cdm sharvari
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Sharvari Shukla
BiostatisticianCentre for modeling and simulation, University of Pune
sharvareeshukla@hotmail.cPh-09822414920
Clinical Data
Management
Module
9
mailto:Sharvareeshukla@hotmail.commailto:Sharvareeshukla@hotmail.com -
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Monitoring
Adverseeventreporting
Regulatoryrequirements
QualityControl
Lab
Management
Statistics
Data
Management
CLINICAL TRIAL
OPERATIONS
Recruitment
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What is CDM ?
TERM
CLINICAL
DATA
MANAGEMENT
REFERS TO
CLINICAL TRIAL
DRUG EFFECTS
DOCUMENTATIONANALYSIS and INTERPRETATION
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CDM Definition Clinical Data Management is the process used to
ensure the accuracy and integrity of data by defining
data flow and quality specifications
CDM is skillful handling of clinical trial information
to be used for statistical analysis and interpretation
by ensuring that data is Accurate, Complete andVerifiable
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Basic Research
Clinical Trials Care and Treatment
DataManagement
DATA MANAGERS Product Teams Project Teams Development Teams Multidisciplinary
Team Computerscience
Statistics Life sciences
Research
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Generate Quality Data
1. Complete2. Correct
3. Clean4. Reproducible5. Representative6. Valid
StatisticalAnalysis
AccurateInterpretation
Trial Report
Presentation
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Clinical Data: It is collection of details
from subjects for a particular drug in a
manner which allows its analysis andstatistical interpretation, with the intent to
discover potential beneficial effects and/ordetermine its safety and efficacy
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Case Report Form Designing
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What is a Case Report Form?
A printed, optical, or electronic document
designed to record all of the protocol required
information to be reported to the sponsor oneach trial subject
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Purpose
Collects relevant data in a specific format- in accordance with the protocol
- compliance with regulatory requirements
Allows for efficient and complete data
- processing, analysis and reporting
Facilitates the exchange of data across- projects and organizations esp. through
- standardization
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Collecting Extra DataExtra Data should not be collected
Is not ethical, as is unnecessary for the protocolfor which participant consented
May create more work for the study coordinator
resulting in longer study visits for theparticipant Results in greater chance for error Creates more work for the statistician as now
more data to be analyzed Takes away the focus from the critical data
points
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CRF and Protocol: Relation
Protocol determines what datashouldbe collected on the CRF
All data mustbe collected on theCRF if specified in the protocol
Data that will not be analyzedshould
notappear on the CRF
Protocol is a BIBLE for any Clinical Trialand
CRF is a TOOL to implement the protocol
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CRF Development: Guidelines
Collect data with all users in mind
Collect data required by the regulatory agencies and outlined
in the protocol
Be clear and concise with your data questions
Avoid duplication
Request minimal free text responses: open ended
Provide units to ensure comparable values
Allow adequate space for response
Use checkboxes wherever possible
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Provide instructions to reduce misinterpretations
Organize CRFs using a combination of visit and type of data
Provide choices for each questions as this allows for
computer summarization
Use None and Not done
Collect data in a fashion that:
- allows for the most efficient computerization
- similar data to be collected across studies
Test and improve the CRF before the trial begins CRF book needs to be finalized and available before an
investigator starts enrolling patients into a study
CRF Development: Guidelines
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Elements of the CRF
Three major parts: Header
Safety related modules
Efficacy related modules Module: block of specific questions CRF module(s) make up single CRF
page
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Header Information
MUST HAVE Study Number Site/Center Number Subject identification number
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Creating Safety Modules
Safety modules are the ones which are used to analyze thesafety of the patient
Select modules appropriate for your study Safety Modules usually include
Demographic Adverse Events Vital Signs Medical History/Physical Exam Concomitant Medications
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Creating Efficacy Modules
Efficacy modules are the ones which are used todetermine the drugs effectiveness
