Abstract
Emergency services are essential to the organization of the health care system. Nevertheless, they face different operational difficulties, including overcrowded services, largely explained by their inappropriate use and the repeated visits from users. Although a known situation, information on the theme is scarce in Brazil, particularly regarding longitudinal user monitoring. Thus, this project aims to evaluate the predictive performance of different machine learning algorithms to estimate the inappropriate and repeated use of emergency services and mortality. To that end, a study will be conducted in the municipality of Pelotas, Rio Grande do Sul, with around five thousand users of the municipal emergency department. If the study is successful, we will provide an algorithm that could be used in clinical practice to assist health professionals in decision-making within hospitals. Different knowledge dissemination strategies will be used to increase the capacity of the study to produce innovations for the organization of the health system and services. A high performance predictive model may be able to help decisionmaking in the emergency services, improving quality of care.
Highlights
In Brazil, urgent and emergency services are a fundamental part of the health care system, ensuring timely assistance for individuals in accidents and life-threatening cases[1]
Each interviewer will perform tests with their family members or friends to increase accuracy and practice the use of research instruments
The study will test algorithms to predict the inappropriate use of emergency services, repeated visits to the service, and death within one year after the interview
Summary
In Brazil, urgent and emergency services are a fundamental part of the health care system, ensuring timely assistance for individuals in accidents and life-threatening cases[1]. Barriers to access to primary health care (PHC) include difficulties in scheduling appointments, obtaining information about health problems, obtaining long-term control medications, and participating in educational groups This context increases the demand for emergency services to deal with conditions that could be treated at other, more appropriate care levels for longitudinal and comprehensive care[7]. Despite the relevance of emergency services and the outcome assessment among users of these services, Brazil has produced few studies on the topic, and for the most part, they are limited to cross-sectional estimates of the demand met[19] Monitoring these individuals can contribute to identifying population groups with a higher risk of inappropriate use of emergency services, repeated visits to the service, and adverse outcomes, especially mortality.
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