Predicting no-show appointments in a pediatric hospital in Chile using machine learning.

ABSTRACT: The Chilean public health system serves 74% of the country's population, and 19% of medical appointments are missed on average because of no-shows. The national goal is 15%, which coincides with the average no-show rate reported in the private healthcare system. Our case study, Doctor Luis Calvo Mackenna Hospital, is a public high-complexity pediatric hospital and teaching center in Santiago, Chile. Historically, it has had high no-show rates, up to 29% in certain medical specialties. Using machine learning algorithms to predict no-shows of pediatric patients in terms of demographic, social, and historical variables. To propose and evaluate metrics to assess these models, accounting for the cost-effective impact of possible intervention strategies to reduce no-shows. We analyze the relatio

SUBMITTER: Dunstan J 

PROVIDER: S-EPMC10257628 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature