[Adverse Drug Events in Hospitalized Patients in Chile: Prevalence & Implications].

Objective: To study the prevalence of adverse drug events (ADE) in hospitalized patients in Chile. As part of our research, we also assessed the validity of the method used to identify the occurrence of an ADE based on the discharge diagnoses of the patient.

Design: The study included 1,7 million patients hospitalized during 2019-2020.

Methodologically grounded semantic analysis of large volume of chilean medical literature data applied to the analysis of medical research funding efficiency in Chile.

Background: Medical knowledge is accumulated in scientific research papers along time. In order to exploit this knowledge by automated systems, there is a growing interest in developing text mining methodologies to extract, structure, and analyze in the shortest time possible the knowledge encoded in the large volume of medical literature. In this paper, we use the Latent Dirichlet Allocation approach to analyze the correlation between funding efforts and actually published research results in order to provide the policy makers with a systematic and rigorous tool to assess the efficiency of funding programs in the medical area.

Machine Learning Readmission Risk Modeling: A Pediatric Case Study.

Background: Hospital readmission prediction in pediatric hospitals has received little attention. Studies have focused on the readmission frequency analysis stratified by disease and demographic/geographic characteristics but there are no predictive modeling approaches, which may be useful to identify preventable readmissions that constitute a major portion of the cost attributed to readmissions.

Objective: To assess the all-cause readmission predictive performance achieved by machine learning techniques in the emergency department of a pediatric hospital in Santiago, Chile.

[Waiting lists management model based on timeliness and justice].

Waiting lists for elective surgery are considered a major health policy concern in most countries of the world. The most common reason to explain this phenomenon is that demand exceeds supply. Traditionally, the management of waiting lists has been focused on timeliness of medical attention.