Data Science to Improve Patient Management System

The rate at which people miss hospital appointments has decreased but remains a big concern for health care professionals as well as funding agencies. This research paper used an open data obtained from the NHS database to determine the factors that may lead to missed appointments and create a model that can be used to predict the likelihood of a patient missing an appointment. Logistic regression models and bivariate analysis were used to determine whether there was a meaningful relationship/association between "did not attend" and forgetfulness, gender, apathy, and transportation. An extensive literature review was conducted to narrow down the reasons that might lead to missed appointments. In conclusion, the research showed there was a significant difference between gender, type of clinic and apathy in organizations.

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