Estimating underdiagnosis of COVID-19 with nowcasting and machine learning.

Objective: To analyze the underdiagnosis of COVID-19 through nowcasting with machine learning in a Southern Brazilian capital city.

Methods: Observational ecological design and data from 3916 notified cases of COVID-19 from April 14th to June 2nd, 2020 in Florianópolis, Brazil. A machine-learning algorithm was used to classify cases that had no diagnosis, producing the nowcast.

Do family doctors refer less? Impact of FCM training on the rate of PHC referrals.

Objective: To evaluate the impact of family medicine residence on the PHC referral rate.

Methods: This is a cross-sectional descriptive study on 375.645 visits and 34.

Quality of data on causes of death in southern Brazil: the importance of garbage causes.

Introduction: The study objective was to analyze the quality of data on causes of death in southern Brazil.

Methods: Mortality Information System (SIM - Sistema de Informações sobre Mortalidade) data were used to evaluate the occurrence of Garbage Causes (GC) in death certificates (DCs) of residents of South states and their capitals between 2015 and 2016. The GC of each state were compared to the other states and grouped by severity level (N1 to N4, according to decreasing potential impact on mortality profile).

Use of health information systems in small municipalities in Southern Brazil.

Objective: To describe the use of health information systems in towns with fewer than 10,000 inhabitants.

Methods: Study conducted in the state of Rio de Grande do Sul, Southern Brazil, between 2003 and 2004. A self-administered questionnaire was sent to municipal managers, containing 11 single-choice questions, three multiple-choice questions and three open questions on the structure available, use of information, indicators valued and satisfaction with the systems.