RoseValloPoster2011TT .pdf


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Using an open source electronic data-capturing system
for clinical trials in low-income countries
Roselyne Vallo1, Halbou A. H. Bambara2, Audrey Jaussent3, Katai Chola4, Tapiwa Gundu5, G. Justus Hofmeyr6,
Chipepo Kankasa7, Stuart Katushabe8, Valérie Maréchal1, Nicolas Meda9, James Tumwine10, Nicolas Nagot1, Thorkild
Tylleskar11 and Philippe Van de Perre1 for the Promise-PEP ANRS 12174 study group
1

UM1/INSERM U1058/CHU, Montpellier, France; 2ANRS12174 trial, Ouagadougou, Burkina Faso; 3CHU, Montpellier, France; 4ANRS 12174 trial,
Lusaka, Zambia; 5ANRS 12174 trial, East London, South Africa; 6Effective Care Research Unit, Eastern Cape Department of Health/University of the
Witatersrand/university of Fort Hare, East London, South Africa; 7Dept of paediatrics and Child Health, School of medicine,Lusaka, Zambia; 8ANRS
12174, Mbale, Uganda; 9Ougadougou university, Ouagadougou, Burkina Faso; 10Dept of Paediatrics and Child Health, Makerere University, Kampala,
Uganda; 11Centre for International Health, Bergen, Norway

Background
Clinical trials require a data management tool to collect and manage the data. Many softwares exist and provide numerous services including online data entry. For organizations with limited
resources the choice of an open source software may be an option. OpenClinica (OC) is an open source clinical data management system built by Akaza research center and compliant with
regulatory guidelines for electronic data entry and management. This software runs on top of either the Postgres relational database or an oracle relational database. www.openclinica.org.

Objectives and Methods
The ANRS 12 174 trial (NCT00640263) is a randomised controlled trial conducted in Burkina Faso, Uganda, South Africa, Zambia and
enrolling 1500 mother-infant pairs. The mother-infant pairs are followed for 50 weeks with a total of 14 visits. For the duration of the
follow-up, a total of 34 case report forms (CRF) are required and 107 CRF are not required.
We report our experience in implementing OC software with the advantages, the limitation and our propose solutions

Results

+ POSITIVE POINTS +

- LIMITATIONS -

-OC meets the requirements of FDA 21 CRF Part 11 regulations and pass Computer Systems
Validation (CSV)
-Accessible via any web browser: nothing to install on machine

-Building an OC database requires strong computer skills (set up a server…) we pay Akaza
services for hosting and development of the database.
-OC offer the possibility to use coding applications, but doesn’t provide any coding application
we designed two coding applications: one for diseases (ICD10) and one for medicines (ATC).

-Snappy and intuitive user interface easy to use
-No programming skills required to build a study:

-OC doesn’t manage mix data entry (simple AND double for same CRF) we use simple data
entry, but we have two data entry operators: One operator enters the data and the other one
checks the data.
-The use of OC requires a decent connection which has been a challenge for us In this case
we use paper CRF, and we have this workflow:

Clinical staff
Fill

Paper
CRF

Data entry
Operator 1

-Library of CRF available in the web site : adverse event, demographics, Laboratory test…

Data
Entry

-For the help:
•Help file

Data entry
Operator 2

•Forum

Check
Data
Entry

•OC frequently asked questions
•OC issue tracker
-Akaza center offers services for fee on demand (building of database, hosting, etc…)
-Overview of the study:

- Overview of the follow up:

- Creation of validation rules
- Creation of notes and discrepancies
- Audit log

- The overview of the follow up is not sufficient for our complex study in order to manage the
visits of the participants, we have designed an MS ACCESS database:

- With OC we cannot create a complex calculated variables (involving several visit and several
CRFs) In order to estimate the compliance to treatment, we have designed an MS ACCESS
database:

- The creation of rules in OC is time consuming we create queries using SAS software
- We have encountered a lot of problems with the export module we first export the data into
SPSS format and subsequently translate it into SAS format

Conclusions
EDC in clinical trials in Africa is increasingly feasible with improving internet connectivity. OC is still a bit immature compared to high-cost clinical trial
softwares. This may create extra workload for the central data manager, depending on trial complexity. This should be considered when selecting software for
clinical trials.


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