Tag Archives: Data management plan

Data Management Plan – Database Archive

Indicate how you intend to archive and share your data and why you have chosen that particular option.

The DMP should outline specific information regarding the organization’s procedures for archiving the electronic records.

Good practice for digital preservation requires that an organization address succession planning for digital assets.

Which criteria will you use to decide which data has to be archived? What should be included in the archive?

Type of data (raw, processed) and how easy it is to reproduce it. Also consider archiving audit trails as long as the records are (CRF Part 11, Section 11.10).

Does the archive have specific requirements concerning file formats, metadata etc.

It is recommended to use open source formats such as PDF-PDF/A, ODM-XML or ASCII type of files.

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Who is responsible for the data after the project ends?

Sponsor, CRO, Vendor? All should be documented on the DMP. Once database is locked, within a reasonable time and after data submission to a regulatory agency, you want to archive your database for long term storage and recovery.

While most data submitted to regulatory agencies are available in SAS formats, there may be times when going back to the original data format may be required.

Even though the easiest way to make sure data is available after database lock is to archive this data in the built in structure as the current system. For example, for Medidata Rave studies, trials are built on on top of SQL server, hence, you should consider archiving the old studies in a compatible format of SQL Server, without any transformation or data manipulation = raw data.

Other formats for data archive can be considered are ODM XML, PDF-PDF/A or ASCII A-8. These are some options for long=term storage. FDA says in the guidance document for 21 CFR Part 11, ‘scope and application – section C.5″, “FDA does not intend to object inf you decide to archive required records in electronic format to nonelectronic media….As long as predicate rule requirements are fully satisfied and the content and meaning of the records are preserved and archived, you can delete the electronic version of the records”.

Archival Plan

For archiving data, this plan should list all the components of the orginal system that will be included in the archive and the formats being used for their storage.

The best practices for clinical data archiving in clinical research are no different from those for archiving any other kind of industry.

 

 

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“Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for “fair use” for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use.”

Anayansi Gamboa has an extensive background in clinical data management as well as experience with different EDC systems including Oracle InForm, InForm Architect, Central Designer, CIS, Clintrial, Medidata Rave, Central Coding, OpenClinica Open Source and Oracle Clinical.

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Data Management Plan – Protocol Summary

This usually describes the management plan for the data collected  during the project. It is a brief description or synopsis of  the protocol.

The protocol, in terms of a clinical research study, is the plan, or blueprint, that
describes the study’s objectives, methodology, statistical considerations, and the organization of the study. [CDISC.org Oct. 2012]

Protocol Summary
Protocol Summary – current state of ‘standardization’ of a protocol document

 

 

 

 

 

 

 

 

 

 

 

 

 

What to look for when reading a protocol?

  • Review of T&E – Time and Event Schedule or Visit Schedule.
  • Assessments e.g. ECGs, PE (physical exams), MH-MedHix or Medical HIstory, labs and more.
  • Critical data variables for analysis. e.g. efficacy and safety data

 

proc print data= work.demog;
where patient in(“&pid”) and page=’3′;
var patient SBJINT page
dob sex bmi weight height;
title ‘Page 3 – Demog’;
run;

-FAIR ;USE-
“Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for “fair use” for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use.”

Anayansi Gamboa has an extensive background in clinical data management as well as experience with different EDC systems including Oracle InForm, InForm Architect, Central Designer, CIS, Clintrial, Medidata Rave, Central Coding, Medrio, IBM eCOS, OpenClinica Open Source and Oracle Clinical.

 

How to document the testing done on the edit checks?

Since the introduction of the Electronic Data Capture (EDC) in clinical trials where data is entered directly into the electronic system, it is estimated that the errors (e.g. transcription error) have been reduced by 70% [ Clinical Data Interchange Standards Consortium – Electronic Source Data Interchange 2005].

The Data Management Plan (DMP) defines the validation test to be performed to ensure data entered into the clinical database is complete, correct, allowable, valid and consistent.

Within the DMP, we find the Data Validation Plan. Some companies call it ‘DVS’ others ‘DVP’.  The Good practices for computerized systems in regulated GxP environments defines validation as a system that assures the formal assessment and reporting of quality and performance measures for all the life-cycle stages of software and system development, its implementation, qualification and acceptance, operation, modification, qualification, maintenance, and retirement.

As an {EDC} Developer or Clinical Programmer, you will be asked to:

  • Develop test scripts and execution logs for User Acceptance Testing (UAT).
  • Coordinate of UAT of eCRF build with clinical ops team members and data management and validating documents, included but not limited to: edit check document, issue logs, UAT summary report and preparation and testing of test cases.

