In our latest series of blogs, we’ll be sharing tips and insights gained over the course of our many years of experience.
This post will look at Oncology Forecasting, and accounting for chronic patients in your forecast.
We’ll now hand over to Kris Barker, Senior Consultant here at J+D Forecasting:
It may well be the case that you have patients who are expected to remain on treatment indefinitely, and hence you need to factor this chronic treatment of patients into your forecast model. With an Onco+ forecast, the easiest way of doing this is to use the ‘persistency curve’ feature within the Therapy Duration section. In this section of your model, you are effectively taking your incident patients at each time period from your Events section, and converting these to ‘patients on treatment’ at each time point using either average length of treatment or persistency curves. Using persistency curves, you can more accurately model the length of time that patients remain on treatment and, if you are needing to model a proportion of patients who receive the treatment indefinitely, then you can make sure that the persistency curve value remains above 0%. In the example below, you can see that for Product 1, there are 5% of all patients treated with this product who remain on this treatment for the duration of the forecast period (whilst all other treatments see the persistency drop to 0%, i.e. no chronic treatment).