Gathering and Leveraging Quality-Centric Metadata in Clinical Trials
Director, Software Architecture
Gathering and Leveraging Quality-
Centric Metadata in Clinical Trials
Increasing Initial Quality
► Quality data on the first pass
► Problem personnel
► Historic performance
► Dynamic Risk Based Monitoring
► Cost model adjustments
Lower Quality = Higher Cost
► Direct Cost
• More cleaning
► Indirect Cost
• Treatments could be less effective
• Treatments could be less safe
Data Entry Data Cleaning$$$ Clean Data
► Who is managing site quality today?
• Who is reporting on Entry Personnel
• Who is holding them accountable
► What are the key metrics?
What Metrics Do We See?
► Page report
► Time to Entry
► Time to SDV
► Time to Sign
► Time to Resolve
► Query counts
What Metrics Don’t We See?
► Was the initial data accurate?
• If not, was intervention required?
• If so, how many interventions?
► What trends are visible from this?
• How often is initial data accurate?
• How often is a change self-initiated?
Difficult to Collect and Report On
► Applicable data takes time to gather
• Hindered by turnover at sites
► Not preserved for the next trial
► Visible as points, but not aggregated
► We need to predict quality to realize the
full benefits of Risk Based Monitoring
We Have a Wealth of History
► Leverage historic quality data during site
• CTMS / Cloud
► Show quality over time
• Cross-trial, cross-sponsor
► Rapid visibility
• Hotspot reports over users
Major Results from Minor Changes
► Increasing user initial quality
• By 3% reduces data changes by 31%
• By 5% reduces data changes by 48%
• By 10% reduces data changes by 79%
Application of the Tools
► Measuring makes us aware
► But we can’t really solve the problem
► Only the site can truly manage
• The personnel are theirs
► Why isn’t this happening today?
• Lack of measurement, lack of incentive
We Can Change These
• New Metrics
• Contract for quality
► For Sites and ClinOps
• Similar metrics for CRAs
The Value of Quality
► Performance and consistency gain value
beyond repeat business
• Additional Income
► A Market Emerges for Quality-Centric
Sites and Personnel
The Market will Adapt
► We will pay more for quality data
► The overall cost is lower
• Data is more accurate
• Confirm and adjust
• Dynamic Risk Based Monitoring
► Risk is user-based
A Quality-Centric Model
► Expectation to manage quality is set
► Quality directly influences payment
► Performance impacts future business
► Sites are motivated and compensated
from Concept to Cure
with DATATRAK ONE
Cary, North Carolina
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