Asthma requires daily monitoring of lung function, which can be affected by variations in medication usage, in addition to a number of different behaviors and triggers. Problems associated with an inappropriate type or dosage level of medication are especially important. Despite our recognition of the variability in patients’ responses to various types of medications and dosage levels, little has been put into place that would monitor a patient’s responses to medication in a continuing way so that proper adjustments can be made for the duration of the use of that drug therapy. The determinants of reduced lung capacity and more severe attacks also vary by individual. Modeling the relationship between levels of stress, exercise, and exposure to environmental triggers such as smoke (first-hand and second-hand) and pollen and the resultant lung function represents another important challenge in this study.
Our approach seeks to optimize the effectiveness of ongoing medical treatment by using adaptive control techniques. These are time series modeling techniques that are used by engineers to ensure the best possible outcomes in dynamic processes. Such models can be accommodated to the needs of medicine and social sciences to increase the positive results of interventions. The basic idea is that first a criterion for determining a good outcome is established (e.g., minimum asthma symptoms with minimum medication dose). Repeated measurements are taken to monitor the outcome. As soon as the outcome deviates from the criterion, the level or content of the intervention is modified to counteract this deviation. At the next measurement occasion, the direction of the outcome is checked for improvement and, if necessary, subsequent modifications of the intervention are made. Unlike many other intervention strategies, the degree or content of the intervention can be adjusted on an individual basis.
In the first phase of this study (currently under way), this will result in the modeling of these relationships indicated above. We currently have intensive data on 15 participants including measures of expiratory lung capacity, incidence of attacks, and triggers along with a number of background variables.
Once these data are modeled, the eventual goal of the project is to apply time series and control modeling techniques to determine the optimal therapy for patients with asthma, with the proximate goal to keep each patient free of disease symptoms and with the ultimate goal of maintaining healthy lung functioning. The application of these techniques will allow the investigators to identify and optimally accommodate individual differences in how drugs operate within persons over time, as well as differences due to variations in levels of stress, exercise, and environmental triggers. These methods will enable the health care provider to make adjustments on an individual basis to medication dosage and/or type of medication, as well as patient-specific recommendations regarding avoidance of behaviors and contexts that trigger symptoms, so that the best outcome is achieved for each individual patient.