A predictive model for retention in specialized HIV/AIDS care

Abstract

The establishment of universal targets for HIV/ AIDS control and the implementation of treatment as prevention reinforce the need for on-going clinical follow-up of persons living with HIV/AIDS as an essential element of their care, where retention in care is both a need and a challenge. This study aimed to create a predictive model for retention of persons living with HIV/AIDS in health care. A decision tree statistical model was created, based on sociodemographic, clinical, and health behavior variables, identified in a database with information from 260 persons with HIV/AIDS, enrolled in a specialized treatment service. The model enabled the identification of nine variables with significant information gains in relation to the outcome variable, probable retention in health care, and the development of 24 decision rules, giving rise to a decision tree with 80.4% correct answers, which can help identify possible strategies to optimize retention and contribute to achieving the proposed targets for confronting the epidemic in the coming years.