A robust budget impact estimation starts with knowledge about the volume of patients that can benefit from the concerned innovation.

But, how to best estimate the optimal target population? We see quite a bit of variance between dossiers by different companies  in the applied methodology. The selected method can be driven by the type of disease (acute, chronic, life-threatening, worsening disease, …), the availability of data (size of the target population,  study size, open registries, …) as well as by clinical aspects (knowledge of the disease, type of intervention, orphan, new indication, …).

To start, you will need to properly understand the concerned indication of your innovation. Do you prefer to achieve market access for all patients in line with the label or would you limit the target population to the subgroup where the medical need is the highest? You will have to analyse this in collaboration with your medical team  and/or base it on interactions with external (clinical) experts.

Some companies work the other way around: they prefer to estimate the potential financial impact of the concerned label-based population after which they may decide to limit the population in the hope to increase the probability of success to enter the market.

Independent of the preferred methodology, at a certain point, a data source will be used to estimate the concerned patient population. This can be an open registry, sales data of competitors, historical data, literature, assumptions, … . Our recommendation is to target country specific data as for instance geo- & demographics and local clinical practice may influence patient numbers.

Of course, this is not always easy. Some disease areas are not captured as such, or the epidemiology data focus on the number of patients at the time of their index event (e.g., oncology data after which patients can progress towards a more severe health state). Or the data you need are not available (e.g., when a combination of selection criteria needs to be taken into account or when the label allows to treat a different target population versus the available data). In addition, epidemiology data can differ very broadly between sources used and additional validation is needed to limit uncertainty.

In short, a lot of variables can influence the outcome of your estimations. As a consultant we strive to play ‘devil’s advocate’ and challenge the numbers received from our clients. In some case, one can estimate patient numbers based on different perspectives. Mortality data can help to confirm the number of patients or to ‘feel’ if the estimated data is logical. Prevalence data can be projected over incidence data multiplied with overall survival data.

Whether your innovation concerns a MedTech, diagnostic or pharmaceutical innovation (or a combination of these), always strive for solid patient data. Once you have a clear view on the size of your target population, you can start to project realistic market shares on it. Does your innovation concern a ‘me too’ or is it really a breakthrough innovation? One of our clients was targeting a market share above 65% in the first launch year while the clinical benefit versus standard of care was limited and competitors had a long history of reimbursement. Although budget neutral,  we kindly advised to limit expectations.

Even when having seemingly very reliable data, stay abreast of external developments! Screen the horizon to trace upcoming competitors and take the awareness effect (experts and patients) and cultural shift (patients) into account. This will certainly help you end up with a robust set of estimations even when the concerned indication has a volatile aspect (e.g., viral).

Getting the patient flow well defined and being able to attribute the right numbers highly important but not necessarily an easy feat for most dossiers, but certainly achievable with the right mind-set and expertise.

Do you want to get in touch with us?

contact