Respiratory Care Awareness Week: How Real-World Evidence Can Help Relieve the Burden of Respiratory Diseases

Respiratory diseases are a significant challenge for European healthcare, especially during colder months when there is a surge in hospital visits and healthcare resource utilisation (HCRU), (European Centre for Disease Prevention and Control, 2023). The strain on the system intensifies as the number of patients with respiratory conditions, both chronic and seasonal, increases. This leads to overwhelming pressure on emergency services and a growing demand for resources, highlighting the importance of optimising respiratory disease care.

Beyond seasonal respiratory diseases like COVID and RSV, chronic conditions such as asthma and chronic obstructive pulmonary disease (COPD) impose a persistent burden. These chronic illnesses place substantial strain not only on healthcare systems but also on patients, their families, and society as a whole. In 2020, about 339 million people were affected by asthma, a condition linked to a significant health burden (WHO, 2020). Frequent exacerbations often necessitate emergency care, which disrupts patients’ quality of life and places additional stress on their support networks. The considerable healthcare costs associated with managing these conditions further highlight the urgent need for more efficient and effective treatment pathways. (Lykkegaard, J. et al., 2022).

The good news is, that there have been significant advancements in the treatment of respiratory diseases in recent years, including innovative therapies targeting asthma and COPD. New treatment options, such as biologics and combination therapies, have opened new possibilities for managing these conditions (Farrell, L.A. et al., 2024). However, determining the most appropriate treatment for each patient remains a complex challenge. With many different treatment options available, individual patient responses can vary, making it difficult to establish which approach will be most effective for a given person.

This is where Real-World Data (RWD) proves invaluable. RWD allows healthcare providers to analyse patterns in treatment effectiveness, enabling them to identify which therapies are likely to work best for particular patients. By observing real-life patient outcomes, healthcare professionals can gain insights into how treatments perform outside the controlled settings of clinical trials.

Randomised controlled trials (RCTs), while considered the gold standard for evaluating treatment efficacy, often fall short when it comes to respiratory disease patients (Walters, S.J. et al., 2022). These trials frequently exclude individuals with chronic or severe respiratory diseases due to strict inclusion criteria, which aim to minimise safety risks. As a result, people living with these conditions, particularly those with multiple comorbidities, are often left out, meaning that the findings may not fully apply to the broader, more diverse groups that clinicians encounter in everyday practice. Real-World Data (RWD), however, offers a more accurate reflection of treatment outcomes across a wider range of patients, including those with complex health profiles.

Moreover, RWD plays a crucial role in assessing the safety of treatments for respiratory diseases. Real-world patients, particularly those with chronic conditions like asthma and COPD, often have different reactions to treatments than those observed in clinical trials. RWD could help confirming the safety of these therapies in real-world settings, offering a more comprehensive understanding of potential side effects and risks when used by a wider patient population.

For healthcare systems under strain, the utilisation of Real-World Data is essential. By observing real patients in real time, hospitals can optimise treatment approaches, ensuring that the therapies selected are both the safest and the most effective available, all while maintaining sustainable costs. Rather than being overwhelmed by seasonal spikes or the ongoing demands of chronic cases, RWD can uncover patterns, identify high-risk patients early, and guide more precise interventions.