STUDY START UP/STUDY SET UP:
eCRF(case report form):
The case report form is a printed or electronic questionnaire for collecting data from study participants and reporting it to trial sponsors. The document is created specifically for each research project in accordance with
the trial protocol, and
recommendations of the Clinical Data Acquisitions Standards Harmonization (CDASH). They are developed by Clinical Data Interchange Standards Consortium to streamline industry-wide data exchange. Say, CDASH dictates dd/mm/yy format for collecting dates. (Read our article on CDISC standards to learn more.)
Well-designed case report forms collect only data necessary for the particular study avoiding any redundancy. The fields to be filled in may include
demographics (age, gender),
basic measurements (height, weight),
vital signs (blood pressure, temperature, etc.) captured at various time points,
lab exams,
medical history,
adverse events, and
more, based on the research requirements.
Data managers create data entry screens and eCRF layouts in collaboration with a database programmer. The design usually goes through several review cycles before finalization.
Crf pfd
Compare crf pdf with protocol
eCRF specification-prepare
Explain ecrf spec to programmer
Draft ecrf Review,updates and changes
Final ecrf
Ecrf in EDC(electronic data management)
Compare ecrf spec with EDC
EDIT CHECK DOCUMENT:
Edit check document
Edit check specification
Manual query and automated query
Dynamics
Populate a query in edc
Provide edit check specification parallel with ecrf specification to programmer
Compare edit check specifications with edc
UAT(user acceptance testing):
Role testing: testing role for team members like access
Screen testing
Structural functionality
Edit checks
Any of the data which falls out of range it should populate a query and for any thing which falls within a range that it express should not populate a query
LAB values-enter in UAT
Sponsor DM—CRO DM—LNR(lower normal range) template—Lead CRA(site)---Fill(template)---CRO CM—EDC —---manual,automated
eCRF completion guidelines
.What you don’t know about study startup activities as Clinical Data Manager
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Often when you hear Study start up activities as clinical data manager, your typical thought process includes
Get Protocol & review ---> Study Kick off Meeting --> Start Building EDC (eCRF's & Edits) --> Screen Review meeting --> UAT --> Go live
However 𝘁𝗵𝗶𝘀 𝗶𝘀 𝗼𝗻𝗹𝘆 𝗮 𝗽𝗲𝗿𝘀𝗽𝗲𝗰𝘁𝗶𝘃𝗲 from Clinical Data Management.
When you consider the study 𝘀𝘁𝗮𝗿𝘁-𝘂𝗽 𝗽𝗵𝗮𝘀𝗲 𝗮𝘁 𝗰𝗹𝗶𝗻𝗶𝗰𝗮𝗹 𝘁𝗿𝗶𝗮𝗹 𝗹𝗲𝘃𝗲𝗹, you will see whole different picture and in the clinical data Management is one critical step.
So let's explore the 𝗯𝗶𝗴𝗴𝗲𝗿 𝗽𝗶𝗰𝘁𝘂𝗿𝗲 of study Start-up activities
⭐ 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁: The first step in the study start-up phase is protocol development. This protocol includes the study design, inclusion/exclusion criteria, data collection forms, and procedures for data analysis.
⭐𝗘𝘁𝗵𝗶𝗰𝘀 𝗖𝗼𝗺𝗺𝗶𝘁𝘁𝗲𝗲 𝗮𝗻𝗱 𝗥𝗲𝗴𝘂𝗹𝗮𝘁𝗼𝗿𝘆 𝗔𝘂𝘁𝗵𝗼𝗿𝗶𝘁𝘆 𝗔𝗽𝗽𝗿𝗼𝘃𝗮𝗹: Before the study can start, it must receive approval from the relevant ethics committees and regulatory authorities.
⭐ 𝗜𝗱𝗲𝗻𝘁𝗶𝗳𝘆 & 𝗦𝗲𝗹𝗲𝗰𝘁 𝗦𝗶𝘁𝗲𝘀 : The sites are identified based on several factors, such as the patient population, regulatory environment, and availability of qualified investigators etc.
⭐𝗜𝗻𝘃𝗲𝘀𝘁𝗶𝗴𝗮𝘁𝗼𝗿 𝗮𝗻𝗱 𝗦𝗶𝘁𝗲 𝗤𝘂𝗮𝗹𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻: The investigators and staff from the site must meet certain qualifications and experience requirements before they can participate in the study.
