Preparing epidemiology data for use in a forecast model - do you know your target population?
Use our guide to check your thinking.
Identifying patient segment(s):
Do you know the indication for the product in sufficient detail for a forecast?
Are there specific inclusion or exclusion criteria mentioned in the label?
Are these mentioning specific comorbidities (e.g. diabetes, atrial fibrillation, COPD etc)
Are these mentioning specific clinical parameters? (e.g. blood pressure, kidney function, ejection fraction?)
Are these mentioning specific drug interactions / contra-indications with other medications? (e.g. anti-fungals, statins, ace inhibitors etc)
Are there any age or gender exclusions mentioned? (e.g. not suitable for women of child bearing age or under 12 year so of age?)
Does the label mention restriction to populations treated with specific prior drug treatments or specific line of therapy, or those refractory to certain treatment options?
Suitable epidemiology sources:
Do you have a suitable source to go to for epidemiology data?
Does the source have data for the head-line epidemiology in a suitable format?
Does the epidemiology data set extend across the time period needed for the forecast model?
Does the data set include parameters / subpopulations that allow suitable identification of patients to align with the label indication?
Robustness and data quality:
Are key sources listed and documented?
Has the data been based on country specific sources or extrapolated from another country?
What methodology was used to construct the dataset?
How was the data projected for the forecast period?
Have impacts of medications / vaccinations / diagnostics been included in the data set? (where relevant)
Our FREE Guide To Epidemiological Data
Our downloadable guide, How To Evaluate Good Epidemiology Data explains how to analyse and make decisions based on Epidemiology data. To access a free copy, simply follow this link - How To Evaluate Good Epidemiology Data.