QUALITY ASSESSMENT OF OBSERVATIONAL STUDIES FOR SYSTEMATIC REVIEWS

Author(s)

Kiss N*;Tongbram V, Fortier KJ Oxford Outcomes, Morristown, NJ, USA

Background:  Observational studies are frequently included in systematic reviews, especially in those disease areas where RCTs are limited.  While there are very specific tools for and guidance on assessing the quality of RCTs, the assessment of observational studies is less standardized.  Objective:  To understand and assess the different tools used to review the quality of observational studies and to make recommendations based on our evaluation.  Methods:  First, a systematic review of literature from 2005-present was conducted in Embase and Medline to determine the frequency of use of quality assessment for observational studies and the type of tools used to conduct the assessment.  Second, we reviewed documentation from NHS guidance on quality assessment of non-randomized studies.  Finally, we reviewed two years of approved HTA submissions to see what methods of assessment have been used for submissions.  Results:  A total of 1429 articles were screened.  Compared to a similar study on older literature, our review found an increase in the use of quality assessment for observational studies.  However, we found that many studies continue to devise their own tool or adapt existing tools rather than use a tool in its entirety.  Downs and Black, MOOSE, and STROBE were the most referenced tools, although STROBE was not originally intended for such use. Guidelines centered on "non-randomized" studies were mixed and were not always found to be applicable to observational studies, but instead mostly to single-armed clinical trials. Conclusions:  There is still a need for guidance and standardization for observational studies assessment for use in systematic literature reviews.  Although quality assessment of observational studies is still not standardized, there are a few methods becoming more frequent in the literature but are difficult to compare across systematic literature reviews because they have often been adapted by each author.

Conference/Value in Health Info

2013-11, ISPOR Europe 2013, The Convention Centre Dublin

Value in Health, Vol. 16, No. 7 (November 2013)

Code

PRM220

Topic

Methodological & Statistical Research

Topic Subcategory

Confounding, Selection Bias Correction, Causal Inference

Disease

Multiple Diseases

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