Remember not every EDC system is alike. Some systems allow you to perform testing on the edit checks programmed; others allow you to enter test data on a separate instance than production (PROD).

Data Validation and UAT Module.png

For example, some EDC systems facilitate re-usability:

  1. There is a built-in test section for each study – where data can be entered and are stored completely separate from production data. This allows you to keep the test data for as long as needed to serve as proof of testing.
  2. The copy function allows for a library of existing checks (together with their associated CRF pages) to be copied into a new study. If there are no changes to the standard checks or pages then reference can be made back to the original set of test data in a standards study, thus reducing the study level overhead.
  3. The fact that many of the required checks (missing data, range checks, partial dates etc.) do not require the programming of an edit check at all. Each of these and many others are already there as part of the question definition itself and therefore do not need any additional testing or documentation for each study.

If you have not documented, you have not done it-FDA

The “ideal world” scenario would be to reduce the actual edit check testing by the system generating a more “human readable” format of the edit checks. The testers that way would not have to test each boundary conditions of the edit checks once the system is validated. All they would have to do is inspect the “human readable” edit checks vs the alerts and would also be easy for the clients to read and sign off.

You can leverage the EDC systems audit trail under certain conditions. First of all – the system you are testing with must be validated in itself. Some EDC products are only ‘validated’ once a study is built on top of them – they are effectively further developed as part of a study implementation process – in this situation, I would doubt you could safely use the audit trail.

Secondly, you need to come up with a mechanism whereby you can assure that each edit check has been specifically tested – traceability.

Finally, you need to secure the test evidence. The test data inside the EDC tool must be retained for as long as the archive as part of the evidence of testing.

The worst methods in my view are paper / screenshot based. They take too long, and are largely non-reusable. My past experience has been creating test cases using MS Word then performing each step as per test case and take a screenshot, where indicated. Then attached to the final documentation and validation summary. This obviously a manual and tedious process. Some companies create test cases using HPQC or similar tool. This is a bit more automated and traceable yet, it is still prone for errors. It is better than documenting using MS Word or Excel but it is still a manual process.

Re-usability is what it is all about, but, you need to ensure you have methods for assuring the test evidence produced for edit checks you are reusing is usable as part of the re-use exercise.

Edit Check Design, Development and Testing is the largest part of any typical EDC implementation. Applying methods to maximize quality and minimize time spent is one of the areas I have spent considerable time on over the last couple of years.

For additional tips on writing effective edit checks please go here -Effective edit checks eCRFs.

To hire me for services, you may contact me via Contact Me OR Join me on LinkedIn

Source images: provided courtesy of Google images.

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“Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for “fair use” for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use.”

Data Management Plan in Clinical Trials

 

The preparation of the data management plan (DMP) is a simple, straightforward approach designed to promote and ensure comprehensive project planning.

The data management plan typically contains the following items. They are:

  1. Introduction/Purpose of the document
  2. Scope of application/Definitions
  3. Abbreviations
  4. Who/what/where/when
  5. Project Schedule/Major Project Milestones
  6. Updates of the DMP
  7. Appendix

The objective of this guidelines is to define the general content of the Data Management Plan (DMP) and the procedures for developing and maintaining this document.

The abbreviation section could include all acronyms used within a particular study for further clarification.

e.g. CRF = Case Report Form
TA = Therapeutic Area

The Who/What/Where/When section should describe the objective of the study specific data management plans for ABC study. This section provides detail information about the indications, the number of subjects planned for the study, countries participating in the clinical trial, monitoring guidelines (SDV) or partial SDV, if any CROs or 3rd party are involved in the study (e.g. IVRS, central labs), which database will be used to collect study information (e.g. Clintrial, Oracle Clinical, Medidata Rave or Inform EDC).

The Appendix provides a place to put supporting information, allowing the body of the DMP to be kept concise and at more summary levels. For example, you could document Database Access of team members, Self-evident correction plan, Data Entry plan if using Double-data entry systems or Paper-Based clinical trials systems.

Remember, this is a living document and must be updated throughout the course of the clinical trial.

If problems arise during the life of a project, our first hunch would be that the project was not properly planned.

Reference: Role of Project Management in Clinical Trials
Your comments and questions are valued and encouraged.
Anayansi Gamboa has an extensive background in clinical data management as well as experience with different EDC systems including Oracle InForm, InForm Architect, Central Designer, CIS, Clintrial, Medidata Rave, Central Coding, OpenClinica, Open Source and Oracle Clinical.

