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DIA 2014 Risk Based Monitoring - Neill Barron
- 1. Risk Assessment Tools – Risk Based Monitoring Implementation at GSK Neill Barron Clinical Data Strategy GSK 26th Annual EuroMeeting 25-27 March 2014 ACV, Vienna Austria
- 2. Disclaimer The views and opinions expressed in the following PowerPoint slides are those of the individual presenter and should not be attributed to Drug Information Association, Inc. (“DIA”), its directors, officers, employees, volunteers, members, chapters, councils, Special Interest Area Communities or affiliates, or any organization with which the presenter is employed or affiliated. These PowerPoint slides are the intellectual property of the individual presenter and are protected under the copyright laws of the United States of America and other countries. Used by permission. All rights reserved. Drug Information Association, DIA and DIA logo are registered trademarks or trademarks of Drug Information Association Inc. All other trademarks are the property of their respective owners.
- 3. Objectives • Introduce GSKs approach to implementing an RBM “data-driven” strategy • Review use of RBM technology to drive risk based actions on real studies • Benefits & Challenges 3
- 4. A “Data-Driven” approach to monitoring...... • The RBM Technology enables a single consolidated “helicopter” view of risk across sites • Ability to drill into the detail behind any or all of the risk signals • Drives focussed and targeted monitoring intervention, where and when needed • Enables tactical Central Study Team oversight of monitoring strategy eDC CTMS External Data Consolidated RBM Database Core RBM Indicators x 11 Study Specific Indicators (2- 4) Monitoring Activity Plan Oversight “Helicopter view” Visuals CRA Action Central Oversight Study Specific Data
- 5. 5 What Do We Mean By “Risks”? 1 Site & Study Performance Recruitment rates Withdrawal rates Screening failures Data completeness Data currency Site Activities Site staff issues Study quality issues Data quality at site Frequency of site visits Overdue activities Clinical Data Driven Data quality Safety trends/outliers Data variability Study Specific Identified by the study team Supplement generic indicators based on needs of protocol Typically key efficacy or safety Key Risk Indicators The right data to drive a risk based approach......
- 6. RBM IN ACTION Real World application of RBM 6
- 7. Site003: Risk score Number of patients Visit Periodicity Intervention Required Site031: Risk score Number of patients Visit Periodicity Intervention Required CompositeRiskScore Site Visit Frequency (Visits per month) Interpreting the data to drive action Data entered Late Protocol Deviations High AE Rate 3 examples of 18 indicators to drill through DR
- 8. AdverseEventRatio Number of Subject Visits Drill-through: Adverse events for a selected site DR
- 9. ProtocolDeviationRatio Expected number of patients enrolled Drill-through: Protocol Deviations for a selected site DR
- 10. Example 1 - High Recruiting site exhibiting High Risk 10 Monitoring Activity Plan Adobe Acrobat Document
- 11. 1100 Month 0000Presentation title in footer Site exhibiting Increase in Overall Risk Score Between October and December Example 2 – Early Detection of increase in Risk Score
- 12. 1200 Month 0000Presentation title in footer Example 3 – Low risk score, High Monitoring Visit Frequency
- 13. 1300 Month 0000Presentation title in footer Example 4 – High risk score, Low Monitoring Visit Frequency
- 14. Implementation – Benefits & Challenges Benefits • Quality: Enhanced study & data quality via earlier detection of emerging risk • Efficiency: Focus monitoring intervention on areas of highest need • Oversight: Provides a “one- stop shop” complete data- driven view of risk across sites to streamline decision making Challenges • Behavioural: Using risk to drive action is not intuitive • Understanding: Interpreting the risk - “What does it mean and what do I need to do?” • Risk Identification: Development of the right study specific indicators to complement the core indicators is essential 14
- 15. Next Steps to Implementation 15 • “Mini-Pilot” deployment of RBM technology to date has validated sensitivity and accuracy of the tool in assessing risk at site • Further “Mini-Pilots” during 2014 will enhance understanding of risk signals and how they drive monitoring intervention • 2H-2014 for full deployment of RBM technology and process on 3 large early adopter studies • Scale up across late phase studies to commence Q1- 2015
Editor's Notes
- The “Holistic” view of risk across all sites, rather than individual CRA’s view of their own sites, enables powerful central decision making on monitoring frequency This visual represent a birds eye view of risk across sites – it is driven and fed by individual core and study specific risk indicators We would expect our higher risk sites to be distributed towards top right of the and green towards bottom left – i.e. Risk is driving Monitoring Visit frequency The “high risk sites” are a minority which indicates that there is significant opportunity in deploying Risk Based Monitoring Looking at this visual in the RBM world, a DQL would identify sites like Site003 where there is a high risk score in a site with a relatively large number of patients (deduced from size of circle) This site could be clicked on and it will allow investigation into the individual risk areas for that site (examples on following slides) so that DQL and CRA can have targeted discussions to address root causes of risk Also, the DQL will identify sites just like the amber site to the far right – here, the monitoring visit frequency (average) is 2.6 times per month which does not correlate with level of risk and is clearly an outlier...DQL would drive RBM by having targeted conversations with CRA/CSM to understand this lack of correlation, which may result in a change in behaviours, or even perhaps we are missing a risk from the tool that we can use to refine further.
- Thresholds are based on 95% and 99.8% control limits, corresponding to approximately 2 and 3 standard deviations respectively, the latter being the classic Shewhart limits. Here you can see where site003 lies on the funnel plot (highlighted on funnel plot in black) By clicking on this site the detail on demand in bottom pane and right hand populate so end user can see detail. This detail automatically populates the site report for monitors generated from heatmap (see previous slide) - along with “recommended actions”
- In upper part of this chart we are highlighting sites that have a statistically higher number of protocol deviations than the mean – in this example, the details of types of deviation are displayed in bottom pane. Again these details would be automatically part of the reports sent to monitors from the heatmap, so they could focus efforts on addressing root causes
- This was what was referred to as the “Jupiter” site. It was a high enroller displaying highest risk driven by a number of red signals across a number of indicators. The site exhibited late data entry, high AE rates, issues with IP compliance and well as red signal for disease progression. As a high enrolling site, this site stood out as the one to tackle first Team had suspicions about this site but couldnt quite put their finger on it. The risk signal drove conversations with the CRA/CSM on the root causes and it drove an onsite visit
- We readily identify sites that jump up in risk score – early detection is important This site’s risk score increase after the addition of study specific indicators relating to (1) Disease Progression (2) IP compliance Before study specific indicators were added to the tool, this site exhibited a low risk score – demonstrates the importance of good study specific indicators This drove specific patient retention conversations with site as well as a retraining on IP – detecting this early was important to the study
- Driving the right RBM behaviours Low Risk Site exhibiting a high MV frequency Validated that low risk at this site was accurate Site has been remotely monitored since then with average MV frequency decreasing for this site (from 1.1 MVs per month to 0.85 MVs per month)
- Commentary/Notes Identifying this outlier in October identified need for a MV After MV, site’s risk score improved as outstanding items were addressed on site