This case study presentation provides examples of how the Metric Champion Consortium (MCC) Imaging Performance Metrics were used by BioClinica to measure and improve clinical trial sponsor, clinical trial site, and Imaging Core Lab clinical trial operations. Learn more about our Imaging Core Lab Services at www.BioClinica.com/Imaging.

1. BioClinica Case Study:
Using Imaging Performance Metrics to
Improve Sponsor, Site, and Core Lab Clinical
Trial Operations
Dawn Flitcraft, VP Client Services
Jennifer Schick, Project Director Oncology
Dana Curcio, Project Director RA/Inflamm
18 January 2012

2. Background on BioClinica’s Involvement
with the MCC
BioClinica is a founding Imaging Core Lab member of
the MCC. The involvement began in November 2007
with BioClinica holding a position on the initial Steering
Committee. During the initiation phase, Working
Groups were established to drive a core set of metrics
for moving forward. BioClinica representation was
present on all of these Working Groups including
Operational, Finance, and Clinical. BioClinica continues
to be a member of the Steering Committee and
Imaging Metrics and Implementation Working groups
today.
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3. Why utilize MCC Imaging Performance
Metrics?
From the sponsor’s perspective:
• Enhanced understanding of the services imaging core labs
provide
• Improved monitoring and evaluation of a core lab’s ability to
meet critical timelines
• Ability to pinpoint areas of interest & utilize both sponsor and
core lab knowledge bases to improve processes for on-going
processes
• Enhanced partnership relationships through improved
communication among all parties
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4. Why utilize MCC Imaging Performance
Metrics?
From the service provider’s perspective:
• Identification of client’s business requirements
• Enhanced understanding of client’s processes
• Improved monitoring of client’s critical deliverables
• Identification of key metrics that the client is focused on
• Greater focus on achieving meaningful process improvement
• Higher customer satisfaction
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5. Example 1: Site Start-Up
MCC Metric Catalyst – Site Start Up:
Percentage of Sites Qualified vs Actual

6. Using Metrics to Improve Quality
Example 1: Site Start-Up
MCC Metric Catalyst – Site Start Up: Percentage of Sites Qualified vs Actual
Reporting
Definition Unit of Measure Target
Frequency
The average number of days from when a site survey is
sent to the site and when the site returns the Days Bi-Weekly 14 days
completed survey to BioClinica.
Context:
As part of the startup process for clinical studies, BioClinica collects important technical
information such as the name of imaging equipment manufacturer, model and software version
for each participating site. BioClinica then provides each investigator with specific image
acquisition parameters. These surveys must be received and completed in order for sites to
receive their Imaging study kits, which are tailored to the sites requirements. The site cannot
begin imaging subjects until these kits have been received.
For the global study profiled here, site surveys were targeted to be completed and returned to
BioClinica within 14 business days. If completed surveys were not received within 7 days,
BioClinica’s process included sending a second follow-up request.
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7. Using Metrics to Improve Quality
Example 1: Site Start-Up
MCC Metric Catalyst – Site Start Up: Percentage of Sites Qualified vs Actual
Reporting
Definition Unit of Measure Target
Frequency
The average number of days from when a site survey is
sent to the site and when the site returns the Days Bi-Weekly 14 days
completed survey to BioClinica.
Review Steps:
• Analysis of “surveys completed” found that the average turnaround time for survey completion
was consistently greater than the target of 14 business days and was on average greater than 35
days.
• The BioClinica team suggested that improving accountability at the site level for survey
completion as well as improving follow up communications would help to motivate better
compliance.
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8. Using Metrics to Improve Quality
Example 1: Site Start-Up
MCC Metric Catalyst – Site Start Up: Percentage of Sites Qualified vs Actual
Reporting
Definition Unit of Measure Target
Frequency
The average number of days from when a site survey is
sent to the site and when the site returns the Days Bi-Weekly 14 days
completed survey to BioClinica.
Action Steps:
• The BioClinica team recommended the implementation of bi-weekly regional CRA
teleconferences to review site survey status in detail.
• Equipped with the up-to-date facts, the CRAs followed up directly to encourage sites to send
the missing information. The sponsor supported this recommendation.
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9. Using Metrics to Improve Quality
Example 1: Site Start-Up
MCC Metric Catalyst – Site Start Up: Percentage of Sites Qualified vs Actual
Unit of Reporting
Definition Target
Measure Frequency
The average number of days from when a site survey is sent
to the site and when the site returns the completed survey Days Bi-Weekly 14 days
to BioClinica.
Results:
Within two months this initiative
demonstrated positive results, the
survey completion rose to 95% (2.48
day turnaround) and 96% (3 day
turnaround) respectively. Currently,
sites are doing far better than the target
of 14 days to complete surveys and are
providing completed site surveys to
BioClinica within an average of 3
business days after survey receipt.
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10. Using Metrics to Improve Quality
Example 1: Site Start-Up
MCC Metric Catalyst – Site Start Up: Percentage of Sites Qualified vs Actual
Lessons Learned
• The importance of Site Survey completion should be emphasized at the
Investigator Meeting, especially the CRA involvement.
• Samples of the survey and live demonstrations aid in the learning process and
should be available.
• Simplification of the survey improved compliance of the site survey process.
• Distribution of the site surveys was coordinated with the initiation visits.
• When surveys were provided too early in the site approval process, they went
unnoticed and delayed in overall response time. In some instances, they needed
to be re-routed for completion.
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11. Example 2: Image Processing
MCC Metric Used – Average number of
Calendar Days from Image Receipt to
Ready for Independent Review