Designed for each therapeutic area based on the protocol Considered to be unique modules and can be more
difficult to develop Design modules following project standards for data
collection Follow general CRF design guidelines Define diagnostics required Include appropriate baseline measurements Repeat same battery of tests Define and identify
- key efficacy endpoints
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Importance of Standard CRFs
Prepares the way for data exchange
Removes the need for mapping during dataexchange
Allows for consistent reporting across protocols,
across projects Promotes monitoring and investigator staff
efficiency
Allows merging of data between studies
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CRF is used for
Subject tracking Data analysis and reporting
Reports to FDA on subject safety New Drug Application submissions
Support of labeling claims
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Flow of CRF Design Process
Reviewers
CRF Designer
CRF Book
Designs CRF from protocol
CRF Review Meeting Comments back to CRF designer
Updates CRF to incl. comments Review and Sign off Coordinate printing and distribution
Site
CRF Designer
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CRF Development Process
After the CRF book is approved Initiate the process for printing
Note: the Protocol must be approved before the CRF book is
approved and printed
After it is printed
Stored according to organizational guidelines
Printed and distributed to research sites
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Members of the CRF development team
representatives of clinical staff,
medical monitors, data entry/management,
ualit assurance and
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Properly Designed CRFs
Components/All of the CRF pages are reusable
Saves time
Saves money
+
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Poorly Designed CRFs
Data not collected Database may require modification
Data Entry process impeded Need to edit data Target dates are missed
Collected too much data Wasted resourcesin collection and processing
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Poorly Designed CRFs
=
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Clinical Database Design
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Data: Information
Database: A structured collection ofrecords or data that is stored in acomputer so that a program can consultit to answer queries
Database
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What is CDMS?
A Clinical Data Management System
is used in clinical research to manage
the data of a clinical trial
The clinical trial data gathered at the
investigator site in the Case Report
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Basic Functions of CDMS
Entry
Store
Validate
Retrieve
Creating Activity Reports
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Purpose of CDMS design
Collects relevant data in a specific format
- in accordance with the CRF
- compliance with regulatory requirement
Allows for efficient and complete data
analysis and reporting
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How this CDMS should be ???
Robust, flexible and powerful option for the studieswho want the data to have double data entry
Quick and easy availability of data entry screens from
a Graphical user interface Edit checks can be run on demand or scheduled to
run at the convenience of the data manager
Ability to handle multiple discrepancies in a userfriendly environment
Flexible reporting capabilities
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Formats of Data
Dates, times: specify format include 24 hrclock if applicable
Numeric data responses Few, if any, text fields Consistent coding (e.g., yes/no) Measurement units (e.g., in/cm, lb/kg, lab
units, dosing units) Option of unknown
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Members of the CDMS design team
Database Designer : Designs the database
Data Entry and Data ManagementPersonnel : Validate the database as per
the CRF
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Widely used CDMS
Oracle Clinical Clintrial Inform OpenClinica
In-house developed systems
D T ki / L i
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Data Tracking / LoggingWhy Track?
Data Management team must produce a database that is:
Accurate, Complete and Verifiable
It should be suitable for analysis by Biostatistics
Data Management may receive data in following formats:
CRF Pages
Lab Reports
Diary Cards etc
What to Track?
D t T ki / L i
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What should be Captured?
Data Management should capture following details:
Who received the data
From whom data was received
When it was received
Details of the data received
For which subject Number of pages received
Missing or Blank pages, if any
Reconcile pages received with transmittal form
Every company has its own data tracking form to capture
above detailsIt ma be electronic or manual
Data Tracking / Logging
Data Tracking / Logging
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Flagging Tracking Queries?
