Description of the pharmaceutical treatment advice in patients with respiratory symptoms in primary care setting (DEPART)

Study type

• Study type:
  Non-interventional study

Non-interventional study

• Non-interventional study design:
  Cohort

Study drug and medical condition

• Medical condition to be studied:
  Chronic obstructive pulmonary disease

  Asthma

  Asthma-chronic obstructive pulmonary disease overlap syndrome

Population studied

• Age groups:
  • Adults (18 to < 46 years)
  • Adults (46 to < 65 years)
  • Adults (65 to < 75 years)
  • Adults (75 to < 85 years)
  • Adults (85 years and over)
• Estimated number of subjects:
  19000

Study design details

• Main study objective:
  Percentages will be used to express the concordance of the pharmacological advices provided by the AC service at the first visit and the patient-reported inhalation medication prescribed by the GP at visit two.
• Outcomes:
  Statistical analyses will be performed to gain insight into factors associated with concordance or discordance. In addition, to investigate associations between switching pharmacological treatment, health status, and the number of exacerbations. Regression and (optional) multilevel modeling will be performed to clarify the predictor variables which contribute to refrain from treatment advice
• Data analysis plan:
  The primary outcome parameter is percentages that express whether the provided treatment advice is followed by the general practitioner. Differences between the re-referred group and the group visiting the AC service once will be examined. Using several statistical analyses depending on measurement levels. The analysis will be performed to gain insight into possible differences between the concordance and discordance group. Whether or not the provided pharmacological treatment advice is followed serves as the dependent variable. If the p-value is <0.05, the results will be reported as statistically significant. Differences in the number of exacerbations and health status between the concordance group and discordance group will be examined by multivariate analyses. A multiple logistic regression model and (optional) multilevel modeling will be used to model the probability of switching pharmacological treatment between the first visit and the follow-up visit.