Literature Search for Scientific Processes in Medical Devices: Challenges, Errors, and Mitigation Strategies

Literature search is a commonly used strategy or a method of collecting evidence on a given research question, specifically for a Clinical Evaluation Report. A precise literature search not only provides accurate evidence but also saves time and efforts during collation of such data. However, unless implemented correctly, literature search can be misleading, timeconsuming, or useless. Focusing the literature search on a precise topic and obtaining relevant evidence in a stipulated time requires high skill levels. Despite several guidance documents and papers, the process of literature search has various types of errors. These are errors of inclusion, exclusion, inclusive exclusion, exclusive inclusion, and limited relevance (exclusive exclusions). In order to obtain optimal outcomes in a literature search, the analysis of these errors is important. These errors pertain to the volume of evidence, relevance of the data, tone of evidence, and its value to the research topic. Analyzing these challenges and devising an accurate strategy to overcome these errors would certainly improve literature search outcomes. Combinations and permutations of these challenges (volume and relevance) present various practical challenges, namely, too high data; too low data; high volume, low relevance data; low volume, low relevance data; high value, high relevance data but repetitive outcomes (monotonous); and high value, high relevance data, but missing trends and threads. In this article, we discuss the abovementioned errors and challenges and mitigation strategies along with literature search automation.