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Abstract #157638

Lazarus O. Odeny, MSc, Statistics and Informatics, Kenya Medical Research Institute/ Centres for Disease Cotrol (KEMRI/CDC), 1578, kisumu, 40100, Kenya, 254 57 2022902, LOdeny@ke.cdc.gov, Anja H. van't Hoog, MD, MSc, TB Operation Research, Centres for Disease Control (CDC), 1578, kisumu, 40100, Kenya, and Allen Hightower, MS, Statistics and Informatics, Centres for Disease Control (CDC), 1578, kisumu, 40100, Kenya.

We are conducting a tuberculosis prevalence survey in rural Western Kenya targeting 20,000 participants residing in an area monitored by a continuous demographic surveillance system (DSS). We demonstrate different data collection methods applied in the survey and discuss experiences gained. The survey uses Personal Digital Assistants (PDA) with integrated bar-code scanners for most field data collection, scannable data collection forms for a separate survey, and networked computer data entry with barcode readers for entry of laboratory data entry. Pre-existing DSS data are loaded into the PDA's to allow linking of survey data to DSS data. The PDA application, programmed using visual CE, prompts the interviewer for the need of an additional sputum sample, based on pre-defined combinations of symptoms. Data collected in PDA's are downloaded into a laptop in the field and queried, allowing any data issues to be discussed immediately with the interviewers. Flash drives are used to transport back up data to the data centre. Barcode scanners inserted in the PDA socket are used to read the participants unique study ID from pre-printed barcoded labels. Barcode scanners are used to track participants when they come for chest X-ray, and to track sputum samples and X-rays upon arrival in the laboratory and X-ray store respectively. Networked data entry of sputum smear results is done in the laboratory. The study number includes 1 check digit, to enable tracing of transcription errors when pre-printed barcode labels cannot be used (e.g. on microscopy slides). The data management process allows timely availability of clean data for reporting and provision of test results to study participants.

Learning Objectives:

• Evaluate efficiency and timeliness of the use of PDA in a large prevalence survey over other data capturing tools

Keywords: , Data Collection

Presenting author's disclosure statement:

Any relevant financial relationships? No
Any institutionally-contracted trials related to this submission?

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.