An Intelligent Application for Determine Patient Satisfaction using Data Mining Techniques - Kayalvizhi, S.; Gunasekar, T.; Thenmozhi, S. (IJRDO -Journal of Computer Science Engineering, 2017)
The healthcare industry today generates large amounts of complex data data about patients,hospital resources, disease diagnosis, electronic patient records and medical devise. Datamining is a collection of algorithmetic ways to extract informative patterns from raw data. Inthis paper, the researcher describe a novel methodology which employs machine learning asan alternative means to explore hospital characteristics and client satisfaction, for decisionmaking and improved quality of care. Applied well known feature selection and data miningalgorithms such as forward selection and Naïve Bayes respectively, to determine patientsatisfaction. The dataset comprised of three types of data which are patient perception aboutreceived care, Nurse perception about the working environment and Organizationalattributes of the hospital. The experimental results exhibited high classification accuracy91.3%, allowing valid conclusions to be reached about the organizational and workforcefactors which attribute to patient satisfaction. The findings were validated using traditionalstatistical methods such as binomial correlation and linear regression.. The result of thestudy will be beneficial to current and future SMEs in India.