⭐ 𝗖𝗼𝗻𝘁𝗿𝗮𝗰𝘁𝘀 𝗮𝗻𝗱 𝗕𝘂𝗱𝗴𝗲𝘁𝘀: Once the sites selection is completed, contracts are negotiated and budgets are developed. These contracts and budgets define the terms of the study, including compensation for the investigators and site staff.
⭐ 𝗦𝗶𝘁𝗲 𝗜𝗻𝗶𝘁𝗶𝗮𝘁𝗶𝗼𝗻 𝗩𝗶𝘀𝗶𝘁 (𝗦𝗜𝗩): The SIV (Site Initiation Visit) serves the purpose of training and ensuring that the Principal Investigator (PI) and their staff fully understand the protocol and Good Clinical Practice (GCP) requirements related to all aspects of the study.
⭐ 𝗧𝗿𝗶𝗮𝗹 𝗠𝗮𝘀𝘁𝗲𝗿 𝗙𝗶𝗹𝗲 (𝗧𝗠𝗙) 𝗦𝗲𝘁𝘂𝗽: A Trial Master File (TMF) is set up to manage all the study-related documents. The TMF includes the protocol, study plans, and other essential documents required for the study.
⭐ 𝗜𝗻𝘃𝗲𝘀𝘁𝗶𝗴𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁: Investigational product management includes the distribution, tracking, and management of the study drug or device.
⭐𝗗𝗮𝘁𝗮 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴: here is where clinical data managers comes in and perform all the critical steps required for data base go live.
As you can see study start-up activities includes more steps then one does in CDM. Also many companies follow additional steps as per their SOP's / SOW.
This phase has immense downstream impact on study conduct and closeout stages & clean study start-up activities can save whole lot of time, money & rework.
We can Categorize study startup activities in to 3 main headings.
𝟭. 𝗘𝗗𝗖 𝗗𝗮𝘁𝗮𝗯𝗮𝘀𝗲 𝗗𝗲𝘀𝗶𝗴𝗻
𝟮. 𝗨𝗔𝗧 𝗧𝗲𝘀𝘁𝗶𝗻𝗴
𝟯. 𝗠𝗲𝗲𝘁𝗶𝗻𝗴𝘀
Let's Learn them one by one:
𝗘𝗗𝗖 𝗗𝗔𝗧𝗔𝗕𝗔𝗦𝗘 𝗗𝗘𝗦𝗜𝗚𝗡
EDC (Electronic Data Capture) is an essential component of study start-up, which allows clinical trial data to be collected, managed, and analysed in a more efficient and accurate way.
So what goes into EDC design?
𝟭. 𝗖𝗹𝗲𝗮𝗿 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝗼𝗳 𝘀𝘁𝘂𝗱𝘆 𝗿𝗲𝗾𝘂𝗶𝗿𝗲𝗺𝗲𝗻𝘁𝘀 𝗳𝗿𝗼𝗺 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹:
All the data that needs to be collected in the study has to be mapped back to study protocol. So clear understanding of study data requirements from the protocol crucial. This link has detailed explanation about how Data Manager need to review Study protocol : https://www.slideshare.net/slideshow/protocol-document-in-clinical-research/267027997
𝟮. 𝗜𝗻𝗽𝘂𝘁𝘀 𝗳𝗿𝗼𝗺 𝗖𝗹𝗶𝗻𝗶𝗰𝗮𝗹 𝗦𝘁𝘂𝗱𝘆 𝘁𝗲𝗮𝗺 :
Here mainly we are focusing on the inputs from study team who brings the wealth of their experience in conducting clinical trials to enhance the study data collection steps or to avoid major issues. Also inputs regarding how study end points needs to be meet with right data collection, what are the challenges & risks in conducting the study
𝟯. 𝗖𝗮𝘀𝗲 𝗥𝗲𝗽𝗼𝗿𝘁 𝗙𝗼𝗿𝗺 (𝗖𝗥𝗙) 𝗗𝗲𝘀𝗶𝗴𝗻:
The CRF is the foundation of EDC design. It is a standardized questionnaire that captures data from study participants. The CRF must be designed in a way that is easy to understand, user-friendly, and collects all necessary data points required by the study protocol. SDTM / CDASH standards should be followed.
𝟰. 𝗗𝗮𝘁𝗮𝗯𝗮𝘀𝗲 𝗗𝗲𝘀𝗶𝗴𝗻:
The database must be designed to ensure data accuracy, consistency, and completeness. It should also be able to handle large volumes of data, have built-in data validation checks, and ensure data privacy and security.
