OBJECTIVES: Evidence has recently emerged regarding the presence of investigator learning curves in the context of clinical trials (i.e., the association between clinical protocol departures and patient enrollment sequence). We reviewed the literature to identify factors contributing to clinical trial learning curves and potential impacts of learning curves on outcomes accuracy, patient safety and overall trial success. METHODS: The PubMed database was searched for studies describing clinical trial learning curve effects and potential solutions to these effects, using search term combinations including “clinical trial”, “clinical protocol”, “learning curve”, and “enrollment sequence”. RESULTS: Learning curve effects were identified in trials including those for treatment of sepsis (PROWESS and ADDRESS) and high-risk cardiac disease (VALIANT). Outcomes of these trials potentially resulting from learning curves included ambiguous treatment benefit, increased adverse events and mortality, and overall trial failure. Potential contributing factors include those related to study site (e.g., large multicenter trials; sites with poor enrollment or previous trial experience; inexperienced staff and high staff turnover), study protocols (e.g., imprecise or complex protocols), and disease severity. Preventing such learning curve effects would likely have required extensive trial site and staff screening and training, as well as improved trial protocol design prior to first patient enrollment. Clinical trial simulation, a methodology identified in several reports, could potentially address clinical trial learning curves by improving protocol design and staff competence. This approach, which focuses on human factors involved in conducting clinical protocols, offers the potential to improve the accuracy of measured trial outcomes and decrease the likelihood of premature trial termination. CONCLUSIONS: Clinical trial learning curves have significant implications for outcomes research accuracy, patient safety, and overall trial success. Clinical trial simulation may provide a broadly applicable methodology for addressing several factors associated with clinical trial learning curve effects and for improving the accuracy of clinical trial outcomes.