Rationale Despite their inherently pervasive limitations, data from observational studies are increasingly relied upon by health care decision makers to fill critical information gaps created by lack of evidence from randomized controlled trials.
Aim and objective The aim and objective of this article was to revisit the major issues associated with observational studies from secondary data sources.
Method The method of this article was canvass of the literature.
Results Sources of bias are highlighted and steps intended to minimize bias are summarized.
Conclusion Efforts should be made to improve causal inference of treatment effects from observational studies found in secondary data sources. Extra care and caution should be exercised in the interpretation and reporting of results from these studies.