Project management in data management:

need for a shift in paradigm

Swati Tare, PhD. PGDCR-SIROCLINPHARM

An organized development of an end product is a Project

and

the discipline driving the process is Project Management which involves juggling between the basic elements, namely cost,

performance and schedule

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Project management

So what’s new ?Technologies have evolved at a faster pace, it is said that 2000 is all about velocity!

Complex trials,

Long durations

Stringent regulatory requirements

Reduce time to market

Cost effectiveness

--Changing timelines…

--Changes in scope…

--Quality issues…

--Resource attrition…

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Time for a shift in paradigm

Changes are inevitable and so are the risks,So acknowledge them!!

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Proactive

Reactive Proactive

Gearing up for pro-activity

• Reporting metrics, • Issue trackers• Deviations log • Governance plan • Risk management plan

• Process improvement• Training • Knowledge sharing• Project plan• Task ownership matrix• Rewards

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Process improvement

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Training

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Training on protocol, efficacy end points,regulatory submission

Knowledge Sharing

Gives an opportunity to capitalize on way-outs and avoid the slip–ups

Accountability --responsibility --answerability --trustworthiness --liability

Rewards

Belongingness!

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Task ownership matrix

Reporting metrics and issue trackers

• Trend analysis on queries Lesser queries-cost saving-better CRO-sponsor

relationships• Reports on discrepancy ageing• Reports on entry to verification gap• Trackers on data issue

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Avoidance rather than Alleviation

Communication

Communication Between

stakeholders plays an important role

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“No one can whistle a symphony. It takes a whole orchestra.”

H.E. Luccock

Risk management

Minimize, Monitor and Control

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Background Rescue study, homegrown system quantum of data unknown, status of data cleaning unknown

Challenges To build a database in absence of complete data specificationsprotocol amendments for new recruitments, stringent timelines

Approach Detailed plan for migration TOMRMP

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Case study

Risk Impact Mitigation

Delay in test data transfer

Increase in timelines

Meetings and follow up with third vendor for data transfer

Different technical platforms

Extensive data mapping and pre-processing of datasets

More resourcesMigration of complex datasets on priority

Different outlook and functionality of database

Acceptability and compliance at site

Training to site personnel

Non acceptable characters in data

Failure of data migration

Identification during review,Data entry for such characters

Surprises

• Despite doing a thorough planning for mitigating risks, there were surprises..

• Few datasets were merged • Whilst few were separated

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Take away..

• Accepting the existence of challenges helps us to make a shift in the paradigm from reactive to proactive

• As quoted by Benjamin Franklin--it is easy to see, hard to foresee

• So better to be equipped for “Fire fighting” as well

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