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7 questions to ask yourself before you choose to set up your own Clinical Data Management department

The arguments to set-up your own Clinical Data Management department are various. You want to learn something new. You can do Clinical Data Management yourself because you could allocate resources for it. Conducting Clinical Data Management in-house could get you more in control of your clinical study data. Clinical Data Management done in-house could cost you less. You could perform Clinical Data Management better yourself. You want to spend your Clinical Data Management budget internally. You see a chance to make (more) money. You see a chance to (better) serve your Customers. You want to complete the gap in your clinical service(s).

Before you make the final decision you could ask yourself 7 questions:
1. For what type of studies should I want to conduct clinical data management myself? For all the studies I conduct? For the first clinical trials in the market application process? For phase III/IV clinical trials? Or for clinical studies conducted post registry?

2. Does a Clinical Data Management group fit in, and does it add value to my company’s core business? Is dedication to the Clinical Data Management performance part of my daily business targets?

3. Do I have enough studies, enough workload for Clinical Data Management to return investments? Is the cost-benefit ratio in my advantage?

4. Can I allocate enough resources, e.g. time, capacity, knowledge and money to the Clinical Data Management department to get clinical data quality from it?

5. Is this the right moment? Right now, should I invest in setting up a new department in my company? Is my company ready for the next step; an own Clinical Data Management group?

6. What are the benefits for my organization when we can conduct Clinical Data Management ourselves? What will it bring us?

7. What are the requirements for this Clinical Data Management department regarding the type of studies and the amount of studies. What are our user requirements for a Clinical Data Management system(s)? What is the capacity we need to handle that Clinical Data Management system and what information do we need?

The number one question in my experience; is a Clinical Data Management department a logical fit within your companies core dedication? Logical like ‘clinical research to get your products accepted for marketing’ or ‘providing clinical research services’. Dedicated Clinical Data Management can start returning investments.

Source:

This is an ezine of Maritza Witteveen of ProCDM. For Clinical Research Directors who struggle with clinical data management to get reliable, quality clinical study data successfully. Receive tips and the free e-book ‘Five strategies to get reliable, quality clinical data’ by subscribing via http://www.procdm.nl/pages/knowledgebase.asp.

Comments? Join us at {EDC Developer}

Anayansi Gamboa, MPM, an EDC Developer Consultant and clinical programmer for the Pharmaceutical and Biotech industry with more than 13 years of experience.

Available for short-term contracts or ad-hoc requests. See my specialties section (Oracle, SQL Server, EDC Inform, EDC Rave, OpenClinica, SAS and other CDM tools)

As the 3 C’s of life states: Choices, Chances and Changes- you must make a choice to take a chance or your life will never change. I continually seek to implement means of improving processes to reduce cycle time and decrease work effort.

Subscribe to my blog’s RSS feed and email newsletter to get immediate updates on latest news, articles, and tips. I am available on LinkedIn. Connect with me there for technical discussions.

Fair Use Notice: This article/video contains some copyrighted material whose use has not been authorized by the copyright owners. We believe that this not-for-profit, educational, and/or criticism or commentary use on the Web constitutes a fair use of the copyrighted material (as provided for in section 107 of the US Copyright Law. If you wish to use this copyrighted material for purposes that go beyond fair use, you must obtain permission from the copyright owner. Fair Use notwithstanding we will immediately comply with any copyright owner who wants their material removed or modified, wants us to link to their website or wants us to add their photo.

Disclaimer: The EDC Developer blog is “one man’s opinion”. Anything that is said on the report is either opinion, criticism, information or commentary. If making any type of investment or legal decision it would be wise to contact or consult a professional before making that decision.

Disclaimer:De inhoud van deze columns weerspiegelen niet per definitie de mening van {EDC Developer}.

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

Complexity and effectiveness of edit checks

ABSTRACT
Much effort goes into the specification, development, testing and verification of programmatic edit checks to ensure that the error rate in clinical trial data is sufficiently low as to have no statistically significant effect on the overall trial results. An analysis of several thousand clinical trials, containing over 1.1 billion data values and 1.1 million edit checks, shows that the majority of edit checks (60%) have no impact on data quality; none of these 678,000 edit checks have generated a single data query or discrepancy. What can be learnt from this analysis; can we reduce the overall number of edit checks without compromising data quality; can we identify the ‘high-performing’ edit checks and improve CRF design to avoid data entry errors; are there novel methods that might achieve similar standards of data quality with less effort?

Edit checks are necessary to ensure data quality reaches acceptably high levels.

