PAGE Study: Summary of a study protocol to estimate the prevalence of severe asthma in Spain using big-data methods
Almonacid Sánchez C1, Melero Moreno C2, Quirce Gancedo S3,8, Sánchez-Herrero MG4, Álvarez Gutiérrez FJ5, Bañas Conejero D4, Cardona V6, Soriano JB7,8
1Hospital Ramón y Cajal IRYCIS, Madrid, Spain
2Hospital 12 Octubre, Madrid, Spain
3Hospital La Paz, Madrid, Spain
4GlaxoSmithKline, Madrid, Spain
5Hospital Virgen del Rocío, Sevilla, Spain
6Hospital Vall d’Hebron, Barcelona, Spain
7Hospital de la Princesa, Madrid, Spain
J Investig Allergol Clin Immunol 2021; Vol. 31(4)
Background: The proposal and the initiative to conduct the Prevalence of Severe Asthma in Hospital Units in Spain (PAGE) study arises from the perspective of widespread implementation of electronic medical records and the limited data available on the prevalence of severe asthma in hospitals in our setting.
Objectives: The primary objective is to determine the prevalence of severe asthma in the outpatient departments of allergy and pneumology services in Spain. Secondary objectives include describing the most prevalent characteristics and phenotypes of severe asthma, evaluating the selection criteria for receiving approved biological treatments for this disease, and estimating resource consumption. Furthermore, taking advantage of the incorporation of digital technology and new data collection sources, which allow the reuse of information stored in electronic medical records (Big Data), the use of one of these tools (Savana) has been integrated into the study.
Methods: The PAGE study is designed as a multicenter, non-experimental, observational, cross-sectional study in a first phase, and prospective in a second phase, controlled, population-based, with a two-stage selection of subjects by random sampling. The research will be carried out in 40 hospitals, following a criterion of convenience, which assumes the geographical representativeness of Spain.
Results: This manuscript describes the study design and protocol.
Conclusions: Our study design is robust to avoid bias and to allow establishing the prevalence of patients with severe asthma in Spanish hospitals. It is the first to incorporate new tools that can help in routine clinical practice and research, such as big data analysis software, and to evaluate its reliability and efficiency.
Key words: Severe Asthma, Big data, Prevalence, Hospital, Machine learning