This document discusses the process of migrating data from legacy clinical trial management systems (CTMS) to a new CTMS. It covers four key phases: determining the purpose and benefits of migration, scoping which studies and data types to migrate, evaluating methods for migration, and considering the optimal timing. The presenter outlines factors to examine like available tools, staff resources, data volumes and complexity, budget, and CTMS rollout strategy. The goal is to take a comprehensive, study-by-study approach to analyze needs and choose the most suitable migration path.
2013 OHSUG - The Ins and Outs of CTMS Data Migration
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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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
17. Closing
Thank you for attending!
psingh@biopharm.com
+1 877-654-0033
+44 (0) 1865 910200
17
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