12. Using Metrics to Improve Quality
Example 2: Image Processing
MCC Metric Used – Average number of Calendar Days from Image Receipt
to Ready for Independent Review
Reporting
Definition Unit of Measure Target
Frequency
Average number of calendar days from when the image
Days Bi-weekly 4-6 days
is designated for review to completion of the review
Context:
BioClinica was contracted to perform an oncology study with a central radiological evaluation
(read) of the CT images that required confirmation of progression by central readers, while both
CT and Nuclear Medicine modalities were required for submission. Specifically, the site was
required to notify BioClinica via a transmittal form of site-suspected progression on for each time
point where progression existed, triggering initiation of a central read. A 4-6 business day
turnaround was required at BioClinica from receipt of this time point to completion of the central
read including notification of the read result to the site.
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13. Using Metrics to Improve Quality
Example 2: Image Processing
MCC Metric Used – Average number of Calendar Days from Image Receipt
to Ready for Independent Review
Reporting
Definition Unit of Measure Target
Frequency
Average number of calendar days from when the image
Days Bi-weekly 4-6 days
is designated for review to completion of the review
Review Steps:
• An initial review of the metric indicated that the average Turn Around Time (TAT) was
consistently greater than the target of 6 business days.
• Further analysis determined that much of the delay was due to sites submitting incomplete
imaging sets: Both CT and Nuclear Medicine modalities were required and quite often sites
were submitting only one of the two required image sets.
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14. Using Metrics to Improve Quality
Example 2: Image Processing
MCC Metric Used – Average number of Calendar Days from Image Receipt
to Ready for Independent Review
Reporting
Definition Unit of Measure Target
Frequency
Average number of calendar days from when the image
Days Bi-weekly 4-6 days
is designated for review to completion of the review
Action Steps:
BioClinica, in collaboration with the sponsor and CRO, made the decision to track an additional
point in the process (i.e., Day 1 of the central read process would be based on the date a complete
image set was received with no outstanding queries or the date that a site confirmed that no
additional image data was acquired or could be submitted).
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15. Using Metrics to Improve Quality
Example 2: Image Processing
MCC Metric Used – Average number of Calendar Days from Image Receipt
to Ready for Independent Review
Unit of Reporting
Definition Target
Measure Frequency
Average number of calendar days from when the image is
Days Bi-weekly 4-6 days
designated for review to completion of the review
Image Receipt to Readiness for Review Results:
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Using the more redefined start date of
12 Day 1, the team tracked the TAT from
10 data ready for the read to site being
8 notified of the read result to track
Days
6
adherence to target metrics.
4
TAT
2
Revised TAT
0
26-Aug 12-Sep 28-Sep 14-Oct
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16. Using Metrics to Improve Quality
Example 2: Image Processing
MCC Metric Used – Average number of Calendar Days from Image Receipt
to Ready for Independent Review
Lessons Learned
• The revised TAT definition allowed BioClinica to look at the time lapse between
when the site notified BioClinica of suspected progression and Day 1.
• BioClinica helped the sponsor to identify which sites should receive additional
training to improve compliance and data quality.
• In addition, BioClinica worked in partnership with the sponsor’s CRO to
determine if missing scans were even acquired per the clinical database, allowing
in some scenarios for the read to be conducted without waiting for site feedback.
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17. Summary
BioClinica utilized metrics that correspond to MCC imaging performance
metrics (v1.0) for Start Up and for Image Processing, on two global projects
of differing therapeutic areas. The utilization of such standardized metrics
allowed monitoring of deliverables and provided the ability to pinpoint
areas that could be improved during the trial process. As indicated by
results from these two examples, application of such metrics resulted in
reduction of specific task completion times. Decreases in these completion
times drive greater patient recruitment efficiencies.
BioClinica’s standard reports currently include seventeen different MCC
Imaging Performance metrics. In addition to the improvements as noted
above, using these metrics has also resulted in internal improvements in
team and employee performance. Due to the establishment and
achievement of clearly defined goals and targets on a per project basis,
BioClinica encourages the use of the MCC standardized metrics in all clinical
trial projects.
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