ENCePP Guide on Methodological Standards in Pharmacoepidemiology
11.4. Quality management in observational studies
Quality management principles
applicable to observational studies with primary data collection or secondary
use of data are described in the Commission Implementing Regulation (EU) No 520/2012, GVP Module I, FDA’s Best Practices for Conducting and Reporting
Pharmacoepidemiologic Safety Studies Using Electronic Health Care Data Sets,
the ISPE GPP or the Guidelines and recommendations for ensuring Good Epidemiological
Practice (GEP): a guideline developed by the German Society for Epidemiology (Eur J Epidemiol. 2019;34(3):301-17).
Data for Regulatory Decision Making: Challenges and Possible Solutions for
Europe (Clin Pharmacol Ther. 2019; 106(1):36-9) describes four criteria for
acceptability of RWE for regulatory purposes: Derived from data source of
demonstrated good quality, Valid (internal and external), Consistent and
Adequate. Challenges for this acceptability and possible solutions in the EU
context are presented.
The following articles are
practical examples of quality aspects implementation in different settings:
Assurance and Quality Control in Longitudinal Studies (Epidemiol Rev. 1998,
20(1); 71-80) provides a comprehensive overview of components of QA and QC in
multi-centre cohort studies with primary data collection that should be an
integral part of their design. Training,
quality assurance, and assessment of medical record abstraction in a multisite
study (Am J Epidemiol. 2003;157:546-51) describes a practical approach to
assurance of good quality control in a large multi-site study.
- Quality assurance in non-interventional studies (Ger Med Sci.
2009;7:Doc 29: 1-14) proposes measures of quality assurance that can be applied
at different stages of non-interventional studies without compromising the
character of non-intervention.
- Chapter 11 ‘Data Collection and Quality Assurance’ of the AHRQ Registries for Evaluating Patient Outcomes: A User's Guide, 3rd
Edition, reviews key areas of data collection, cleaning, storing, and
quality assurance for registries, with practical examples.
- Interviewer variability – quality aspects in a case–control
study (Eur J Epidemiol. 2006;21(4);267-77) describes the procedures used to
reduce interviewer variability, including procedures of quality assurance (i.e.
education and training of interviewers and data validity checks) and quality
control (i.e. a classification test, annual test interviews, expert case
validation and database validation).
- Establishment of the nationwide Norwegian Prescription Database
(NorPD) – new opportunities for research in pharmacoepidemiology in Norway (Norsk epidemiologi. 2008;18(2):129-36) describes the quality checks applied to
- Validation and validity of diagnoses in the General Practice
Research Database (GPRD): a systematic review (Br J Clin Pharmacol.
2010;69:4-14) assesses the quality of the methods used to validate diagnoses in