Top 5 forecasting tips in Oncology.
Contact us for a consultation Find more J+D Forecasting insights 1 – All Change Consider the stability of the market when deciding on the methodology. Patient flow models are accurate and provide a great deal of insight, however, they’re only really necessary when there is a part or future variability across stages or lines of …
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Find more J+D Forecasting insights
1 – All Change
Consider the stability of the market when deciding on the methodology.
Patient flow models are accurate and provide a great deal of insight, however, they’re only really necessary when there is a part or future variability across stages or lines of treatment.
2 – Devil’s in the detail
Using pre-calculated treatable patients saves a lot of time.
However, check the data and assumptions used by your data provider. They should use up-to-date sources that are local where possible
3 – Look before you jump
As with all forecasting, there are 3 key considerations that should be weighed against each other: value of the decision, accuracy required and the data available.
Before employing a patient flow methodology, rather than a more simplistic prevalence-based model, the forecaster should consider if the data supports the methodology, lots of complex algorithms do not deliver value if the inputs are largely assumption-based.
4 – Does it make a difference?
Sometimes there is an urge to forecast a variable because you can, but the more detailed and complex a model is, the less value it will often bring.
So always ask the question: Does it make a difference? A good example is the inclusion of 3rd or 4th line patients, does their inclusion make any substantial difference to the final forecast? If the answer is no, then group them.
5 – Step out of the bubble
Your product can achieve great OS, or perhaps PFS or ORR, however, the wider environment may pose some challenges.
Consider some questions:
- How competitive is the market?
- How much investment is required to penetrate a highly competitive market?
- What is the distribution of potential prescribers?
- Could the healthcare system bear the cost of the product?