Since programming edit checks takes time and resources, it’s important to ensure that the effort invested maximizes the benefit and re-usability of each edit check.

See attached document for full article information published by:

Optimizing Data Validation by Andrew Newbigging, Medidata Solutions Worldwide, London, United Kingdom

 

Comments? Join us at {EDC Developer}

Anayansi Gamboa, MPM, an EDC Developer Consultant and clinical programmer for the Pharmaceutical and Biotech industry with more than 13 years of experience.

Available for short-term contracts or ad-hoc requests. See my specialties section (Oracle, SQL Server, EDC Inform, EDC Rave, OpenClinica, SAS and other CDM tools)

As the 3 C’s of life states: Choices, Chances and Changes- you must make a choice to take a chance or your life will never change. I continually seek to implement means of improving processes to reduce cycle time and decrease work effort.

Subscribe to my blog’s RSS feed and email newsletter to get immediate updates on latest news, articles, and tips. I am available on LinkedIn. Connect with me there for technical discussions.

Fair Use Notice: This article/video contains some copyrighted material whose use has not been authorized by the copyright owners. We believe that this not-for-profit, educational, and/or criticism or commentary use on the Web constitutes a fair use of the copyrighted material (as provided for in section 107 of the US Copyright Law. If you wish to use this copyrighted material for purposes that go beyond fair use, you must obtain permission from the copyright owner. Fair Use notwithstanding we will immediately comply with any copyright owner who wants their material removed or modified, wants us to link to their website or wants us to add their photo.

Disclaimer: The EDC Developer blog is “one man’s opinion”. Anything that is said on the report is either opinion, criticism, information or commentary. If making any type of investment or legal decision it would be wise to contact or consult a professional before making that decision.

Disclaimer:De inhoud van deze columns weerspiegelen niet per definitie de mening van {EDC Developer}.

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

 

Data verification puzzles

 

Important part of the data management job is to verify received data. Checking for inconsistencies and unexpected patterns. Verifying that the data is complete, legible, logical and plausible.

However, how to perform data verification?

You could regard the data verification job as completing a couple of puzzles. Each puzzle is one subject participating in the clinical trial or clinical study at stake. As such, the puzzles resemble each other a great deal. But they are not exact copies. Each subject, each puzzle, is (slightly) different, unique.

Pleasant and thoughtful team action:

Do you have a puzzle somewhere in a cupboard? More than one from the same series? At least 2 puzzles with > 100 pieces each? Open the boxes, drop their content in one pile on the table and start completing the puzzles/subjects. The more pieces in place of a puzzle, the more evident which pieces to expect.

1. Get the parts received, divide them per subject/puzzle and start making all the puzzles. The clinical information up on each subject is coming in pieces, per completed visit data, per available adverse event information. In the beginning you’ll thus work with lots of incomplete puzzles.

2. Any holes in any puzzle/subject, any missing parts, you need to look for/query. Note that holes are allowed if your puzzle/story is as such! However, leave no unexpected holes. Meaning that if an assessment took place, you want to have the corresponding result(s) completed.

3. Any duplicate pieces, get rid of them. Please query.

4. Any pieces not fitting your puzzle/subject story, you need to check up on. Maybe they belong to another puzzle/subject. Or they are incomplete and can therefore not fit (yet). They could even be wrong delivered and not belong to the study at all.

5. Any pieces fitting but rotated 90 or 180 degrees, please turn/query. Get the puzzle showing a logical story.

6. Any pieces damaged, please try to fix the damaged parts. E.g. spilled coffee over a paper CRF. Illegible text parts. Or unclear texts that can be interpreted differently.

7. Any pieces added at the wrong place, query and bring to their right position. E.g. an error in an assessment date.

In trial/study language, the more data for a subject received and in the database, the easier to get the subject’s story complete. However, the more care needed to get the true story. The logical, plausible subject story. Attention to medication given for an adverse event but missing in the concomitant medication list. Or laboratory shifts to worse results but missing corresponding adverse events listed.

Completing the holes in a puzzle is easy, for data management the edit checks help you tremendously with that. Getting a logical, plausible story for each patient, reflecting the truth, is the real data management challenge. Which takes more than just structuring pieces. It asks you to look and understand the pictures up on the pieces received.

Good luck with your data management puzzles,

Source:

“This is an article of ProCDM. Clinical data management training. Receive tips and the free e-book ‘Five strategies to get reliable, quality clinical data’ by subscribing via http://www.procdm.nl/pages/knowledgebase.asp.”

