Physician-Specific Data Mining for Targeted Pharma Marketing
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Solution Overview
Problem
The pharmaceutical industry faces inefficiencies in marketing due to generic and static marketing materials that do not address the specific needs of individual physicians' practices, leading to high costs and ineffective influence on prescribing behavior.
Innovation Solution
A method that determines specific pharmaceutical sales and marketing information by analyzing a physician's prescribing history and disease prevalence, using a database of hierarchical medical attributes to score drug safety and efficacy based on drug-drug, drug-disease, and drug-allergy interactions, and generating practice-specific marketing materials.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If generic and static marketing materials are used for physician detailing, then marketing coverage can be maintained across all physicians, but the effectiveness of influencing prescribing behavior deteriorates due to lack of personalization
Solution Approach 1:
The patent segments the physician population into individual practice profiles by analyzing each physician's prescribing history, patient demographics, and practice characteristics. Marketing materials are then customized for each segment, moving from generic one-size-fits-all approaches to targeted messaging that addresses specific physician needs and patient populations.
Solution Approach 2:
The patent applies local quality by tailoring marketing content to match the specific characteristics of each physician's practice. This includes customizing drug comparisons based on the physician's current prescribing patterns, highlighting safety profiles relevant to their patient demographics, and emphasizing efficacy data for conditions prevalent in their practice.
2Reliability
If personalized marketing materials are created for each physician, then the effectiveness of influencing prescribing behavior improves, but the cost and complexity of marketing operations increases
Solution Approach 1:
The patent performs preliminary action by pre-analyzing physician prescribing histories and practice characteristics before marketing campaigns begin. This advance preparation creates ready-to-use physician profiles that guide personalized material generation, eliminating the need for real-time customization and reducing operational complexity during execution.
Solution Approach 2:
The patent uses copying by creating template-based personalized materials that can be efficiently replicated across multiple physicians. Once a physician profile and corresponding marketing message are developed, the system can generate similar customized materials for other physicians by copying and adapting the template structure, significantly reducing the complexity of producing personalized content at scale.
3Adaptability or versatility
If comprehensive analysis of prescribing history and disease prevalence is performed, then the relevance of marketing messages to specific physician practices improves, but the time and computational resources required increase
Solution Approach 1:
The patent applies preliminary action by conducting and storing analysis of physician prescribing histories and disease prevalence data in advance. This pre-computed information is readily available when generating personalized marketing materials, eliminating the need for time-consuming real-time analysis and enabling rapid customization.
Solution Approach 2:
The patent substitutes mechanical manual analysis with automated computer-based systems that can process prescribing history and disease prevalence data rapidly. This computational approach replaces time-intensive manual review with efficient algorithms that can analyze large datasets instantaneously, significantly reducing the time required to generate relevant marketing messages.
Data Source
AI summary
The present invention relates to a system and method for electronic and algorithmic data mining of an individual physician's prescribing history to determine the approximate distribution of diseases within their practice population for optimizing pharmaceutical sales and marketing. Rapid and large-scale determination of specific clinical safety and efficacy attributes of a marketed drug which are most pertinent and relevant to a given physician, when compared to a competitor's drug, are defined and tabularized. Major clinical characteristics taken into account include a drug's safety, efficacy, cost, dosing convenience, formulary insurance coverage, side effect profiles, and FDA approval for the intended use. A symbolic representation of knowledge is employed in which the marketed drug and each competitor's drug are compared algorithmically against each other with a scoring system that is based upon machine analysis of each major clinical characteristic. The score is further refined according to the number and severity of safety interactions which are relevant to the comparison, and also based upon predicted prevalence of such interactions within a specific physician's practice.