Quality Assurance in Epidemiologic Studies

Manya DeLeon MillerEPID 712

22 March 2000

Topics to be Discussed

• Brief history of quality assurance (QA)

• Applied aspects of QA for use in clinical trials and observational studies

• Some “how to” steps to establish/maintain QA systems

History and Background

• Quality Assurance (QA) is not a new idea: cunieform instructions for quality in work may be found from 2000 b.c.

• Japan and industry initiated “modern” QA efforts/philosophy

History and Background

• Biggest efforts from pharmaceutical industry—clinical trials, FDA changes to require randomized controlled trials in 1960’s

• Alphabet soup: QA, QC, TQI, QM, TQM, etc., etc… What does it all mean?

An Applied Approach to QA

• Data as a skeleton: A person and his realityinterviewer/MD/nurse/etc. case report forms (CRFs)data entrynumbers

An Applied Approach to QA

• The person who used to look like this:

• now looks like this: 1019988563222009

An Applied Approach to QA

• QA necessary to ensure that data are abstracted– HONESTLY– ACCURATELY

So that the subject is adequately reflected by the data.(fraud vs. error…)

An Applied Approach to QA

• REMEMBER:

the data should conform the person; the person doesn’t need to conform to the data codes, etc.!

An Applied Approach to QA

• Always consider the conclusions that will come from your study, and how inaccurate data will affect your conclusions.

An Applied Approach to QA

• Standardization is CRUCIAL• All techniques designed to ensure

that data are collected in a fashion that is:– Standardized– Systematic– Reliable– Valid

An Applied Approach to QA

• Consider system and QA issues BEFORE setting up study… Not during or after!

Steps in QA

• Study set up/study design/protocol• Regulatory• Forms/source documents• QA• QC• Data entry• Monitors/audits

Steps in QA

• Study set up/study design/protocol– Starting with a solid protocol is essential.– Should articulate IN DETAIL all aspects of

the study so that techniques (lab, data abstraction, evaluations, etc.) are the same irrespective of who/where study is done

– NO AMBIGUITY!– See real protocols, book, appendix D, web

Steps in QA

• Regulatory– Regulatory aspects should be well

maintained; part of assuring not only quality, but safety of subjects (and staff)

– IRB– Simple files fine, just be sure that they

are consistent and adherent with regulatory guidelines of institution, city, state, federal

Steps in QA

• Forms/source documents– Forms (often called Case Report Forms or

CRFs) should be well considered and piloted before implementation

– Want to standardize how questions are asked and be sure that answers address the study questions of interest

– Often, bad formsbad study, even if all else is great

– Training is essential!

Steps in QA

• QA– Define (second set of eyes…)– Check all data before submission for

• Logical consistency• Adherence to protocol/study• Correct representation of subject experience

– How to? • Specific training• Red pen sticky note or more elaborate

systems

Steps in QA

• QA– Team spirit essential with QA

Steps in QA

• QC– If possible, great to have a third set of

eyes for QC… obvious logical issues. May work together with data entry or be same person

Steps in QA

• Data entry– Again, training is key– Validity checks in data entry screens– Real time logical checks

(later=harder)– Double data entry (pros/cons)– Random sample double data entry

Steps in QA

• Monitors/audits– In clinical trials, very common – Should also do for cohort/case-

control/cross-sectional studies

Examples

• Pediatric AIDS Clinical Trials Unit

• Partner Notification Study

• Ever heard the saying,– GARBAGE IN, GARBAGE OUT??

• Think about the effort you are giving your study, the conclusions you want to be able to make. Data need to be valid; QA techniques allow valid data to emerge from your study

• Questions??