Comments? Join us at {EDC Developer}

Anayansi Gamboa, MPM, an EDC Developer Consultant and clinical programmer for the Pharmaceutical and Biotech industry with more than 13 years of experience.

Available for short-term contracts or ad-hoc requests. See my specialties section (Oracle, SQL Server, EDC Inform, EDC Rave, OpenClinica, SAS and other CDM tools)

As the 3 C’s of life states: Choices, Chances and Changes- you must make a choice to take a chance or your life will never change. I continually seek to implement means of improving processes to reduce cycle time and decrease work effort.

Subscribe to my blog’s RSS feed and email newsletter to get immediate updates on latest news, articles, and tips. I am available on LinkedIn. Connect with me there for technical discussions.

Fair Use Notice: This article/video contains some copyrighted material whose use has not been authorized by the copyright owners. We believe that this not-for-profit, educational, and/or criticism or commentary use on the Web constitutes a fair use of the copyrighted material (as provided for in section 107 of the US Copyright Law. If you wish to use this copyrighted material for purposes that go beyond fair use, you must obtain permission from the copyright owner. Fair Use notwithstanding we will immediately comply with any copyright owner who wants their material removed or modified, wants us to link to their website or wants us to add their photo.

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

CDISC/CDASH Standards at your Fingertips

A standard database structure using CDISC (Clinical Data Interchange Standards Consortium) and CDASH (Clinical Data Acquisition Standards Harmonization) standards can facilitate the collection, exchange, reporting, and submission of clinical data to the FDA and EMEA. CDISC and CDASH standards provide reusability and scalability to EDC (electronic data capture) trials.

There are some defiance in implementing CDISC in EDC CDMS:

1. Key personnel in companies must be committed to implementing the CDISC/CDASH standards.

2. There is an initial cost for deployment of new technology: SDTM Data Translation Software, Data Storage and Hosting, Data Distribution and Reporting Software.

3. It can be difficult to understand and interpret complex SDTM Metadata concepts and the different implementation guides.

4. Deciding at what point in a study to apply the standards can be challenging: in the study design process, during data collection within the CDMS [CDASH via EDC tools], in SAS prior to report generation [ADaM], or after study completion prior to submission [SDTM].

5. Data management staff [CDM, clinical programmers], biostatisticians, and clinical monitors may find it difficult to converge on a new standard when designing standard libraries and processes.

6. Implementing new standards involves reorganizing the operations of (an organization) so as to improve efficiency [processes and SOPs].

7. Members of Data Management team must be retrained on the use of new software and CDISC/CDASH standards.

standards8. There are technical obstacles related to implementation in several EDC systems, including 8 character limitations [SAS] on numerous variables, determining when to use supplemental qualifiers versus creating new domains, and creating vertical data structure.

Comments? Join us at {EDC Developer}

Anayansi Gamboa, MPM, an EDC Developer Consultant and clinical programmer for the Pharmaceutical and Biotech industry with more than 13 years of experience.

Available for short-term contracts or ad-hoc requests. See my specialties section (Oracle, SQL Server, EDC Inform, EDC Rave, OpenClinica, SAS and other CDM tools)

As the 3 C’s of life states: Choices, Chances and Changes- you must make a choice to take a chance or your life will never change. I continually seek to implement means of improving processes to reduce cycle time and decrease work effort.

Subscribe to my blog’s RSS feed and email newsletter to get immediate updates on latest news, articles, and tips. I am available on LinkedIn. Connect with me there for technical discussions.

Fair Use Notice: This article/video contains some copyrighted material whose use has not been authorized by the copyright owners. We believe that this not-for-profit, educational, and/or criticism or commentary use on the Web constitutes a fair use of the copyrighted material (as provided for in section 107 of the US Copyright Law. If you wish to use this copyrighted material for purposes that go beyond fair use, you must obtain permission from the copyright owner. Fair Use notwithstanding we will immediately comply with any copyright owner who wants their material removed or modified, wants us to link to their website or wants us to add their photo.

Disclaimer: The EDC Developer blog is “one man’s opinion”. Anything that is said on the report is either opinion, criticism, information or commentary. If making any type of investment or legal decision it would be wise to contact or consult a professional before making that decision.

Disclaimer:De inhoud van deze columns weerspiegelen niet per definitie de mening van {EDC Developer}.

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

How to write query texts – 6 template sentences

How to write queries unambiguously expressing what is asked for? Using short, polite sentences? Objectively explaining the underlying inconsistency?

