Ensuring Data Quality in an EDC Study: When Traditional QC No Longer Applies

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Marcus Bradley
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1 Ensuring Data Quality in an EDC Study: When Traditional QC No Longer Applies Ellen Morrow Sr. Director, DM Standards and Solutions Quintiles, Inc The presenters have disclosed that they have no proprietary or financial interests in the topics covered in this presentation.

Director, DM Standards and Solutions Quintiles, Inc The presenters

2 Agenda What Led to the Quality Query Report (QQR) Implementation? Objectives to Implementing QQR Process Flow: Where Does QQR Fit? Components of QQR QQR Process Current Status and Next Steps Challenges Faced in QQR Implementation Expected Benefits of QQR Other EDC Quality Initiatives

Components of QQR QQR Process Current Status and Next Steps Challenges

3 What Led to QQR: QC in Traditional Paper-Based Studies Paper Based Study Final Inspection Critical Data QC Identifies errors in recording data on CRF. Identifies errors entering data from CRF into database. 3

Data QC Identifies errors in recording data on CRF.

4 What Led to QQR Implementation: Traditional QC No Longer Applies EDC Studies What is Data Management s role in ensuring the quality of the data in an EDC study? Can we add value beyond manual review of listings? What does QC mean in an EDC study? 4

ensuring the quality of the data in an EDC study?

5 Objectives to Implementing QQR Develop tools and process for ensuring queries are generated and closed appropriately and accurately (focus quality checks on queries, rather than data entry) Provide an additional quality gate to query management Start with InForm studies and include only queries closed by Data Management staff (not Clinical) 5

rather than data entry) Provide an additional quality gate to query management Start

6 Components of QQR Cognos Report (generates listing of all manually closed queries) Excel macro to sample queries for review Work instruction to document process (SOP) Template to document study-specific QC plan (e.g., time points for review; SOP) Standard form to document study-specific results (SOP) 6

document process (SOP) Template to document study-specific QC plan (e.g.

7 QQR Process: Define the Study-Specific QC Plan Time points for review Sample size (i.e., percentage of queries manually closed in that timeframe) QC of any paper-based components of the study (e.g., diaries, etc)

8 Run Report QQR Process: Select Queries for Review Select Date Range (subset based on dates, e.g., study start date to current date) Select Query Closed by Rights Group (subset by rights group of who closed the query, e.g., DM)

9 QQR Process: Select Queries for Review (cont) Save the listing to Excel Run Excel macro; select percentage according to QC Plan Add Comments column to aid in completing documentation

10 QQR Process: Review Queries Review queries in Excel* to identify errors: Query raised with inappropriate query text Duplicate query Incorrect query due to misunderstanding of the edit check Query closed instead of re-querying the site (i.e., initial response did not satisfy the conditions of the check) *Reviewer cannot be the same person who generated or closed the query.

check Query closed instead of re-querying the site (i.e., initial response did not satisfy

11 QQR Process: Review Queries (cont) Document the results on the InForm QC Form and estimate the error rate Remediate if necessary (e.g., issue follow-up query) Analyze to Identify Possible Trends Same person making mistakes Same edit check Same types of data Preventive action, if necessary

, issue follow-up query) Analyze to Identify Possible Trends Same person

12 Current Status of Implementation and Next Steps Pilots run on 7 studies; process tweaked Training workshops held in June and July Creating the QC Plan Use of Cognos Report Selecting sample of queries for review What constitutes an error; documenting the results Work instruction, standard template and form made effective 01-Aug; required for all new InForm studies Working on reports for other EDC platforms

for review What constitutes an error; documenting the results Work instruction, standard template and

13 Challenges Faced in QQR Implementation QQR does not currently facilitate 100% review of queries associated with critical data items Acceptable error rate not yet defined No precedent yet in the industry Volume of checking lower than with paper (i.e., less tolerance for errors) Assessments of errors are more subjective than in a paper-based study

14 Expected Benefits of QQR Improved query management process for the benefit of all: Higher quality queries will result in higher quality data Investigators not frustrated by nonsensical queries Enhanced confidence in DM s abilities and understanding of query management (for Clinical, PM, Sites, Sponsors, etc) DM doing our part in delivering high quality data that leads to the development of new treatments for patients

confidence in DM s abilities and understanding of query management (for Clinical, PM, Sites, Sponsors,

15 Other EDC Quality Initiatives Implementation of Build Teams ; improving quality of set-up through specialization Technical Designers Validation Leads Implementation of additional quality gate to ensure completion and quality of testing documentation Implementation of Quality SOP to raise awareness of quality gates

Implementation of additional quality gate to ensure completion and quality of

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17 Thank You! Ellen Morrow Sr. Director, DM Standards and Solutions Quintiles, Inc Contact Information:

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