Patient Flows – From Complexity to Simplicity
Pharmaceutical organizations, more than ever, are seeking to better understand the patient journey as they strive to maximize the potential of their brands by tying their thinking to their patients, as this approach results in accurate forecasts and effective marketing strategies. However, this endeavour brings with it several complexities like – Evolving population dynamics, changing regimen usage and medication compliance trends, to name a few. Patient flow becomes an increasingly valuable tool here as it helps model these complexities and illuminate the mechanics behind them.
Patient flow models are market specific. By definition, they model the unique flow of patients through a specific disease area and capture the nuances of that market’s treatment process. Creating such a model requires gathering and sorting copious amounts of patient-level data. Analysts need to quantify how patients in a specific disease area move through that disease. That means pinpointing how long they exhibit certain symptoms, their relapse rates, their adherence rates, their survival rates, and the therapy models they follow.
Patient Flow Analysis is always effective but when it needs to be done repeatedly over multiple indications, it turns –
- Complex in terms of development
- Intensive in terms of effort and data, and
- Cumbersome in terms of current reporting processes
Having identified these drawbacks, D Cube developed a completely automated therapeutic area agnostic Patient Flow tool that develops rapid, repeatable and actionable flows at a fraction of the effort required by current practices. The objective was to ensure applicability across TAs and scalability across multiple assets.
The algorithm is holistically designed to be a self-service solution, that is to say it’s comprehensive in its ability to answer key questions that a brand team would expect from a patient flow, while being intuitive enough for anyone to provide a few inputs to the algorithm and have a patient flow analysis done in a short span of time. Additionally, we eased the scalability of the solution by automating the process of outputs creation (PowerPoint presentations and Tableau dashboards).
The solution was immediately well received by our client’s brand teams and is being –
- Deployed across all inline and pipeline assets to devise better forecasts based on future trends influenced by the use of their product in different lines of therapy rather than historical epidemiology trends.
- Leveraged to analyse emerging markets and how patients move within them, the duration of therapy for a patient on a line before drop-offs or progressions, patient share and top combination therapies.
- Utilized to model unknowns in a patient’s journey and thus forecast what volume a pharma company can expect to sell in a given market over a given period.
We are seeing a marked increase in our clients’ interest for this productized approach as they are looking to better understand their patients and align marketing decisions. Get in touch with us to find out how we can help you leverage Patient Flows better.