This study aims to know how the pandemic has affected the health of citizens and has modified the health care activity in primary care centers
Keywords: COVID-19; primary care; diagnose variations; big data; ICD10
The results shows that consultations related to infectious and parasitic diseases have almost doubled due to the pandemic: The increase has been 91.07%, given that in 2019, 52220 diagnoses were made and in 2020, 99,779.
The work also shows how the total number of visits made by the teams has not changed significantly (1,402,406 visits during 2020 and 1421,779 in 2019). What has changed is the reason for the visit and the way it is attended.
Description of the Study:
- Title: Big data-based analysis to characterise and identify variations in the type of Primary Care visits before and during COVID in Catalonia.
- Principal Investigators: Francesc Lopez Segui, Guillem Hernandez Guillamet, Héctor Pifarré Arolas, Xavier Marin Gomez, Anna Ruiz Comellas, Anna Maria Ramirez Morros, Cristina Adroher Mas and Josep Vidal Alaball.
- Centers of Implementation: Research and Innovation Unit of Institut Català de la Salut (ICS).
- Study Population: Database from the Primary Care Services Information Technologies System of the Health Region of Central Catalonia (Catalonia, Spain) belonging to the Catalan Institute of Health.
- Methods: A database from the Primary Care Services Information Technologies Information System of Catalonia is used. The aim of the analysis is the register of visits (2,824,185) and their diagnostic codes (3921974, mean 01.38 per visit) as approximators of the reason for consultation, registered according to the International Classification of Diseases (ICD-10) at three different grouping levels. The data is represented by a term frequency matrix and analysed recursively in different partitions aggregated according to date.
Objectives of the Study:
Principal Objective: To analyse diagnoses from primary care visits and distinguish between those that had higher and lower variations, relative to the 2019 and 2020 periods (roughly pre- and during COVID), to identify clinical profiles that may have been most impaired and diagnoses least visited during the pandemic.
More about this Study:
Background: The COVID-19 pandemic has turned the care model of health systems around the world upside down, abruptly cancelling face-to-face visits to avoid contagion and redirecting the model towards telemedicine. Digital transformation boosts information systems, which, the more robust they are, the easier it is to monitor the healthcare system in a highly complex state and allow for more agile and reliable analysis.