Investigating and Modeling the Reasons of Percutaneous Coronary Intervention Patients to Participate Rarely in Cardiac Rehabilitation: A Data Mining Approach

Introduction: the high prevalence of cardiovascular diseases has caused many health problems in countries. cardiac rehabilitation programs (crps) is a complementary therapy for percutaneous coronary intervention (pci) patients. however, pci patients hardly attend crps. this study aims to decipher the reasons why pci patients rarely participate in crps after pci. methods: a cross-sectional study was used. the parameters affecting the attendance of the patients at crps were identified by using the previous studies and opinions of experts. a questionnaire was designed based on the identified parameters and distributed among pci patients who were referred to tehran heart center hospital. according to data mining approach, 184 samples were collected, cleaned by replacing the corresponding mean value, and classified with three algorithms (decision trees, k-nearest neighbor (knn), and naïve bayes) by using spss 19 and weka 3.6. results: the obtained results by decision trees were superior with the average accuracy of 82%, while knn and naïve bayes obtained 81.2% and 78%, respectively. results of j48 classification algorithm and regression showed that lack of physician’s advice was the most significant reason for non-participation of pci patients in crps (p< .001). other factors were family and riends’ encouragement, paying expenses by insurance, awareness of the benefits of the crps, and comorbidity, respectively. conclusion: results of the best model can help medical centers to increase the knowledge about the factors that affect participation of pci patients in crps. therefore, related centers can provide better services for patients.