OBJECTIVES: Analysis of large datasets such as claims and healthcare utilization databases has become a routine way that drug, device and diagnostic manufacturers understand current treatment pathways and project market potential for development products.  The time, resources, and costs associated with these data analyses can be a barrier for small- to mid-size companies operating under the pressure of lean development processes.  We sought to analyze the current published literature on claims analyses in four therapeutic areas (cardiovascular, ophthalmology, oncology, and women’s health) to better understand the size of companies engaging in this type of research.  METHODS: A literature review of published articles from January 1, 2000 – December 31, 2013 was conducted to better understand the analyses of large datasets being conducted by company size.  The data were then abstracted to obtain the following data:  therapeutic area, funding support for data analysis, company size, large dataset utilized, approximate cost of obtaining data, approximate cost of analyzing data, approximate US patient population for drug/device/diagnostic under development. RESULTS: Analyses of large datasets were just as likely to be conducted by government and academic institutions as private sector organizations (research firms and manufacturers).  Of the 35 articles that met inclusion criteria in cardiovascular disease, 19 conducted by private sector organizations.  For the 19 analyses conducted by private sector organizations, 3 were conducted by manufacturers, of which two were large pharmaceutical companies and 1 was a nationwide pharmacy chain. CONCLUSIONS: None of the claims data conducted by manufacturers were small- to mid-size companies.  It is unclear whether this is due to the cost of data and analysis or the desire to have a seemingly unbiased third-party author.  Further research is needed to determine why small- to mid-size drug, device or diagnostic manufacturers are not engaging in this type of research.