Systematic reviews of quasi-experimental studies: challenges and considerations

BACKGROUND: In contrast to other observational study designs, quasi-experimental approaches (eg, difference-in-differences, interrupted time series, regression discontinuity, instrumental variable, synthetic control) account for some sources of unmeasured confounding and can estimate causal effects under weaker assumptions. Studies which apply quasi-experimental approaches have increased in popularity in recent decades, therefore investigators conducting systematic reviews of observational studies, particularly in biomedical, public health, or epidemiologic content areas, must be prepared to encounter and appropriately assess these approaches. OBJECTIVE: Our objective is to describe key methodological challenges and considerations for systematic reviews including quasi-experimental studies, with attention to current recommendations and approaches which have been applied in previous reviews. CONCLUSION: Recommendations for authors of systematic reviews: We recommend that individuals conducting systematic reviews including quasi-experimental studies: (1) search a broad range of bibliographic databases and gray literature, including preprint repositories; (2) do not use search strategies which require specific terms for study design for identification, given inconsistent nomenclature and poor database indexing for quasi-experimental studies; (3) ensure that their review team includes several individuals with expertise in quasi-experimental designs for screening and risk of bias assessment in duplicate; (4) use an approach to risk of bias assessment which is sufficiently granular to identify studies most likely to report unbiased estimates of causal effects (eg, modified Risk Of Bias In Nonrandomized Studies - of Interventions); and (5) consider the implications of varied estimands when interpreting estimates from different quasi-experimental designs. Researchers may also consider restricting systematic review inclusion to quasi-experimental studies for feasibility when addressing research questions with large bodies of literature. However, a more inclusive approach is preferred, as well-designed studies using a variety of methodological approaches may be more credible than a quasi-experiment which violates causal assumptions. Recommendations for the research community: Many of the challenges faced in conducting systematic reviews of quasi-experimental studies would be ameliorated by improved consistency in nomenclature, as well as greater transparency from authors in describing their research designs. The broader community (eg, research networks, journals) should consider the creation and implementation of reporting standards and protocol registration for quasi-experimental studies to improve study identification in systematic reviews.

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