Using ODM Messages to Integrate Clinical Trial Systems and Improve Data Quality

Transcription

1 Using ODM Messages to Integrate Clinical Trial Systems and Improve Data Quality Bay Area CDISC Implementation Network 15 July 2010 David Borbas Jazz Pharmaceuticals, Inc.

2 Disclaimers The opinions expressed in this presentation are not the official views or policies of Jazz Pharmaceuticals, Inc. 2

3 Topics Current state / Business Problem Solution Description Design Testing Results Summary of Experience 3

4 Current Clinical Trial Landscape Multiple E-technologies to process clinical data. These systems have duplicate information and are designed to function as separate systems. Significant work after data entry to reconcile the data errors / inconsistencies from these separate systems including: Identifying & Correcting errors Managing the data reconciliation process Time and Cost impact 4

5 Business Problem Can we prevent or reduce errors and decrease the cost and the time to reconcile the data from these separate systems? Can we realize the full benefits of EDC in this current state? 5

6 Evolution of Clinical Data Processing Paper & Pen CRFs entered into a database CRFs Database 6

7 Evolution of Clinical Data Processing Mixed Data Collection Study ECG IXR ediary CRFs Clinical Study Database Lab Data Reconciliation 7

8 Evolution of Clinical Data Processing Full E-Technology ECG IXR ediary Subject # Subject # Subject # EDC Subject # Clinical Study Database Data Reconciliation Lab Subject # Data Entered across all / some of the systems: Subject Number, Subject Initials, Date of Birth, Visit Numbers, Visit Dates, Pain Score, Randomization number, Kit numbers 8

9 ODM and Web services Use ODM messages and web services to transfer data between systems so there is one source for data that is shared between systems. ODM message is a triggered xml data file between systems Use this transfer method between systems to standardize and control data so that: Data is entered only once in the source system The source sends data to the receiving system The receiving system cannot edit the data received from the source 9

10 ODM and Web Services Flow Source Receiver IXR EDC Subject # Initials Date of Birth Gender Visit Date ODM v 1.2 Subject # Initials Date of Birth Gender Visit Date 10

11 Why ODM? ODM Operational Data Model CDISC standard that is: Designed for transport and archiving Vendors/Application developers have been certified ODM compliant so their systems are built to handle data transported by ODM Validated APIs (application programming interfaces) with the ODM data structure which supports Plug and play usability between different systems Rapid implementation with low cost and short timeline 11

12 Solution Using ODM Use of ODM messages and web services to standardize and control data between an IVRS and EDC system currently in use at Jazz Pharmaceuticals including: Design Testing Practical Aspects of Use in a clinical trial 12

13 Design Understand the data and business activity that each system supports Decide what data items to move between systems Assess your ability to manage the work and coordination needed as well as the risks and benefits 13

14 Design Data interfaced between IXR and EDC: Demographics Site Number Subject Number Subject Initials Date of Birth Sex Visit and Randomization Visit 1 date CGIs (Clinical Global Impression score) Randomization Number Randomization Date 14

15 Design Benefits Prevent important data errors between 2 systems Reduces data reconciliation queries - time & cost Risks What are the potential points of failure? How can you detect and recover? Is there a way to resend xml interface files if a failure occurs? 15

16 Testing Data Integration Specifications developed and signed off between JPI and both vendors Testing started once initial specs signed Generating and loading generic files to confirm communications path and successful transfer Additional specification refinement and testing Final testing with IXR UAT generated data entered by JPI personnel simulating real sites and subjects 16

17 Testing & Implementation Timeline Major Data Integration Tasks Start End Duration (business days) Start of Contract 21 Jan 2010 EDC build ecrfs Final Initial Data Integration Specifications Testing & specifications refinement 21 Jan Feb days 27 Jan Feb days 05 Feb Mar days IXR UAT Testing 01 Mar Mar days Go Live 09 Mar wks + 4 days 17

18 ODM Interface Message <?xml version="1.0" encoding="utf-8"?> - <ODM xmlns=" ODMVersion="1.2" FileType="Transactional" FileOID="Jazz _UAT_UBC_IXRS_INCR_26_2010FEB xml" CreationDateTime=" T07:00:37"> - <ClinicalData StudyOID="08-004(UAT)" MetaDataVersionOID="1"> - <SubjectData SubjectKey=" " TransactionType="Update"> <SiteRef LocationOID="041" /> - <StudyEventData StudyEventOID="SCRN"> - <FormData FormOID="ENROLL"> - <ItemGroupData ItemGroupOID="DM"> <ItemData ItemOID="SUBJID" Value=" " /> </ItemGroupData> </FormData> </StudyEventData> - <StudyEventData StudyEventOID="RAND"> - <FormData FormOID="RD"> - <ItemGroupData ItemGroupOID="DM"> <ItemData ItemOID="CGISSG" Value="5" /> <ItemData ItemOID="RANDDT" Value="24 FEB 2010" /> <ItemData ItemOID="RANDNO" Value="9245" /> </ItemGroupData> </FormData> </StudyEventData> </SubjectData> </ClinicalData> </ODM> 18

19 Application Workflow IXR creates a subject IXR randomization visit registered Data edits/updates in IXR due to Monitoring, Data review IXR EDC 19

20 Audit Trail for Data Integration CGIs Score from IXR Data ODM data file Date and Time Stamp present User Rave Import 20

21 Cost / Benefit Drivers Fixed cost for interfaces between systems 1 per vendor The more you do the cheaper it is Decreases Data Reconciliation work at the back by preventing errors Less DCFs & Queries Costs Time Greater initial data integrity 21

22 Data Integration Advantages Fixed Implementation Cost No Significant Timeline Impact Cost Reduction for Data Reconciliation Usually not a fixed cost Smoother Less Frenzied Database Lock Resending messages possible Message Failure alert to DBA 22

23 Data Integration Risks / Concerns Depends on System and Internet uptime Multiple points of failure Who to call? Sender, Receiver, Internet Giant Potential Finger pointing Design should incorporate understanding of the data & operations of both systems and the impact on your study What is feasible / practical? Still need to perform data reconciliation 23

24 Summary No Complaints from Clinical Sites! YEAH!! Replacing part of a variable cost error correction method with a fixed cost approach Supports study timelines 24

25 References Data Integration: Past & Future. Applied Clinical Trials, Solomon Schacter June

26 Thank you! David Borbas RN, MIS Director, Data Management Jazz Pharmaceuticals, Inc P