Tracking person should flag following tracking queries to data cleaningpersonal:
Header information is not consistent on all pages for a subject Initial is not matching on page 1 and page 2
Pages are not in good condition
Number of pages received not match with the transmittal
This may vary from company tocompany
Data Tracking / Logging
Data Tracking / Logging
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Data Logging
Data Management should log received data into Clinical Data Management
System (CDMS):
Enter Subject information in CDMS
Enter which all pages are received
Enter whether page is blank or filled
Data Tracking / Logging
Data Management should be able to generate following reports from CDMS:
Pages received by site, subject Missing page details
Blank page details
D T ki /
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Data Tracking /Logging
Working Copy
sent toData Entry
Original
Stored inArchive
CRF Received
CRF Logged by
Page
Photocopy or
Separate pages
Data Flow
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Protocol
CRF
Data Collection
Database Set-up
Data Logging
Clinical Study Report
Stats Analysis
SAS Programming
Database Lock
Query ManagementData Entry
Data Flow
Data Tracking QC Process
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Data Entry
Possible Methods for Data Entry
Most of CDMS provide following option for data entry :
Independent Double data entry with THIRD PERSON verification
Double data entry with INTERACTIVE verification
Single data entry with MANUAL review
Single data entry with NO review
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Understanding Data Entry
Understanding data entry: process of enteringdata from CRF to response fields in anyCDMS, following certain guidelines/SOPs
CRF
D t E t G id li
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Data Entry Guidelines
Data entry guideline should include
Field by field details on how to enter data
How to enter date, how to enter partial date
How to enter time, how to enter partial time
How to record blank pages
How to handle special characters (@, & sign etc..)
Any general instructions on the study
B f S i i h D E P
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Before Starting with Data Entry Process
Understanding 21 CFR Part 11, that is, Code ofFederal Regulations part 11 chapter 21
FDA defines that persons handling clinical data
have to be sufficiently trained & need to haveelectronic signatures of their own Therefore, each person will have electronic
signature as part of 21 CFR Part 11 compliance
We are all Trainedand we
haveour Elec. Signatures .
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Audit Trail & 21 CFR Part 11
Audit Trail means ... Record of Activities
Data entered, deleted,altered, updated etc.
E-signature help usidentify who did what?
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Data Entry Screen
UNDERSTANDING
DATA ENTRY
RIGHT SIDESCANNED CRF IMAGE
LEFT SIDECDMSSCREEN
CDMS
CRF
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Types of Data Entry
Double Entry
Single Entry
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Data entry
manual verification
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Double data entr
Data entry second data entry
Discrepancies resolved
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Refers to data beingentered to databasefor first time
DEO enters all dataof each document &releases work item
First PassData Entry
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SecondPassData Entry
2
Second pass entry done by another DEO,following first entryThis becomes first quality check in CDMprocessBoth DEO & system contribute to this firstquality check in CDM processSystem gives an alert if second pass entersanything different from first pass
Correct value is confirmed & entered
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Dealing with Different Kinds of Data
DEO (Data Entry Operator) should be aware ofkind of data to be entered
Also, awareness of project specific guidelines &standard guidelines is a must
Data types
DATES/EVENT
S MEDICAL
TERMINOLOGI
ES
NUMERICA
L
DATA
ABBREVIATIONS
GENERAL &
MEDICAL
D
AT
A
DD-MM-YYYY
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Handling Dates ??
Recording dates on case report forms -plays very
integral part DEOs must know different schemes of recording
dates Indians follow dd-mm-yyyy pattern Americans follow mm-dd-yyyy pattern Few European countries follow yy-mm-dd pattern
M di l T i l i
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Medical Terminologies
DEOs should encouragethemselves from beginning toverify (use online sources) & beaware of spellings of variousmedical terminologies
Essential because a slightchange or mis-spelt term canmean totally different
Also, many medical
terminologies have more thanone way of spelling
ReferOnlineSources
Check MySpellingsTwice !!
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During entering data,DEOs have liberty ofentering comments - calledOperator Comments fora particular data point
Operator commentsentered when DEOs are notsure about any illegible text/unclear text
Also, if data is recorded inan erroneous way, operatorcomments can be recorded
InsertComment
If NotSureok
Yes..PointNoted
Stop Entering If NotSure
S T O P !!!