First of all my general guidelines.

My preference is to use no more capitals then needed. Capitals in the middle of a query text, e.g. for CRF fields or for tick box options, could distract from getting the actual question asked. E.g. compare the same query texts, with and without extra capitals. Please verify stop date. (Ensure that stop date is after or at start date and that stop date is not a future date.) Please verify Stop date. (Ensure that Stop date is after or at Start date AND that Stop date is not a future date.)

Referring to CRF fields as they are shown on the CRF. To easily find the involved field(s).

I prefer to leave any ‘the’ before a CRF field referral out of the query text. For more to-the-point query texts. E.g. compare the same query texts, with and without ‘the’ before data fields. Please verify stop date. (Ensure that stop date is after or at start date and that stop date is not a future date.) Please verify the stop date. (Ensure that the stop date is after or at the start date and that the stop date is not a future date.)

Consistency in phrasing a query text can help to quickly write query texts or pre-program query texts in a structured, familiar way. That’s the thought behind the following 6 template sentences for query texts. Which you can use to help you write or program your queries.

The six ‘template’ sentences for query texts:

Please provide…

For asking the study site people to provide required data from patient care recordings. Examples: Please provide date of visit. Please provide date of blood specimen collection. Please provide platelet count. Please provide % plasma cells bone marrow aspirate. Please provide calcium result.

Please complete… For asking the study site people to complete required data as required by the study CRF design. (Not necessarily required for patient care). Examples: Please complete centre number. Please complete subject number. Other frequency is specified, please complete frequency drop-down list accordingly.

Please verify…

For asking the study site people to check date and time fields fulfilling expected timelines. Or for asking the study site people to check field formats. Examples: Please verify start date. (Ensure that start date is before date of visit.) Please verify stop date. (Ensure that stop date is after or at start date and that stop date is not a future date.) Please verify date of blood specimen collection. (Ensure that date of blood specimen collection is before or equal to date of visit and after date of previous visit.) Please verify date last pregnancy test performed. Please verify date of informed consent. (Ensure date of informed consent is equal to date of screening or prior to date of screening.) Please verify date as DDMMYYY.

…., please correct.

For asking the study site people to correct a data recording inconsistent with another data recording. Example: Visit number should be greater than 2, please correct.

…., please tick…

For asking the study site people to complete required tick boxes. Examples: Gender, please tick male or female. Pregnancy test result, please tick negative or positive. Any new adverse events or changes in adverse events since the previous visit, please tick yes or no. Laboratory assessment performed since the previous visit, please tick yes or no. LDH, please tick normal, abnormal or not done.

Please specify…

For asking the study site people to specify the previous data recording. Examples: Please specify other dose. Please specify other frequency. Please specify other method used. Please specify other indication for treatment.

Finally, for query texts popping up during CRF data recording, it could be helpful to put location information in it. Like: Page 12: Please verify start date. (Ensure that start date is after or at start date on page 11.)

Good luck finding your way to structure query texts…

Source:

This article is written by Maritza Witteveen of ProCDM. For clinical data management. You can subscribe to her blog posts at www.procdm.nl.”

Comments? Join us at {EDC Developer}

Anayansi Gamboa, MPM, an EDC Developer Consultant and clinical programmer for the Pharmaceutical and Biotech industry with more than 13 years of experience.

Available for short-term contracts or ad-hoc requests. See my specialties section (Oracle, SQL Server, EDC Inform, EDC Rave, OpenClinica, SAS and other CDM tools)

As the 3 C’s of life states: Choices, Chances and Changes- you must make a choice to take a chance or your life will never change. I continually seek to implement means of improving processes to reduce cycle time and decrease work effort.

Subscribe to my blog’s RSS feed and email newsletter to get immediate updates on latest news, articles, and tips. I am available on LinkedIn. Connect with me there for technical discussions.

Fair Use Notice: This article/video contains some copyrighted material whose use has not been authorized by the copyright owners. We believe that this not-for-profit, educational, and/or criticism or commentary use on the Web constitutes a fair use of the copyrighted material (as provided for in section 107 of the US Copyright Law. If you wish to use this copyrighted material for purposes that go beyond fair use, you must obtain permission from the copyright owner. Fair Use notwithstanding we will immediately comply with any copyright owner who wants their material removed or modified, wants us to link to their website or wants us to add their photo.

Disclaimer: The EDC Developer blog is “one man’s opinion”. Anything that is said on the report is either opinion, criticism, information or commentary. If making any type of investment or legal decision it would be wise to contact or consult a professional before making that decision.

