ABSTRACT
Asthma is a respiratory disease and a significant global health problem. Current methodologies of management have not been individualized, hence low patient outcomes. Furthermore, Asthma is typified by a few symptoms, hence patients’ personal decisions may alter formulation adherence. This study suggests the definition and examination of an original CDSS to facilitate individualized asthma care. The CDSS will assess findings in patient data utilizing machine-learning algorithms, allowing the patient for additional suggestions. It will also assist physicians in making individualized decisions regarding the care of patients affected by asthma who are conducive to better adherence. In this study, we will conduct a pilot study enrolling several asthma patients at different points to determine the efficacy of the CDSS. The information will be retrieved through a questionnaire and evaluation of medical records in the pre- and post-periods of CDSS use. The rates of change in interest levels will be compared over this period. The proposed CDSS is expected to enhance patients’ asthma control with early intervention and adequate medication regimens. The frequency of exacerbations is expected to decrease by 20–30%. Moreover, the CDSS may also improve the rates of adherence and further the practices by 10–15% and reduce the costs of medication and care. At the same time, the user-friendly system optimally educates patients and provides alerts in a timely manner. Thus, CDSS technology for patient-centered asthma therapy appears promising with the reference.
