Patient Flow Modeling
In an era of escalating marketing and promotional spend, the ability to look at markets and patients from unique perspectives takes on an increasingly important role. Excel-based modeling is appropriate for point-in-time analysis, but is insufficient for modeling the longitudinal reality of patients within markets. Understanding the dynamics of the system, where an event influences an outcome, which in turn influences the future event, is a critical tool in creating a differentiated marketing message and anticipating, rather than reacting to, market trends. For example, an HIV patient's future regimen is determined by prior drug treatments, adherence, viral strain, and resistance levels. Patient flow modeling allows for these interactions, and provides a rich information source that can drive strategy development. The company that differentiates itself into the future will be the company that identifies relevant patient segments and develops targeted messages to these groups rather than to a fictional "average" patient.
CASE EXAMPLE
Situation A market with strong historical growth experienced a recent deceleration despite significant spending on DTC and professional promotion. Traditional secondary data analysis was not useful in elucidating the reasons for the decline and a better understanding of the patient dynamics was necessary to re-define product strategy and to renew growth.
Approach Trinity facilitated a meeting with the brand and business analysis teams to develop a conceptual map of patient flows within the market. We leveraged patient segmentation studies, epidemiology data, and longitudinal secondary data (claims data) to model patient movements over time. We populated the model using systems dynamics modeling software, and tuned to actual historical market behavior to discover reasons for the market's softening. We simulated several marketing strategies into the future to establish their potential impacts.
Result Trinity's model was validated through historical data and brand-team market knowledge, yielding significant strategic insights resulting from the longitudinal approach to the data. For example, DTC spending targeted treatment of naïve, undiagnosed patients. The majority of receptive patients to this treatment were already targeted, and the patient pool was dwindling. Additionally, marketing lever points such as adherence programs and targeted messaging to "quitters" were highlighted and modeled to optimize future value.
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