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

Autor: Tara Zamir, Mohammad Mehdi Sepehri, Hassan Aghajani, Morteza Khakzar Bafruei, Toktam Khatibi
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Journal of Health Management & Informatics, Vol 6, Iss 2, Pp 56-65 (2019)
Druh dokumentu: article
ISSN: 2322-1097
2423-5857
Popis: 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
Databáze: Directory of Open Access Journals
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