Title of article :
Investigating and Modeling the significant reasons of Percutaneous Coronary Intervention patients to participate rarely in cardiac rehabilitation - A data mining approach
Author/Authors :
Zamir, Tara Tarbiat Modares University, Tehran Tarbiat Modares University, Tehran , Sepehri, Mohammad Mehdi Tarbiat Modares University, Tehran , Aghajani, Hassan Department of Cardiology - Tehran University of Medical Sciences, Tehran , Khakzar Bafruei, Morteza Department of Industrial Engineering - Technology Development Institute (ACECR), Tehran , Khatibi, Toktam Tarbiat Modares University, Tehran
Pages :
10
From page :
56
To page :
65
Abstract :
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
Journal title :
Journal of Health Management and Informatics
Serial Year :
2019
Record number :
2503385
Link To Document :
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