Aim: Evaluating the public health impact of regulatory interventions is important but there is currently no common methodological approach to guide this evaluation. This systematic review provides a descriptive overview of the analytical methods for impact research.
Methods: We searched MEDLINE and EMBASE for articles with an empirical analysis evaluating the impact of European Union or non-European Union regulatory actions to safeguard public health published until March 2017. References from systematic reviews and articles from other known sources were added. Regulatory interventions, data sources, outcomes of interest, methodology and key findings were extracted.
Results: From 1,246 screened articles, 229 were eligible for full-text review and 153 articles in English language were included in the descriptive analysis. Over a third of articles studied analgesics and antidepressants. Interventions most frequently evaluated are regulatory safety communications (28.8%), black box warnings (23.5%) and direct healthcare professional communications (10.5%). 55% of studies measured changes in drug utilisation patterns, 27% evaluated health outcomes and 18% targeted knowledge, behaviour, or changes in clinical practice. Unintended consequences like switching therapies or spill-over effects were rarely evaluated. Two thirds used before-after time series and 15.7% before-after cross-sectional study designs. Various analytical approaches were applied including interrupted time series regression (31.4%), simple descriptive analysis (28.8%) and descriptive analysis with significance tests (23.5%).
Conclusion: Whilst impact evaluation of pharmacovigilance and product-specific regulatory interventions is increasing, the marked heterogeneity in study conduct and reporting highlights the need for scientific guidance to ensure robust methodologies are applied and systematic dissemination of results occurs.
- Journal article
- Regulatory interventions
- Impact evaluation
- Real-world effectiveness
- Health outcomes
- Methodological gaps
- Before-after study design
- Interrupted time series