Incorporating a Fingerprinting System into the Western Kenya

Health and Demographic Surveillance System, 2009

Ezekiel Chiteri, Wilfred IjaaFrank Odhiambo, Marta Ackers, Allen Hightower, James Kwach,

Kayla LasersonINDEPTH CONFERENCE

27th October 2009

KEMRI/CDC Research and Public Health CollaborationKisumu, 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

“SINGLE”POPULATION

KEMRI/CDC &OTHER MEDICAL

HEALTH ORGANIZATIONS

Background (2)

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 BrandAverage

Cost

Fingerpt Reader Microsoft fingerprint reader $50

SDKFingerprint SDK 2009 by

griaulebiometrics $36

PCAny Brand with the above

specifications $1200

Average Cost Per work Station $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

TOOLSPOINT OF OPERATION

Centralized or Replicated Database

Fingerprints

POPULATION

Health facility

Mobile Surveillance

Other studies

Data Point 4

Data Point 5

PC, Laptop, Tablet PC

Fingerprint Reader

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