Objective: To estimate the degree of scatter of reports of randomised trials and systematic reviews, and how the scatter differs among medical specialties and subspecialties. Design: Cross sectional analysis. Data source: PubMed for all disease relevant randomised trials and systematic reviews published in 2009. Study selection: Randomised trials and systematic reviews of the nine diseases or disorders with the highest burden of disease, and the broader category of disease to which each belonged. Results: The scatter across journals varied considerably among specialties and subspecialties: otolaryngology had the least scatter (363 trials across 167 journals) and neurology the most (2770 trials across 896 journals). In only three subspecialties (lung cancer, chronic obstructive pulmonary disease, hearing loss) were 10 or fewer journals needed to locate 50% of trials. The scatter was less for systematic reviews: hearing loss had the least scatter (10 reviews across nine journals) and cancer the most (670 reviews across 279 journals). For some specialties and subspecialties the papers were concentrated in specialty journals; whereas for others, few of the top 10 journals were a specialty journal for that area. Generally, little overlap occurred between the top 10 journals publishing trials and those publishing systematic reviews. The number of journals required to find all trials or reviews was highly correlated (r=0.97) with the number of papers for each specialty/subspecialty. Conclusions: Publication rates of speciality relevant trials vary widely, from one to seven trials per day, and are scattered across hundreds of general and specialty journals. Although systematic reviews reduce the extent of scatter, they are still widely scattered and mostly in different journals to those of randomised trials. Personal subscriptions to journals, which are insufficient for keeping up to date with knowledge, need to be supplemented by other methods such as journal scanning services or systems that cover sufficient journals and filter articles for quality and relevance. Few current systems seem adequate.