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Informative Article | Health Economics | India | Volume 9 Issue 4, April 2020 | Rating: 4.7 / 10
Forecasting Patient Persistency Behavior: A Comparison of Methodologies
Abstract: Patient persistence is a critical factor in the management of chronic diseases and effectiveness of therapies. High levels of persistency are associated with better clinical outcomes and can affect the cost - effectiveness of treatment. Understanding and improving patient persistence are crucial for achieving optimal treatment efficacy and patient health outcomes. There are various methods to calculate persistency, including the medication possession ratio, medication availability at a fixed point in time, and gaps between refills. Different methods provide distinct insights into medication adherence. The (shifted) beta - geometric (sBG) mixture model is based on a storytelling approach and has been shown to offer accurate forecasts and insights into patient dropout probabilities over time. The paper recommends the use of the sBG model as a starting point for understanding and forecasting patient persistence and retention patterns. It is important to validate the model's predictions with real - world data and compare them with other forecasting models or traditional methods of analyzing patient persistence to evaluate its effectiveness and advantages in predicting medication adherence behavior. The paper also suggests that a few key factors, such as time period, therapeutic class, and region, should be considered when calculating patient persistence.
Keywords: patient persistence, fixed interval, shrinking interval, withdrawal interval, medication adherence
Edition: Volume 9 Issue 4, April 2020,
Pages: 1828 - 1831