Operator
Comment
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Heads-Up Data Entry
I ReviewData As I EnterData
Also called thinking dataentry personsThey raise a flag when data isillegible for data reviewers or datamanagers
mp y put, t ese entry personne
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Heads-Down enter what they see on CRF Entry faster as they follow natural
flow of CRF
Skill emphasis on number of
keystrokes made and specific
training on database to be utilized
Second pass entry provided after
i l bl
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Single Entry versus Double Entry
FDA & ICH regulations do not require doubleentry or any other specific data entry process
Skill level of resource, time availability and costcontribute to choice of entry process
Double entry helpful where data are subject tofrequent random keystroke errors or where arandom error would be likely to impact the
analysis Single entry with good manual review can be
better than a sloppy double entry one
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Click to edit Master subtitle style
Edit Check Programming
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Edit Check - Definition
An auditable process, usually
automated, of assessing the content of a
data field against its expected logical,
format, range or other properties that is
Wh t i Edit Ch k ???
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What is an Edit Check ???
Edit Check = Validation
Validation is the process of checking if something
satisfies a certain criterion
It is important because it disallows data that cannot
possibly be either true or real to be entered into a
database or computer system
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Purpose of Edit Check Programming
It is a tool used for data clean up so as to
ensure that the data which is entered in
the Database is error free and can be
send for analysis
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Where do we define Edit Checks ???
The Edit Check Programmer defines /creates Edit Checks as defined in the Data
Validation Plan
These edit check programs are defined inthe study database
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Types of Edit Checks
Simple Edit Check (Diastolic BP greater than
Systolic BP)
Edit Check with an Arithmetic Function(Difference between Systolic and Diastolic BP >
20)
Complex Edit Check (comparison of onset andresolved date of an Adverse Event)
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Data Clarification Form
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Members of the Edit CheckProgramming team
Edit Check Programmer : Creates the
Edit Check Programs
Data Management Personnel : Validate
the edit check programs as per the Data
Validation Plan
Testing of Edit Check Programs
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EC Programmer writesEC programsReceipt of EC Plan
from DM
DM tests EC programs
EC Program is final andready for production
Testing of Edit Check Programs
Execution o E it C ec Programs
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Execution of EC programs
on production
Review of discrepancies
Update DCF resolution in
DBAll discrepancies are updated
Send DCFs toInvestigator, if required
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Quality Assurance is a process Quality Control is a check of process
Accuracy of data entry checked by auditing
data stored in database against CRF
Ongoing internal and external audits
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Quality Control
Protocol Data Collection Data Processing
Data Analysis CSR
Applied at all steps throughout the trial
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Data that supports conclusions andinterpretations equivalent to those
derived from error-free data
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Advantages of a Data Quality Inspection
Savings on time and money Post db lock, data would be labeled
uncorrectable and excluded from analysis
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How does one improve the quality of data?
Engineer data quality into the process- creating systems that limit the opportunity for
errors Collect only data directly related to the outcome
variable Do it right the first time Do it right
- at the site Remember
data quality is defined at the field!
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Quality must be measured, before
it can be controlled
How does one measure quality?
Error rates
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What are Error Rates?
Error rate = No. of errors / no. of fields inspected
Data quality can be compared across data sets and
across trials
Data quality does not mean -
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Data quality does not mean checkin for ever ossible error
Fields critical to analysis
Identify points with a high frequency of error
Cover data points where a high percentage of error
resolution is possible
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Data Integrity
Data is complete
Data is reliable
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The key to the success of any clinical
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Database closure
Checklist of database closure Generation of final reports
Archiving database and associateddocumentation
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Statistical anal sis
Preparation of Table, graphs and listing Handling of missing values and outliers Scope of evaluation
SAS report generation Statistical analysis and report generation Archiving data and documents
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Thank you
sharvareeshukla@hotmail.com
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