To hire me for services, you may contact me via Contact Me OR Join me on LinkedIn

Disclaimer: The legal entity on this blog is registered as Doing Business As (DBA) – Trade Name – Fictitious Name – Assumed Name as “GAMBOA”.

Role of Project Management and the Project Manager in Clinical Data Management

 

The Project Manager is responsible for the development, oversight of implementation, and communication of clinical research studies.

So what is a Project?

A project is a work effort with a definite beginning and end, an identifiable end result (deliverable), and usually has limits on resources, costs and/or schedule.

What is Project Management?

The application of knowledge, skills, tools, and techniques to project tasks in order to meet project requirements.

In order to be a successful project manager, you need to understand the “Tripple Constraint” and how they affect your project. Let’s look up the WBS-edit checks:

Note: I will refer a project = clinical study

Scope: What is in the contract? How many edit checks, SAS checks and manual checks are required in this study? What is the effort per edit check, SAS check and manual check?

The goal is to convert the idea of data management to that of statistical analysis – an analyzable database.

Time: What are the deliverables and timelines? What resources are needed?

Cost: What are the budget restrictions? Are there any risks associated with any changes?

Project Planning: During the planning of a clinical study, we identify the project scope, develop the project management plan and we identify and schedule the clinical study activities.

Some questions might arise during the project planning phase: how many sites/subjects and pages will be collected?Who will attend team meetings? what study fields will be code (i.e. Adverse Event term)?

Other important activities that the project manager and clinical team members will need to be involved:

Work Break Down (WBS) – it is the list of activities that will be performed during the course of a clinical study.

Resourcing – it is important to assign the right person to a particular task based on skills, education and experience.

ICH Guidelines ‘…all personnel involved in clinical trials must be qualified and properly trained to perform their respective tasks…’

Estimating Cost – look at historical data as well as good estimates from effort per unit and units using your WBS as references.

Scheduling and Budgeting – you will be able to build schedules and budgets that transform project constraints into project success after you successfully construct your Work Breakdown Structures (WBS) and network diagrams and estimate task durations.

Projects managers used techniques for employed to establish project. Project Manager can decide which activity can be delayed without affecting the duration of the projects. They help improving quality and reduce the risks and costs related with the projects.

A recent survey by the Project Management Institute provided 10 challenges affecting project managers. This research intended to identify key factors affecting project team performance:

  1. Changes to Project Scope (Scope Creep)
  2. Resources are Inadequate (Excluding Funding)
  3. Insufficient Time to Complete the Project
  4. Critical Requirements are Unspecified or Missing
  5. Inadequate Project Testing
  6. Critical Project Tasks are Delivered Late
  7. Key Team Members Lack Adequate Authority
  8. The Project Sponsor is Unavailable to Approve Strategic Decisions
  9. Insufficient Project Funding
  10. Key Team Members Lack Critical Skills

Another question to ask is what tools are available to help you get the job done?

  1. Resource allocation (and the software’s ability to easily display staff who were overallocated)
  2. Web-based/SaaS option
  3. Cost/Price of the system (big one!)
  4. Contractual terms we could enter into (i.e. 6 months, 12 months, month to month)
  5. Ability to demo the software and for how long
  6. What sort of customizations could be made to the software after purchase
  7. Types of customers the software has served
  8. Report types
  9. Ability to sync with accounting software and which ones, if so
  10. Timeline generation capabilities and import function with MS Project
  11. Ability to create template projects
  12. Ability to alert on early warning signs (i.e. budget overruns over 10%)

It is suggestted that you review each suggestion on project management tool very, very carefully to determine how it fits your processes.

Your organization’s processes are unique to your organization; no other organization anywhere has quite the same processes. So what may work for one organization may not necessarily work for you. Your organization developed its processes to suit your particular corporate culture, the particular collective character attributes of the employees (their experience, etc.), the type of projects that you execute and the particular types customers/clients that you have (especially the regular ones).

You now have to make sure that the tools you choose work for you and your particular processes. Do not change your processes again to suit whatever workflow (process) is dictated by the fancy tool that the fancy salesman sold to you; you are likely to find that the tool-dictated workflows do not work that well in your organization, with the result that the employees will give up following processes and/or give up using the tool, throwing everything into chaos again.

