Predicting Home Health Care Services Using A Novel Feature Selection Method

Abstract

In the hospital management and medical areas, the experience of the patients is seen as having a dominant reputation. Online patient reviews are acknowledged as a crucial factor in assessing the effectiveness and quality of healthcare services. Many people find the traditional method of assessing service excellence to be cumbersome. However, the data assessment and evaluation processes are now more informal and time-efficient thanks to machine learning classifiers and opinion mining tools. Patient satisfaction and hospital patient service quality currently play a significant role in the health care industry. This is achieved by foreseeing the various hidden patterns and pinpointing the essential elements that contribute to patient fulfilment. This work provides the novel feature selection method for identifying the key feature in Home Health Care Services using patient satisfaction data. Several components are examined to evaluate the superiority of different health care services based on diverse metrics. Various machine learning algorithms are applied to guess the significant aspects affecting patient healthcare satisfaction. As recognized, the patient experience is an indispensable for assessing the quality in healthcare services.