OC Global Conference ’13Boston, MA

21st June 2013

An Alternative Approach to using OpenClinica in “Offline” mode: A case

of WHO Buruli Study.

Raymond Omollo&

Michael Ochieng

Presentation Outline

• About DNDi

• Introduction

• Methodology

• Challenges

• Conclusion

About DNDi• A collaborative, patients’ needs-driven, not-for-profit

research and development (R&D) organization that develops safe, effective & affordable treatments for neglected diseases (www.dndi.org).– Afflicting the worlds poorest people– HAT (Sleeping sickness), Leishmaniasis, Chagas disease,

Paediatric HIV, Filaria & Malaria

• Headquartered in Geneva, Switzerland with 7 regional & support offices in Kenya, New York, Brazil, India, Malaysia, Japan and Democratic Republic of Congo

• Objectives:– Develop 11 to 13 new treatments by 2018– Use & strengthen capacities in disease endemic countries– Raise awareness about the need to develop new drugs for

neglected diseases & advocate for increased public responsibility

Introduction: • The DNDi Data Centre (DC) located in Nairobi, Kenya

– Data Management – Statistical Analysis

• The DNDi - DC supports the DM component of the Buruli Ulcers (BU) trial in West Africa (Ghana & Benin)

• WHO BU Study– Randomized controlled trial comparing efficacy of

8 weeks treatment with Clarithromycin and Rifampicin versus streptomycin and Rifampicin for buruli ulcer (m. Ulcerans infection)

– Sample Size (n=430)– Ghana (4 Sites), Benin (1 Site)

Sites Geographical Distribution

Pobe

Agogo

BeninTogo

Dunkwa

Tepa

Nkawie-Toase

Other DNDi Sites

BU Site Assessment• Site users had no prior experience with

OpenClinica before– Previous usage of other web based systems

• php based database surveillance system– Need for training & retraining including Data

Management principles• All sites access internet through modems

– Cell phone service providers• Internet Connectivity

– Limited or unstable in some instances (remote sites)

Implementation Scenarios:

•Pros

• Data is available in real time– Cleaning and extraction done

as soon as entry at site is done.

• More efficient – movement of paper CRF’s

from sites eliminated.

• Data management capacity at the site.

•Cons

• Reliable internet connectivity needed at the sites.

• Understanding of the database by site users is a must.

• Data entry may slow down with time– Database size as it grows

Case 1: OpenClinica Installed in a Server at the DC and access provided to Data Managers/Data Entry Personnel at the sites.

Implementation Scenarios:

•Pros• No need for Internet at

data entry. – Only periodically for

synchronization.

• Faster data entry– No internet bandwidth related

issues.

• Helps develop data management capacity at the sites.

•Cons

• Complex synchronization done periodically– Program scripts

• Remote data support needed– Troubleshoot the database– Technical person may be

needed to help with this.

Case 2: Local installations at each study site followed by synchronization with the central database in Nairobi.

Implementation Scenarios:

•Pros

• No need to have data entry personnel at the sites.

• No internet and computers needed at the sites.

•Cons

• Movement of Paper CRF’s between the sites and DC cumbersome– May lead to other risks such as

loss and increase in expenses.

• Missed opportunity for the Development of Data management capacity at the sites.

Case 3: OpenClinica installed in Nairobi with data entry done in Nairobi.

Methodology: • Issues:

– OC does not support offline use as currently developed

– Need for timely data entry and availability (EDC)

– Work in areas with limited or unreliable internet connection

• Developed an alternative approach to benefit from OC in our setup– Database set-up and deployment– Data collection at site– Synchronization with central database

Methodology: User Training

Methodology: Site Activities • At the sites

– OC installation on the study laptops.• Central DB is replicated on all site

computers.– Data Entry and Reconciliation

• Fast since no internet is needed during data entry.

• More users can do entry on the study computer through LAN.

Methodology: Data Sharing

– Study data back up• Daily data backups on the study laptops.• Automated Weekly backups saves in the

Dropbox.–Postgre database–.data folder;Attached Files–dataInfo.PROPERTIES file

Methodology: DC Activities• At the DC

– Retrieval of backup data from the Dropbox for synchronization with the central database.• Site Database dump is restored on the

Server.– OpenClinica Event Scheduler script is run

• Automatically creates and schedules new subjects in OC by Comparing Site DB with Central DB.

– http://en.wikibooks.org/wiki/OpenClinica_User_Manual/OfflineDistributions

Methodology: DC Activities

– Data Import through OC Web services• Python Data Import Script imports data into

OC through Web Services interface.– Sample script to be circulated to OC Community

• Log file automatically generated showing import status.

Implementation in offline modeSite Activities

Entry into source documents and patient

files

Run site Data Backup & Save in Dropbox

Data Entry into OpenClinica

Discrepancy Notes in OpenClinica for Query

Management

Source Data Verification

(SDV)

Data Centre ActivitiesData Centre Activities

Data Extraction into STATA for further Query

Management

Clean Dataset for Analysis

Synchronization into Central Database

Synchronization into Central Database

Restore Site DB on the server

Run OC Event Scheduler Script

Run OC Data import Script;

Imports data through WS.

Query Processing in Query Management System

(QMSPlus)

10% Verification of Central Database data against the

Site Database

OC Event Scheduler

OC scheduler pseudo-code

• Plug in the site database dump on the same server as the central database.

• Fetch all the subject from the subject table in site database.– For each subject record in the site DB, check if it

exists in the Central DB and if not add the subject.• Fetch all subject’s Study Events from the Study_event

table.– For each subject’s study_event fetched, check if

exists in the Central DB and if not add the study event.

Subject Data Import

• Site DB is plugged on the same server as Central DB.• Executed after scheduling has been done.• Uses OC Web Services interface:

– The SOAP Messages are dynamically enveloped from subjects site data.

– Each SOAP Envelop request is sent for each CRF assigned to an event.

• Data Import overwrites previously imported data.• Data import is done on weekly basis.

Data Import Log

Challenges: • Site user training and assessment

– Initially done at Agogo (Ghana) and Pobe (Benin) for all site users

– Understanding of how OC works to reduce user support workload

• Implementation of CRF changes– Possible during study lifetime (protocol amendments)– Maintain same database structure at the DC as well as

sites • Data transfer and synchronization

– Internet still necessary at some point to effect transfer of data

– Data is encrypted and password protected during transfer; does this affirm security?

Challenges: • Large Data imports

– Takes much time; scheduled to run over the weekend• Standardize OC installation between sites and DC

– Any change on the central DB is replicated across all site DBs.

• OC is designed to work in online mode– One of the world’s preferred software of choice for

clinical trials– Limited use and acceptance in the presence of poor

and unreliable internet infrastructure• A number of processes are involved

– Most of them automated making the whole process feasible

Conclusion

• Automated most processes involved• Promotes EDC capabilities of OC in areas with

limited or unreliable internet infrastructure• The Data Center has developed an interface to

have OC working in offline mode;– The process is automated through python

scripts.– Use of Dropbox makes site data sharing

faster and safer.• This is unique addition by the Data Center

Asante Sana