OBJECTIVES: Increasingly, value demonstration evidence requirements cannot be addressed with a single data source and/or methodology.  The objective of this research is to present, using case studies to illustrate, a strategic and step-wise approach for the development of optimal study designs to address research questions which warrant multiple data sources including primary or secondary sources of real-world data.   METHODS: Steps followed in the conceptualization of designs that integrate multiple data sources include: the identification and prioritization of research questions, delineation of evidence gaps and potential data sources, assessment of data availability by source and feasibility of data integration, study synopsis development, data protection and legal reviews, and study protocol  development. RESULTS: In the first case example, the purpose of the study was to understand reasons why patients discontinue therapy for a rare disease.  Due to the orphan drug status, multiple data sources were needed to identify and recruit subjects to participate in the study.  A second case study combined the use of a patient support program database to identify potential subjects, drug dispensing data from a specialty pharmacy to assess medication adherence, and a longitudinal patient survey assessing disease activity and patient satisfaction.  Finally, two studies were designed (1 observational, 1 interventional) which utilize pharmacy claims data to identify potential subjects and evaluate medication adherence during the study period.  This data is linked with longitudinal patient surveys evaluating topics including treatment experience, reasons for non-adherence, and experience of adverse events. CONCLUSIONS: These case studies demonstrate a novel approach to study design from within a single research network, whereby data from multiple sources may be integrated in order implement prospective observational research studies that answer complex research questions.