THE USE OF PDAs IN LONGITUDINAL DATALONGITUDINAL DATA

COLLECTION

Dorean Nabukalu, George Pariyo, Stefan Peterson, Daniel Kadobera Daniel Kayiwa Jorn KlungsoyrDaniel Kadobera, Daniel Kayiwa, Jorn Klungsoyr,

Edward Galiwango, Bruce Macleod

IGANGA/MAYUGE DSS-UGANDA

Collaborating partnersCollaborating partners• Makerere University

– Faculty of Computing and Information TechnologyFaculty of Computing and Information Technology– Makerere University School of Public Health– Institute of Statistics and Applied Economics– Directorate of Information and Communication Technology (DICTS)

• University of Southern Maine (Bruce Macleod)

U i it f B (J Kl J• University of Bergen (Jorn Klungsoyr, Jan Obrestad)

• Karolinska Institutet• Karolinska Institutet

Background• It is located in the mid Eastern part of

Uganda, 118Km from Kampala, along the East African Highway

NebbiArua

Gulu

Adjumani

KatakwiMoroto

Kotido

Kitgum

Lira

Moyo

East African Highway

• The DSS had its first baseline census in 2005

MasindiNaka-songolaHoima

Kibaale Kiboga

Luwero

Apac

KAMPAL AM b d

JinjaIganga

Bugiri Bus ia

Mbale

Tororo

Kapchorwa

Pallisa

Kumi

Katakwi

Soroti

Kamuli

• The DSS had its first baseline census in 2005

• The DSA covers an area of 3931sq Km and

Kasese

MukonoMubendeKabarole

K b l

Mbarara

Rakai

Sembabule

Masaka

Kalangala

g

Mpigi

Bushenyi

RukungiriNtungamo

KENYA

TANZANIA• The DSA covers an area of 3931sq.Km and currently follows up a population of 65515 people two times a year

Kabale TANZANIA

ObjectivesObjectives• Develop a computer based data collection

system to:

– maximize the data collection speed

minimize data collection costs while at the same time– minimize data collection costs, while at the same time

– maintaining or improving on the accuracy/quality of g p g y q ythe collected data

MethodologyMethodology• The study was conducted in one village of the DSA y g

which has a total of approximately 300 households

• The following steps were taken:Questionnaire designD t d l dData download Interviewer training and Data collectionData uploadData upload

Step 1: Questionnaire designData collection forms were designed in Epihandy

Household FormLocation form

Pregnancy formPregnancy form

Step2: Download to PDA

• This was done manually through Active Sync

• Epihandy forms and data are downloaded to PDA as shown dow o ded o s s owin the pictures

Step 3: Data collectionStep 3: Data collection

• 5 interviewers were trained in PDA use f i d f t k i t PDAfor a period of two weeks prior to PDA field work

• The training sessions included both theory g yand practical

• The theory part was introducing them to the hand held computersthe hand held computers

• The practical part was taking them through the mobile HRS software on the gPDA

An enumerator conducting an interview

Step 4: Data UploadStep 4: Data Upload

At th d f h d d t ll l d d i t th• At the end of each day, data was manually uploaded into the server through synchronization

• Cleaning and editing of the collected data is done from the database within the office

• The above steps can be summarized in the diagram that follows

Data flow and managementg

Results/findings• The number of households visited per day with a PDA was• The number of households visited per day with a PDA was

almost double the number of households visited with paper

• Fewer errors were found during editing

• Reconciliation of migrations was possible• Reconciliation of migrations was possible

• An experienced paper based interviewer could easily adopt to the use of the PDA

• Reduced time for electronic availability of data (No need for• Reduced time for electronic availability of data (No need for data entry)

Challenges/problemsChallenges/problemsSoftware Related• More work needs to be done on the migration module

• The data transfer phase needs to be worked on soonp

• Searching for an individual takes a long time

• More work needs to be done on the location module

i d fid i li• Data security and confidentiality

Challenges/problems cont’dChallenges/problems cont dOther Cases• The search engine can not be used if proper• The search engine can not be used if proper

identification details are not known

D t l d i th f b tt h i• Data loss during the process of battery changing

• Its faint light causes strain on the Interviewer’s eyes

• Limited screen size

• Lack of adequate technical support

RecommendationsRecommendations

N d l til t id d t l• Need non-volatile memory to avoid data loss

• Immediate data transfer methods should be put in place ed ate data t a s e et ods s ou d be put p ace

• Software developers to continue fixing remaining bugs

• The software is open source and we are looking for sites who would like to participate in the next phase of field p p ptests

ConclusionConclusion• The PDA data collection systems are the wayThe PDA data collection systems are the way

to go for HDSS

• The users’ and respondents’ preferences further indicated that PDA based data collection is acceptable and welcome in the DSS communities

Acknowledgement• InDepth Network• InDepth Network• Makerere University• Host Districts: Iganga and Mayuge • System developers• Funding Agencies

– Sida/SAREC – The Rockefeller Foundation

• Iganga/Mayuge DSS Management• Iganga/Mayuge DSS Staff• Iganga/Mayuge DSA communities

THANK YOU