𝟱. 𝗘𝗱𝗶𝘁 𝗖𝗵𝗲𝗰𝗸 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴:
To ensure data accuracy and completeness, the EDC system should have built-in data validation checks and edit checks. Edit checks are programmed to detect logical errors in the data. We use Edit Check spec to guide the programming team.
𝟲. 𝗠𝗲𝗱𝗶𝗰𝗮𝗹 𝗖𝗼𝗱𝗶𝗻𝗴, 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹 𝗗𝗲𝘃𝗶𝗮𝘁𝗶𝗼𝗻𝘀 (𝗣𝗗𝗦) & 𝗩𝗲𝗻𝗱𝗼𝗿 𝗗𝗮𝘁𝗮 𝘀𝗲𝘁𝘂𝗽 :
Medical coding is an important component of EDC that involves assigning standardized codes to medical terms, procedures, and diagnoses.
Similarly, PD's & all the required vendor data setup needs to included into EDC.
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Most important goal of a Clinical Data Manager is to ensure the consistency, quality & accuracy of clinical data. In this journey Edit check specification (ECS)plays a very crucial role to enable data cleaning.
ECS is created by DM’s with the input of study team member in clinical database build stage.
3 crucial things to understand about ECS
1. What are the pre-requisites to create / build ECS?
2. What are the checks to include in ECS?
3. What to avoid while writing ECS?
⭐ 𝗣𝗿𝗲-𝗿𝗲𝗾𝘂𝗶𝘀𝗶𝘁𝗲𝘀 𝘁𝗼 𝗰𝗿𝗲𝗮𝘁𝗲 / 𝗯𝘂𝗶𝗹𝗱 𝗘𝗖𝗦: To build an ECS that severs the CDM needs,
- One should have clear understanding of study protocol & eCRF data points collected.
- Data dictionary of the database (EDC) - this helps to understand the various attributes, definitions of the elements that are being used in database.
- Possible data entry scenarios & test data: This will help to create a correct edit checks to address all the possible data issues that can happen when study go live.
- List of critical data points such as study end points, AE / SAE data etc.
⭐ 𝗖𝗵𝗲𝗰𝗸𝘀 𝗶𝗻𝗰𝗹𝘂𝗱𝗲𝗱 𝗶𝗻 𝗘𝗖𝗦?
Based on the type, checks in ECS can be categorized into
a. Univariate checks (these checks only applicable to a single field or single variable ona eCRF.)
b. Multi-variate Checks (edit checks with more than one fields or variables involved.)
c. Programmed Checks (they will fire as soon wrong data is entered)
d. Manual Checks ( need to run manual programs on the data & output reports are analyzed for data issues)
Based on core function – checks that are included in ECS can be categorized into
1. Missing data & eCRF checks : these checks ensure all the critical data points & eCRF’s are collected as needed (Ex : Missing inform consent date / missing Vital sign forms etc
2. Range Checks & format checks: they raises a query when entered value is out of range or format - specified for data collection point (ex: height, weight dates, time etc
3. Checks for Duplicate data: These checks alerts sites / DM when duplicate data is entered. Ex: Entering same AE event twice
4. Protocol deviation checks : These are must have checks to flag PD’s
5. External Data Checks : These check will ensure data quality of external data such as labs data, ECG etc
6. Inconsistency across single CRF & other eCRF’s : These will check inconsistencies on the same eCRF form across eCRF forms.
⭐ 𝗪𝗵𝗮𝘁 𝘁𝗼 𝗮𝘃𝗼𝗶𝗱 𝘄𝗵𝗶𝗹𝗲 𝘄𝗿𝗶𝘁𝗶𝗻𝗴 𝗘𝗖𝗦?
1. Avoid complicate queries messages – this will hurt sites
2. Avoid placing too many edit checks in a form or visit
3. Avoid leading /probing/ or guiding participants enter any data point in a particular way.
4. Do not blindly copy checks from other / sister studies.
User Acceptance testing (UAT)
.UAT is part of validation done by end users to ensure the database is built as per the study requirements. Before go live end users will be sponsors & internal testing team.𝗣𝘂𝗿𝗽𝗼𝘀𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗨𝗔𝗧 𝗶𝗻𝗰𝗹𝘂𝗱𝗲
1. To identify any issues or defects & address them before database go live
2. To gain feedback from end-users about the system's functionality, usability, and performance.
3. To document the validation steps for that serves as evidence of testing.
𝗜𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 𝗰𝗼𝗺𝗽𝗼𝗻𝗲𝗻𝘁𝘀 𝗼𝗳 𝗨𝗔𝗧 includes:
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.1. UAT Plan
2. Testcases
3. Mock data for testing
4. Documentation
5. Approvals
What you miss in UAT during study start-up will come back and haunt you as PPC in study conduct!! & this will cost you time, money and effort.
