Virtual Tumor Cases

Virtual Tumor Cases^TM are web-based presentations of case-based scenarios that mimic tumor conferences. This research method helps clients identify market usage, behavioral influencers, and segmentation/trending. Virtual Tumor Cases also offer enhanced efficiency of sensitivity analyses and prescribing prioritization. Each case is approximately 45 to 60 minutes in length during which time members of the NOCR network answer a series of questions related to how they would treat the patient. Clients can also integrate economic and reimbursement assessments pertinent to the case.

Leading indicators
Virtual Tumor Cases provide unique insight into how physicians intend to treat based on perceptions, awareness, current utilization, and estimated market changes. Ultimately, the data can serve as a predictor of future product performance.

Disease state and general knowledge
Each Virtual Tumor Case series provides detailed demographic and landscape data critical for understanding market segments, tendencies, and projections and is customized to meet the scale and scope of individual client research objectives. Xcenda also has the ability to provide detailed cross-tabulations that would be cost-prohibitive in other research formats.

While all Virtual Tumor Case series are customized to meet each client’s research goals,     the following elements are consistent for all engagements:

• A medical director or other disease area expert collaborates with each client to identify current issues and outline research objectives
  
  
• Strategic consulting, content case development and execution, data collection, and interpretation services
  
  
• Each launch is customized and geographically focused to ensure balanced data is gathered from each physician sample
  
  
• A fair market value (FMV) honorarium is paid to all qualified respondents
  
  
• Xcenda procures up to the desired amount of respondents (up to 500 in a single Virtual Tumor Case launch), creating a robust sample size of US hematologists/oncologists

Respondents are screened for eligibility based on specified criteria:

• Volume of patients treated in the disease state of interest
• Geographic diversity
• Experience/years in practice
• Academic vs community practice
• Additonal demographic information is captured and used to analyze responses in aggregate