Disclaimer:De inhoud van deze columns weerspiegelen niet per definitie de mening van {EDC Developer}.

Choosing a Successful Clinical Trial Management System [CTMS]

Steps towards a successful CTMS:

Exploring the benefits of clinical trial management system (CTMS)

The benefits of mapping and developing an enterprise wide solution include6:

  • Centralizing decentralized departments
  • Optimizing institutional review board (IRB) functionality
  • Realizing real-time data available to both investigators and leadership
  • Decreasing bottlenecks in knowledge transfer between various entities involved in research
  • Reducing human errors in reporting that often cause compliance issues
  • Tracking milestones for grants, awards, fellowships, etc.
  • Streamlining the financial structure — billing and invoicing

operational, infrastructure, compliance, and governance issues that can be improved by implementing a CTMS:

  • Staffing: with a better understanding of resources, management will be capable of reallocating staffing assignments to offset excess or inadequate roles.
  • Communication: improved communication will improve patient satisfaction and monitoring of clinical trials.
  • Human error: CTMSs have integrated checking components to limit errors in reporting.
  • Operational flow: improved knowledge flow in various divisions (finance, marketing, administration, training, and recruitment) will help to achieve real-time results and data.
  • Managing clinical data: more accurate and efficient reporting tools will be useful internally and externally for current and future project assessments.

 

Choosing a CTMS that serves your institutional needs

ctmsEven though there is no perfect system, consider the reviewing of some common elements among most of the best systems:

  • Financial reporting tools (coverage analysis, residual and overage reporting)
  • Clinical trial management tools (including applicable clinical trial milestones and reporting dashboards)
  • Searchable clinical trial database
  • Analytical risk-based decisions
  • Reporting dashboards
  • Data warehousing module
  • Recruitment support module
  • Electronic case report form (eCRF)
  • Integrates easily with electronic medical records (EMRs), IRB system(s), etc.

Cost factors and implementation overview

In our experience with the implementation of CTMSs, the following are key aspects of the process:

  • Building a steering committee: the most important aspect of implementing a CTMS is having a committee that is capable of making well-informed decisions for the institution.
  • Forecasting future issues: know the current and future issues of the institution that hope to be resolved with the CTMS.
  • Adapting to change: understand that implementing a CTMS will come with new responsibilities. The institution should be prepared to have individuals fill these new roles. Without this preparation, the CTMS is doomed from the beginning. New hires might not be necessary, but rather a shift in responsibilities. Create a culture of transparency to eliminate conflict and inconsistencies in the future.
  • Training and preparation: design an ongoing tailored training program to meet the short- and long-term needs of staff.  Implement training and train staff on the new technology.

A successful CTMS connects all aspects of clinical trial management and allow administration to focus on making strategic decisions based on analytics and accurate real-time data.

References: Original article can be seen at Applied Clinical Trials with

Comments? Join us at {EDC Developer}

Anayansi Gamboa, MPM, an EDC Developer Consultant and clinical programmer for the Pharmaceutical and Biotech industry with more than 13 years of experience.

Available for short-term contracts or ad-hoc requests. See my specialties section (Oracle, SQL Server, EDC Inform, EDC Rave, OpenClinica, SAS and other CDM tools)

As the 3 C’s of life states: Choices, Chances and Changes- you must make a choice to take a chance or your life will never change. I continually seek to implement means of improving processes to reduce cycle time and decrease work effort.

Subscribe to my blog’s RSS feed and email newsletter to get immediate updates on latest news, articles, and tips. I am available on LinkedIn. Connect with me there for technical discussions.

Fair Use Notice: This article/video contains some copyrighted material whose use has not been authorized by the copyright owners. We believe that this not-for-profit, educational, and/or criticism or commentary use on the Web constitutes a fair use of the copyrighted material (as provided for in section 107 of the US Copyright Law. If you wish to use this copyrighted material for purposes that go beyond fair use, you must obtain permission from the copyright owner. Fair Use notwithstanding we will immediately comply with any copyright owner who wants their material removed or modified, wants us to link to their website or wants us to add their photo.

Disclaimer: The EDC Developer blog is “one man’s opinion”. Anything that is said on the report is either opinion, criticism, information or commentary. If making any type of investment or legal decision it would be wise to contact or consult a professional before making that decision.

Disclaimer:De inhoud van deze columns weerspiegelen niet per definitie de mening van {EDC Developer}.