UAT is a critical component in ensuring the clear database go live during the study startup, also we do minor UAT testing’s during PPC implementation as well.
After handling multiple PPC’s that have raised due to start up issue, i can say how significant proper understanding & implementation of UAT is .
So let’s explore 5 critical steps to ensure successful UAT during study startup.
1. 𝗖𝗹𝗲𝗮𝗿𝗹𝘆 𝗱𝗲𝗳𝗶𝗻𝗶𝗻𝗴 𝘁𝗵𝗲 𝗨𝗔𝗧 𝗽𝗹𝗮𝗻:
UAT Plan is the heart of the testing, which defines what components of databases are tested ( eCRF’s edit checks etc). Clear UAT plan serves a long way in successful UAT.
2. 𝗖𝗿𝗲𝗮𝘁𝗲 𝗮 𝘁𝗲𝘀𝘁 𝗰𝗮𝗿𝗲 𝘁𝗵𝗮𝘁 𝗰𝗼𝘃𝗲𝗿𝘀 𝗺𝘂𝗹𝘁𝗶𝗽𝗹𝗲 𝘀𝗰𝗲𝗻𝗮𝗿𝗶𝗼𝘀
An experience clinical data managers can come up a multiple scenarios to be tested for a given data point on the eCRF’s, for example – on lab forms test cases need to written to test scenarios for blank data, values below or above the normal limits, checking for correct units etc.
3. 𝗠𝗼𝗰𝗸 𝗗𝗮𝘁𝗮 𝗲𝗻𝘁𝗿𝘆 & 𝘁𝗲𝘀𝘁𝗶𝗻𝗴
Mock data entry gives a real time experience for database tester to clearly test the eCRF’s or Edit checks – as it simulate the live data entry.
4. 𝗖𝗹𝗲𝗮𝗿 𝗨𝗔𝗧 𝘁𝗲𝘀𝘁𝗶𝗻𝗴 𝗱𝗼𝗰𝘂𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻
Missing / incomplete UAT documentation is one of the major audit findings one notice in study startup phase. Ensure to clear document UAT testing steps, checks that are failed, passed, and next round of testing for failed checks.
5. 𝗔𝗽𝗽𝗿𝗼𝘃𝗮𝗹𝘀 & 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗶𝗼𝗻
Proper closure of UAT is required to move ahead with go live of the study / PPC which includes complete approvals from database testers, data managers and study lead.
Ensure to keep a clear, open communication with study team about the UAT proceedings.
What 𝗰𝗼𝗺𝗽𝗼𝗻𝗲𝗻𝘁𝘀 𝗮𝗿𝗲 𝘁𝗲𝘀𝘁𝗲𝗱 𝗱𝘂𝗿𝗶𝗻𝗴 𝗨𝗔𝗧:
𝟭. 𝗲𝗖𝗥𝗙'𝘀: During UAT, eCRF functionality is tested for the completeness & accuracy of the entered data. Also dynamic visits and eCRF's are tested as well.
𝟮. 𝗘𝗱𝗶𝘁 𝗰𝗵𝗲𝗰𝗸𝘀: Edit checks are automated validation rules that flag potential errors or discrepancies in the data collected on the eCRFs. During UAT, edit check are tested to ensure that they are triggered correctly and are accurately detecting data anomalies with accurate queries.
𝟯. 𝗖𝗼𝗱𝗶𝗻𝗴: Coding refers to the process of assigning standardized medical codes to clinical trial data, such as adverse events or medications. During UAT, coding functionality is tested to ensure that the correct codes are assigned to the correct data in AE, MH & CM forms.
𝟰. 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹 𝗗𝗲𝘃𝗶𝗮𝘁𝗶𝗼𝗻𝘀 (𝗣𝗗'𝘀) are events that occur during a clinical trial that deviate from the study protocol. During UAT, PD tracking functionality is tested to ensure that deviations are being captured and documented accurately.
𝟱. 𝗜𝗩𝗥𝗦/𝗜𝗪𝗥𝗦 𝘀𝗲𝘁𝘂𝗽: 𝗜nt
er active Voice Response Systems (IVRS) and Interactive Web Response Systems (IWRS) are used to manage clinical trial supplies and randomization. During UAT, IVRS/IWRS functionality is tested to ensure that randomization is being performed correctly and that supplies are being tracked and managed accurately.
