Longitudinal Data: What is it? How is it Used?

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• Definition
• Key Learning Objectives
• Who Should Attend
• Content
• Case Studies
• Leavebehind
• Contact for More Information

Definition

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• Patient longitudinal data is information that tracks disease progression, time intervals, and all facets of patient details and outcomes that occur at every progression point.

Key Learning Objectives

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• Understand the scope and depth of information that longitudinal data can provide
• Create awareness of the types of marketing and market research questions that longitudinal data can help answer
• Know how longitudinal data should and should not be used
• Understand applications for use
• Review the feasibility and challenges of generating longitudinal data via a custom study

Who Should Attend

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• Market Research
• Marketing
• Forecasting
• Pricing
• Outcomes Research

Content

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• Discussion of longitudinal data and the types of questions they can help answer
  1. Breadth and depth of longitudinal data
  1. Extent of patient demographics captured, treatment details and timeframes, and cost of treating disease in terms of dollars, time, and resource usage
  2. Today's tools: What is available, what they cover, and limitations of each
     1. Clinical trial data
     2. Medical claims databases (eg, IMS' Lifelink and Verispan's Patient-Centric Data Warehouse)
     3. Drug audits (eg, IMS and Verispan)
     4. Disease-specific databases based on Patients' Medical Records (eg, Intrinsiq's Cancer Patient Monitor and Market Certitude's HIV PatientMonitor)
  3. How longitudinal data are used by different groups and departments and the types of business questions they can help answer
     1. Market research and marketing (determine disease treatment patterns)
     2. Pricing groups (quantify the value of a new therapy and/or combination regimen)
     3. Outcomes research (demonstration of product value via better outcomes and/or reduced resource usage)
     4. Forecasting (quantify true prescribing potential)
• Using longitudinal data in marketing research
  1. Breadth and depth of longitudinal data
  2. Defining product potential by quantifying the actual number of prescribing opportunities in a given market
  3. Market segmentation using customized definitions
  4. Estimate duration of treatment and persistency
  5. Explore detailed changes in a given year by new and continuing patients
• Generating longitudinal data from custom studies
  1. What to know before you go (ie, what to build into the study design)
     1. Diagnosis information (symptoms experienced, tests administered, hospital time)-what led the doctor to make the diagnosis?
     2. Patient characteristics and vital stats-did patient meet criteria for treatment choice?
     3. Reasons for treatment choice
     4. Causative factors that prompt adjustments to therapy
     5. Treatment outcome details including adverse effects experienced and need for supportive care therapy
  2. Key information that should be captured
     1. Progression over time
     2. Unique patients and time intervals
     3. Detailed patient demographics
     4. Rich clinical detail
  3. Hurdles and challenges
     1. Feasibility of capturing and reporting rich clinical detail, in light of physician workloads and time constraints
     2. Ability to recruit and maintain a loyal physician panel over the long term
     3. Cost of the above
• Dos and don'ts when using longitudinal data

Case Studies

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• Relevant pharmaceutical examples will be used to illustrate the concepts

Leavebehind

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• Each participant will receive a 2-sided laminated card with key learnings from the course

For More Information, Contact:

Leslie Goldberg, Executive Vice President

666 Godwin Avenue, Suite 320
Midland Park, NJ 07432
p: 201-670-7722 ext. 205
f: 201-670-8707
lgoldberg@advantageh.com