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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) : 308-315
doi: 10.18176/jiaci.0483

Background: The proposal and the initiative for the Prevalence of Severe Asthma in Hospital Units in Spain (PAGE) study came about because of the 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 was to determine the prevalence of severe asthma in the outpatient clinics of allergy and pulmonology departments in Spain. The secondary objectives were to describe the most prevalent characteristics and phenotypes of severe asthma, to evaluate the selection criteria for receiving approved biological treatments for this disease, and to estimate consumption of resources. Furthermore, digital technology and new data collection sources made it possible to reuse information stored in electronic medical records (Big Data). The study was performed using one such tool, Savana.
Methods: The PAGE study was a multicenter, nonexperimental, observational, cross-sectional study in the first phase and a prospective study in the second phase. The study was controlled and population-based, with 2-stage selection of patients by random sampling. The research was carried out in 40 hospitals selected using convenience sampling in order to ensure geographical representativeness in Spain.
Results: This manuscript describes the study design and protocol.
Conclusions: Our study design was sufficiently robust to avoid bias and to establish the prevalence of patients with severe asthma in Spanish hospitals. It was also the first to incorporate new tools that can help in routine clinical practice and research, such as big data analysis software, and to evaluate the reliability and efficiency of these tools.

Key words: Severe Asthma, Big data, Prevalence, Hospital, Machine learning, Predictions