Investigating and Modeling the significant reasons of Percutaneous Coronary Intervention patients to participate rarely in cardiac rehabilitation - A data mining approach

Tara Zamir, Mohammad Mehdi Sepehri, Hassan Aghajani, Morteza Khakzar Bafruei, Toktam Khatibi


Objective: 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: 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.

Results: According to data mining approach, 184 samples were collected and classified with three algorithms (Decision Trees, k-Nearest Neighbor (kNN), and Naïve Bayes). 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 showed that lack of physician’s advice was the most significant reason for non-participation of PCI patients in CRPs (P< .0001). Other factors were family and friends’ encouragement, paying expenses by insurance, awareness of the benefits of the CRPs, and comorbidity, respectively.

Conclusion: Results of the best model can enhance the quality of services, promote health and prevent additional costs for patients.


Keywords: Cardiovascular Disease, Percutaneous Coronary Intervention, Cardiac Rehabilitation Programs, Data Mining, Classification

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