Direct cost saving potential in medication costs due to a reduction in outdoor air pollution for the Brussels Capital Region.
The adverse health effects of exposure to air pollution have been well-established and include mortality, hospital admissions, emergency department visits, etc, but also less severe outcomes such as medication use and purchase. The economic impact, an additional motivator for policy, has been studied primarily for the more severe outcomes.



Purchase data of reimbursed medications typically prescribed for asthma and chronic obstructive pulmonary disease, were obtained through the mandatory Belgian health insurance system. A time series analyses approach was used to model daily sales on daily air pollution concentrations (NO2, PM10 and PM2.5) for residents of the Brussels Capital Region as a whole. In addition, a higher geographical resolution of both sales and pollutant concentrations allowed for a multi-sector approach. Annual savings were estimated for the scenario of a 10% reduction in each of the pollutants.



Medication purchase was significantly associated with NO2 concentrations, leading to an annual cost saving potential of € 107,845 [95%CI: € 71,483-€ 143,823] in R03 sales (WHO classification for drugs of obstructive airway diseases). Saving potentials of PM10 and PM2.5 were not significant. Estimates were not sensitive to the geographical resolution, however, higher precision can be obtained with higher resolution data, subject to the condition that the number of sales is sufficiently large.
Unit Health and Environment, Scientific Institute of Public Health, Juliette Wytsmanstraat 14, 1050 Brussels, Belgium; Department of Biostatistics and Medical Informatics - Public Health, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium.
Koen
K
Simons
Interuniversity Centre for Health Economics Research, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium.
Stefanie
S
Devos
Interuniversity Centre for Health Economics Research, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium.
Koen
K
Putman
Department of Biostatistics and Medical Informatics - Public Health, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium.
Danny
D
Coomans
Unit Health and Environment, Scientific Institute of Public Health, Juliette Wytsmanstraat 14, 1050 Brussels, Belgium.
An
A
Van Nieuwenhuyse
Department of Biostatistics and Medical Informatics - Public Health, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium.
Ronald
R
Buyl
D000393:Air Pollutants / Q000032:analysis; D000397:Air Pollution / Q000331:legislation & jurisprudence / Q000517:prevention & control / Q000706:statistics & numerical data*; D001530:Belgium; D002318:Cardiovascular Diseases / Q000453:epidemiology*; D017046:Cost Savings; D017281:Cost of Illness; D016527:Drug Costs / Q000706:statistics & numerical data*; D004781:Environmental Exposure / Q000191:economics / Q000706:statistics & numerical data*; D004784:Environmental Monitoring; D058735:Environmental Policy; D006801:Humans; D052638:Particulate Matter / Q000032:analysis
D000393:Air Pollutants; D052638:Particulate Matter
Air pollution; Direct costs; Medication sales; Time series analysis