Severity assessment of chronic obstructive pulmonary disease based on hesitant fuzzy linguistic COPRAS method

Abstract Chronic obstructive pulmonary disease (COPD) has two courses with different options for medical treatment: the acute exacerbation phase and the stable phase. However, the patients suffered with COPD, whether it is acute or stable, serious or mild, are willing to go to the general hospitals rather than the primary-level professional medical institutions, which leads to the imbalance of medical resources in hospitals with different levels. In order to allocate patients into different levels of hospitals, the fundamental and important thing is to assist the doctors to assess the severity of the COPD patients. This paper establishes an assessment indicator system about the severity of the COPD from the perspectives of system engineering and actual clinical experience, and then proposes a hesitant fuzzy linguistic complex proportional assessment (HFL-COPRAS) method to solve the decision-making problems under hesitant fuzzy linguistic environment. This method not only matches the doctors’ expression habits, but also considers both benefit and cost criteria with the proportional calculation. In addition, the weights of criteria are derived by the negative-ideal-solution-based method. Finally, we apply the HFL-COPRAS method to assess the severity of the COPD patients in the West China Hospital.