Be careful if you are looking at tools that offer to do a number of different functions or can be made to do any function you want it to do. They seldom do the job that you bought it for particularly well. For example, I have worked with a tool that was advertised as a combination issue tracking and defect/bug tracking tool. It was used as a defect tracking tool but it was very poor; it was tremendously difficult to make it prepare useful reports. A hand-written tool set up in a spreadsheet (e.g. Microsoft Excel) or database (e.g. Microsoft Access) would have worked better.

That said, there are tools out there that are specific to one particular function but do offer flexible workflows – they may be modified to match whatever processes your organization already follows.

If your organization has just started to organize the PM processes and PMO that would mean processes & other related areas are not explicitly defined. So there may be a huge risk trying to adopt an integrated and centralized project management system. It is more likely to offer you a very comprehensive, complex but expensive solution wherein your problem is still not defined completely. In such a case you are just not ready with the environment and process maturity that an integrated tool requires prior to implementation.

A more efficient approach should be iterative, incremental and adaptive in nature. That means you shall use simple, not so expensive tools with limited scope to begin with; they can be tools with basic functionalities of WBS, scheduling, traceability and custom datasheets. These tools should have capability to exchange data both ways with more commonly uses tools like MS Excel, MS Project, and Word etc. The processes are likely to mature over time and we will then know the real effectiveness of these basic tools in the context of company requirements. That may be the time to analyze and switch to more integrated solutions.

One important key to remember. The role of project management in clinical trials is evolving. There is a debate about who should be the ‘project manager’ for a particular clinical study. CRA or Clinical Data Manager or an independent project manager? Let’s review their roles within data management.

Clinical Research Associate (CRA): main function is to monitor clinical trials. He or she may work directly with the sponsor company of a clinical trial, as an independent freelancer or for a Contract Research Organization (CRO). A clinical research associate ensures compliance with the clinical trial protocol, checks clinical site activities, makes on-site visits, reviews Case Report Forms (CRFs) and communicates with clinical research investigators. A clinical research associate is usually required to possess an academic degree in Life Sciences and needs to have a good knowledge of Good clinical practice and local regulations. In the United States, the rules are codified in Title 21 of the Code of Federal Regulations. In the European Union these guidelines are part of EudraLex. In India he / she requires knowledge about schedule Y amendments in drug and cosmetic act 1945.

Clinical Data Manager (CDM): plays a key role in the setup and conduct of a clinical trial. The data collected during a clinical trial will form the basis of subsequent safety and efficacy analysis which in turn drive decision-making on product development in the pharmaceutical industry. The Clinical Data Manager will be involved in early discussions about data collection options and will then oversee development of data collection tools based on the clinical trial protocol. Once subject enrollment begins the Clinical Data Manager will ensure that data is collected, validated, complete and consistent. The Clinical Data Manager will liaise with other data providers (eg a central laboratory processing blood samples collected) and ensure that such data is transmitted securely and is consistent with other data collected in the clinical trial. At the completion of the clinical trial the Clinical Data Manager will ensure that all data expected to be captured has been accounted for and that all data management activities are complete. At this stage the data will be declared final (terminology varies but common descriptions are Database Lock and Database Freeze) and the Clinical Data Manager will transfer data for statistical analysis.

Clinical Data Management (CDMS) Tools: (we will review each of them on a separate discussion)

  • Standard Operating Procedures (SOPs)
  • The Data Management Plan (DMP)
  • Case Report Form Design (CRF)
  • Database Design and Build (DDB)
  • Validation Rules also known as edit checks
  • User Acceptance Testing (UAT)
  • Data Entry (DE)
  • Data Validation (DV)
  • Data Queries (DQ)
  • Central Laboratory Data (CLD)
  • Other External Data
  • Serious Adverse Event Reconciliation (SAE)
  • Patient Recorded Data (PRO)
  • Database finalization and Extraction
  • Metrics and Tracking – see BioClinica article on Metrics
  • Quality Control (QC)- see discussion on A QC Plan for A Quality Clinical Database

In conclusion, a key component of a successful clinical study is delivering the project rapidly and cost effectively. Project managers must balance resources, budget and schedule constraints, and ever-increasing sponsor expectations.

Source:

To hire me for services, you may contact me via Contact Me OR Join me on LinkedIn
Anayansi Gamboa has an extensive background in clinical data management as well as experience with different EDC systems including Oracle InForm, InForm Architect, Central Designer, CIS, Clintrial, Medidata Rave, Central Coding, OpenClinica Open Source and Oracle Clinical.