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Strategies for Dealing with the CRF &Preventing Data Discrepancies

Slideshare – 22 October 2012

Mary K.D. D’Rozario

MSCR, CCRP, RAC, CCRA

President / Clinical Research Consultant

Clinical Research Performance, Inc.

mary.drozario@crplink.com

@marydrozario

marydrozario

Marykddrozario

We work for sites.

See inside…

ONE tip to

really save

time!

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Strategies for dealing with your data without tears.

• Outcomes of this presentation:

Understand how different personalities experience data differently.

Obtain strategies for working with data, especially if you are not a “data person.”

Learn a standard patterns for responding to queries and preventing queries.

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What is the regulation? ICH 4.9.1-3

4.9.1 The investigator should ensure the accuracy, completeness, legibility, and timeliness of the data reported to the sponsor in the CRFs and in all required reports.4.9.2 Data reported on the CRF, that are derived from source documents, should be consistent with the source documents or the discrepancies should be explained.

Not necessarily exactly letter-for-letter the same as…

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What is the regulation? ICH 4.9.1-3

4.9.3 Any change or correction to a CRF should be dated, initialed, and explained (if necessary) and should not obscure the original entry… Sponsors should provide guidance to investigators and/or the investigators’ designated representatives on making such corrections. Sponsors should have written procedures to assure that changes or corrections in CRFs made by sponsor’s designated representatives are documented, are necessary, and are endorsed by the investigator. The investigator should retain records of the changes and corrections.

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Lots of different types of people touch data management!

Data: Scientists

Writers Project Management

Data Management

Clinical Monitoring

Investigators/Designees

Point choices, formatCollection

Verification

Validation

Quality

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They come from all over the place!

• Drug development sponsor Partner sponsors Subcontractors Consultants

• Clinical Research Organization Secondary CRO Subcontractors Consultants

• Laboratories• Data management vendors• Sites

Associated professionals (hospitals, clinics, labs) Research designees Non-research professionals

• Other Other medical care for subject

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Their personalities are wildly divergent!

• Myers-Briggs TypesE/I S/N T/F J/P

Attitude Function Function Lifestyle

Extroverted Sensing Thinking Judging

Introverted iNtuition Feeling Perception

Typical successful DM professional.

Typical successful study coordinator.

The typical successful DM professional and the typical successful study coordinator have totally different performance strengths and means of communication.

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What/how do you see this picture?

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What/how do you see this picture?

• One systematic way to review the fig newton data is to review each upper edge for jelly.

• Another systematic review is to review each side edge for cake.

• A data manager will review both ways.• AND:

A non-data person can know that there is a problem without doing a systematic review. You just looked at it and you KNEW. So don’t let anyone tell you that your skills in data management don’t matter. You have a GREAT skill!

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How about this one?

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How about this one?

• A systematic review of bread on the side would have missed the problem. (Did you see the fig newton that has bread on all four

sides?)

• Is this a problem or is it a fact?

• How do you record missing data?

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How would you explain this?

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How would you explain this?

• A systematic review would catch the missing bread and the missing jelly, but could miss the RABBIT in the fig newtons.

• A systematic review cannot tell you what should be there.

• How would you record this on this CRF:

Data Label Yes/No Field

Jelly on top? Yes No

Bread on the side? Yes No

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Data Recorded Must Correlate…

• …with the facts.

• …with the data instructions.

• …with all other data.

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What correlation looks like:

Adverse Event Name Start Date

Sprained Ankle Left 12 AUG 2011

Con Med Start Date Dose Measurement

Indication

Tylenol 3 12 AUG 2011

1 Tablet Sprained Ankle Left

CRF Page Field InstructionAdverse Event Name For bilateral body part, state “left” or

“right” as last word.Concomitant Medication

Dose For combination medication, provide dose in terms of packaged units.

*These data guidelines could have been, and often are, different.

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What about data correlation for withdrawn subjects?

• What is a withdrawn subject? Ends participation in the intervention. Ends participation in the study.

• Special cases: Death Lost to follow up

• Did you have consent to seek other data sources?

• FDA Guidance: Data Retention When Subjects Withdraw from FDA-

Regulated Clinical Trials

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Good Descriptions: Source document templates are the solution to almost all data problems.

• Have a work instruction.• As soon as possible review against:

Protocol Informed Consent Form Case Report Forms

• Re-review upon updates.• Create a cycle of continuously

improved templates.

Creative Commons Lic. DPS-User

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Ask yourself:

• Does it look like something a computer would say?

• Is it codeable?

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Queries: Solve the problem, not the query.

• You don’t know what the problem is until after you have solved it. The delegated site personnel resolves the query.

• Not the monitor, not DM• (Mostly- permitted in ICH and can be done with proper

documentation) Queries must be solved based on:

• Facts about the patient• Data entry guidelines

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Not the query!

• Queries must not be resolved based on: The Query! A query flags a problem, it does not tell you what

the solution is. (Do not use “Data updated per query.”) A query that directs you to an answer is a potential inspection

finding

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Therefore, the single best tip I can give you to save you aggrivation and time answering queries is…

• SOLVE THE PROBLEM THEN ANSWER THE QUERY. Just do it. Bonus: In most computer system, automated queries

which are resolved by the data update disappear… you NEVER have to answer them!

This one tip

will save you

time and

aggrivation!

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Don’t take it personally. Don’t make it personal.

• The data got the query, not you.

• Names of staff are not appropriate in CRF data. (Usually)

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Don’t beat your head against the wall.

• Data will get queries that are the same, but from different review perspectives just verification wrong based on information invisible to the site based on internal disagreements invisible to the site

• Resolve it once, then phone-a-friend

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