Description

The project focuses on evaluating the management in the implementation of the INSPIRE respiratory health program, being applied in the health network of the municipality of Botucatu with the active co-participation of municipal managers and the local population, aiming to achieve all the proposed results. This thorough evaluation will be conducted through a longitudinal cohort study, with patient follow-up over five years. All evaluated subjects will be contacted annually to contribute to effective management and positive outcomes in respiratory health. The primary care networks (basic health and family health networks), secondary care, including urgent care and emergency units, and tertiary health care in Botucatu (tertiary hospital in the municipality of Botucatu) will participate.

The local media and primary health care unit will be informed of the monthly dates on which individuals with a history of smoking and/or passive exposure and/or respiratory symptoms can be referred for a multiprofessional evaluation. This referral can be made during a consultation or by spontaneous demand at the primary health care unit, which in turn will refer for specialized evaluation.

Statistical analyses will be divided into three main packages: disease incidence, clinical evaluation, and AI algorithms. Positive cases occurring during the evaluation period will be considered for disease incidence. For incidence calculation, the time to diagnosis for each participant will be considered in a measure expressed in person-years. Poisson regression models will be applied to estimate the relative risk for incidence among all possible groups to compare sociodemographic and other characteristics. Adjustments for possible confounding factors may be necessary and will be decided later. The second package includes the comparison between clinical characteristics and body composition. Positively and negatively screened individuals will be compared using appropriate statistical tests. Continuous variables will be tested for symmetry, and appropriate tests will be conducted (t-test or Wilcoxon; ANOVA or Mann-Whitney; parametric or non-parametric regression models). Fisher's exact tests and Chi-square (heterogeneity or trends) will be used for categorical variables.

Each participant will have their coding, preventing the identification of patients. Medical data will be kept confidential and securely stored. To ensure data quality, all researchers will be trained before the start of the study, contact with the coordinator will be allowed to clarify study protocol-related doubts, coded electronic databases will be used, which will be monitored by an external team to the study and will draw patient codes that will be monitored and their data certified. Discrepant data will automatically question the veracity of the data to reduce data inconsistency. Data will be continuously monitored to identify and correct inconsistencies. The data capture program will be REDCap, in which the developer will be solely responsible for database modifications after approval by the scientific committee.