2013 OHSUG - The Ins and Outs of CTMS Data Migration

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The Ins and Outs of Clinical Trial Management Software Data Migration

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2013 OHSUG - The Ins and Outs of CTMS Data Migration

  1. 1. The Ins and Outs of CTMS Data Migration [Session #] [Date] Param Singh Vice President of Clinical Trial Management Solutions BioPharm Systems, Inc. 1
  2. 2. Today’s Agenda Topic Welcome and Introductions Should We Migrate? What Should We Migrate? How Should We Migrate? When Should We Migrate? Migration Demo Q&A
  3. 3. Should We Migrate? (Purpose) • What are the benefits of having historical study data in the new CTMS? – Comprehensive reporting – Complete picture of each study • What are the benefits of having current study data in the new CTMS? – All study team members working in one system within one set of business processes – More cost-effective for IT to support and maintain one system 3
  4. 4. Should We Migrate? (Purpose) • What are the risks of migrating? – Loss of Functionality: New CTMS might not have the same functionality as all combined legacy systems and tools – Loss of Data: Data could be lost in the process of cleaning and/or migrating – Time Lag: Could be a gap between when the data is unavailable in the legacy system and when it is available in the new system – Time Overlap: One study could be available in two systems before the legacy system is decommissioned 4
  5. 5. Examples Scenarios Growing CRO • Recently secured a new, global client • Several large-scale and long- term studies planned or already started • Limited human resources to manage studies; need to operate as efficiently as possible • Limited IT department to support systems and tools Global Pharma • For all studies of all sizes, need to track subject data, even after officially closed • New Clinical Director requires comprehensive reporting on study, site, and vendor expenses • Recently implemented a data warehouse
  6. 6. What Should We Migrate? (Scope) • Scoping takes place on two levels: 1. Study: Which studies should be migrated? 2. Data Type: Which types of data should be migrated for all of the studies chosen? • Begin with a study-by-study analysis: – Compare each study timeline to your CTMS implementation timeline, especially CTMS go-live date and legacy system cutoff date(s) – For current studies, consider the volume of work that remains, given available resources 6
  7. 7. Example Studies EndSoon Study LastLong Study StartSoon Study Study ends in three months (before legacy system cutoff) Study will continue for at least one year post CTMS go-live Study begins one month before CTMS go-live Manageable volume of work with available staff Large volume of work Moderate volume of work, but do not need to use CTMS for first 2 months Migrate = No Migrate = Yes Migrate = No 7
  8. 8. What Should We Migrate? (Scope) • Data Types: Which are available in the new CTMS? – Contacts – Subject Visits – Accounts – Adverse Events – Addresses – Protocol Deviations – Products – Correspondence – Programs/Projects – Site Visit Reports – Studies – Investigator Payments – Sites – Vendor Expenses – Subjects – Documents 8
  9. 9. What Should We Migrate? (Scope) • Which are you currently tracking? – Contacts – Subject Visits – Accounts – Adverse Events – Addresses – Protocol Deviations – Products – Correspondence – Programs/Projects – Site Visit Reports – Studies – Investigator Payments – Sites – Vendor Expenses – Subjects – Documents 9
  10. 10. What Should We Migrate? (Scope) • Which of the remaining data types do you need in the system going forward? Think: – Extracting and/or reporting data • No need for correspondence; no reporting needs • No need for adverse events; safety system is system of record – Acceptable workarounds • Keeping existing vendor payments tool • Approved site visit reports can be printed and archived 10
  11. 11. How Should We Migrate? (Methods) • Inventory your source systems: Where does the data currently live? – Spreadsheets – MS Access databases – Home-grown databases – Word documents – Document management system – Accounts payable system – Existing CTMS 11
  12. 12. How Should We Migrate? (Methods) • How many records do you have of each date type in each source system? – Use reports or embedded functions that provide row and column counts • How closely does the source system format map to the CTMS format? Think: – Relationships: one-one, one-many, many- many – Attributes: fields – Data Standards: field contents 12
  13. 13. How Should We Migrate? (Methods) • Manual migration vs. automated migration – Automated options: • Embedded tools • Existing external tools • Custom-built tools • To choose a method, consider: – Available tools – Available staff – Volume – Complexity – Budget – Time 13
  14. 14. When Should We Migrate? (Timing) • Timing depends on your CTMS rollout strategy – Big Bang: All studies go live at the same time – Study-by-Study: Begin with a pilot study, roll out subsequent studies one by one • Recommendation: Study-by-Study – Iron out kinks in business processes and training materials during pilot • Increases user adoption – Easier to manage training rollout 14
  15. 15. Summary 4 Phases of CTMS Data Migration Analysis • Purpose: What is the business driver behind the migration? • Scope: Which studies do we need? Which data types do we need for those studies? How will the data be used? • Methods: What tools and resources are available, and how do they fit with our budget and timeline? • Timing: What makes the most sense, considering our CTMS rollout plan? 15
  16. 16. Q&A 16
  17. 17. Closing Thank you for attending! psingh@biopharm.com +1 877-654-0033 +44 (0) 1865 910200 17
  18. 18. Presenter Bio Param Singh Vice President of Clinical Trial Management Solutions • 5+ years with BioPharm • 13+ years of experience implementing Siebel Clinical • 30+ Siebel Clinical implementations 18

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