2. Quantitative research


Quantitative research

Quantitative research, as its name implies, is concerned with quantifying results of observations/measurements and is research that generates numerical data or data that can be converted into numbers. Quantitative data is any data that comes from an objective measurement such as cholesterol level in a blood sample, or number of individuals aged 18 to 25 in a sample.

Common types of quantitative research in health technology development are experiments, often in the form of randomised controlled trials, which seek to measure the effects of a new technology in comparison with other treatments (comparators, usually the standard of care or ’gold standard’) or (in some cases) no treatment (placebo-controlled). Trial participants are observed or contribute to obtaining important data such as changes in measurable parameters of the targeted disease (endpoints), possible side effects (adverse events), and subjective data like pain scores (e.g., scales). It is assumed that these observations are a fair reflection of reality and are predictive of the future. For example, if a new medicine reduces heart attacks compared to a comparator in repeated experiments, it is assumed that this will likely happen in similar patients with the same type of medicine in the real world situation, as opposed to the more controlled conditions in a clinical trial.