIV and TB care and treatment programs conducted in all
health facilities
• The current method of linkage between HDSS and HF/projects
is through a search engine tool
Background (2)
“SINGLE”
POPULATION
KEMRI/CDC &
OTHER MEDICAL
HEALTH
ORGANIZATIONS
Background (3)
Challenges to linking individuals from HDSS data
to HF/ studies information
•
•
•
•
Misplaced ID cards
Name similarities
Migrations reconciliation
Non uniform identification of participants by
different projects/studies
Objective
To develop an efficient identification system for
the whole organization:
• To be used for linking the HDSS to all
HF/projects’ data
• Scalable and adaptable
• Acceptable
• Cost effective
Methodology
• Design a fingerprint system
– Database design
– Selection of hardware and software development kits
(SDKs)
– User application design
• Develop SOPs and procedures for the fingerprint system
• Ethical clearance -obtained from the KEMRI Ethical
Review Committee and the CDC Institutional Review
Board
• Implementation of the fingerprint system
• Post implementation review
Database Design
Front-end Design
System Specification
(HARDWARE)
• Finger Print Readers
– Microsoft Fingerprint Reader
– Digital persona
• Computers
– Pentium Processor (i386) (2.0 GHz or
later)
– 1GB RAM or more
– 5GB of free space in the hard disk.
System Specification
(SOFTWARE)
• Database and SDK
– Fingerprint SDK 2009 for Windows by
GriauleBiometrics
– MS SQL SERVER 2005
• Operating System
– Windows XP Professional
System Costs
Item
Recommended Brand
Fingerpt Reader Microsoft fingerprint reader
Fingerprint SDK 2009 by
SDK
griaulebiometrics
Any Brand with the above
PC
specifications
Average Cost Per work
Station
Average
Cost
$50
$36
$1200
$1286
Implementation
STEPS:
• System deployment and user training
• Health facility and additional study sites’ data
collection points
• HDSS household surveillance data collection
points
• Fingerprint data consolidation
Fingerprint Collection Points
POPULATION
POINT OF OPERATION
TOOLS
Health facility
Mobile Surveillance
PC, Laptop, Tablet PC
Other studies
Fingerprint Reader
Data Point 4
Data Point 5
Fingerprints
Centralized or
Replicated
Database
Results
• 868 fingerprints collected
• 1352 patient visits recorded in the hospitals
• Patient visits include multiple visits by the
individuals
– Fingerprints are enrolled only once
– Enrolled fingerprints used to identify
individuals in subsequent visits
• Children<1 were not fingerprinted
Limitations
• Children under 1 year were not finger printed
due to a low success rate in enrolling their
finger prints during the pilot stage
Conclusions
• High acceptability at current collection points
• Feasible means of individual identification in
health and demographic surveillance research
• It takes short time to enroll/identify
individuals
What next?
• Measuring the success rate of fingerprint
identification
• Build fingerprint database of all residents
using HDSS surveillance
• Measure acceptability in our surveillance area
Acknowledgements
• Colleagues (Programmers)
• DSS data managers and field
workers
• Study participants
• KEMRI/CDC
• PEPFAR