𝟲. 𝗩𝗲𝗻𝗱𝗼𝗿 𝗗𝗮𝘁𝗮 𝘀𝗲𝘁𝘂𝗽: During clinical trials, vendors may be contracted to provide data management services or technology platforms. During UAT, vendor data setup is tested to ensure that data is being transferred and managed accurately between the study team and the vendor.
During UAT all the errors are logged in defect tracking sheet subsequent rounds of testing is performed to address all the open errors.
Data Manager, Database Programmer & tester, Coding SME, Sponsor are involved in the UAT
𝗜𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 𝗠𝗲𝗲𝘁𝗶𝗻𝗴𝘀 𝗶𝗻 𝗦𝘁𝘂𝗱𝘆 𝗦𝘁𝗮𝗿𝘁-𝘂𝗽 :
⭐ 𝗦𝘁𝘂𝗱𝘆 𝗸𝗶𝗰𝗸 𝗼𝗳𝗳 𝗺𝗲𝗲𝘁𝗶𝗻𝗴
This meeting brings together all stakeholders involved in the study, including clinical research associates, clinical trial lead, statisticians, programmers (Database, SDTM, SAS) project managers, and the study sponsor to plan the study activities in details & also highlight any possible risks to the study.
⭐ 𝗦𝗰𝗿𝗲𝗲𝗻 𝗿𝗲𝘃𝗶𝗲𝘄 𝗺𝗲𝗲𝘁𝗶𝗻𝗴
In this meeting DM along with technical designer & database programmer, presents the eCRF's & edits to study sponsor for review and feedback on the initial EDC build.
This meeting happens before the UAT.
⭐ 𝗜𝗻𝘃𝗲𝘀𝘁𝗶𝗴𝗮𝘁𝗼𝗿 𝗺𝗲𝗲𝘁𝗶𝗻𝗴 (𝗳𝗼𝗿 𝗗𝗠 𝗽𝗿𝗲𝘀𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻)
Before database go live Data manager attends the Investigator meetings to give a complete overview of the EDC system to the PI, Sites, CRA's & other study personals.
The topics covered in the presentation include data collection process, including non-CRF data , sample case report forms (CRFs), CRF completion guidelines, data queries and self-evident corrections etc.
⭐ 𝗩𝗲𝗻𝗱𝗼𝗿𝘀 𝗠𝗲𝗲𝘁𝗶𝗻𝗴
DM will meet with various vendors who provide third party data such as central labs, imaging data, specialist labs etc, for EDC integration & work on documentations (such as Data Transfer agreement & specifications ) & test transfers before database go live to ensure things are in place.
𝗜𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 𝗗𝗼𝗰𝘂𝗺𝗲𝗻𝘁𝘀 𝗶𝗻 𝗦𝘁𝘂𝗱𝘆 𝗦𝘁𝗮𝗿𝘁𝘂𝗽 :
⭐ 𝗘𝗖𝗦
Edit check specification is a document that describes the rules and conditions that are used to validate the data entered into a clinical trial database.
⭐ 𝗗𝗮𝘁𝗮 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗣𝗹𝗮𝗻 (𝗗𝗠𝗣)
A document that outlines the procedures for collecting, managing, and analysing data for a clinical trial. (Know more here https://clinicalda.blogspot.com/2024/02/data-management-plan.html)
⭐ 𝗲𝗖𝗥𝗙 𝗲𝗻𝘁𝗿𝘆 𝗚𝘂𝗶𝗱𝗲𝗹𝗶𝗻𝗲𝘀
A set of instructions that provide guidance to clinical trial personnel on how to correctly and consistently enter data into the eCRF
⭐ 𝗗𝗮𝘁𝗮 𝗧𝗿𝗮𝗻𝘀𝗳𝗲𝗿 𝗔𝗴𝗿𝗲𝗲𝗺𝗲𝗻𝘁𝘀 (𝗗𝗧𝗔) & 𝗗𝗮𝘁𝗮 𝗧𝗿𝗮𝗻𝘀𝗳𝗲𝗿 𝗦𝗽𝗲𝗰𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 (𝗗𝗧𝗦). More details on DTS here https://clinicalda.blogspot.com/2024/03/dtadata-transfer-agreement.html
⭐ 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹 𝗗𝗲𝘃𝗶𝗮𝘁𝗶𝗼𝗻 𝗦𝗽𝗲𝗰𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀
Along with above mentioned documents, ensuring completeness of UAT documents, Database go live checklist & its approval are critical in study start-up.
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