OC Global Conference ’13 Boston, MA 21 st June 2013

1. OC Global Conference ’13Boston, MA21st June 2013 An Alternative Approach to using OpenClinica in “Offline” mode: A case of WHO Buruli Study. Raymond Omollo & Michael Ochieng

2. Presentation Outline • About DNDi • Introduction • Methodology • Challenges • Conclusion

3. 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

4. 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)

5. Sites Geographical Distribution Togo Benin Pobe Tepa Agogo Nkawie-Toase Dunkwa

6. Other DNDi Sites

7. 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)

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

9. Implementation Scenarios: Case 2: Local installations at each study site followed by synchronization with the central database in Nairobi. Pros Cons Complex synchronization done periodically Program scripts Remote data support needed Troubleshoot the database Technical person may be needed to help with this. • 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.

10. Implementation Scenarios: Case 3: OpenClinica installed in Nairobi with data entry done in Nairobi. Pros 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. • No need to have data entry personnel at the sites. • No internet and computers needed at the sites.

11. 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

12. Methodology: User Training

13. 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.

14. 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

15. 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

16. 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.

17. Site Activities Entry into source documents and patient files Data Centre Activities Synchronization into Central Database 10% Verification of Central Database data against the Site Database Restore Site DB on the server Data Entry into OpenClinica Data Extraction into STATA for further Query Management Discrepancy Notes in OpenClinica for Query Management Run OC Event Scheduler Script Query Processing in Query Management System (QMSPlus) Source Data Verification (SDV) Run OC Data import Script; Imports data through WS. Run site Data Backup & Save in Dropbox Clean Dataset for Analysis Implementation in offline mode

18. OC Event Scheduler

19. 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.

20. 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.

21. Data Import Log

22. 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?

23. 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

24. 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

25. Asante Sana