Evaluation of the implementation of the obstetric risk system (ORS) on the accuracy of classification, prevention of maternal Near Miss, and optimization of care in the maternal and child unit of the university hospital

Abstract

Introduction: Maternal and perinatal morbidity and mortality remain major challenges for health systems, highlighting the importance of strategies that ensure timely access and safe obstetric care. Obstetric risk classification, supported by computerized systems, has become an essential tool for organizing care flow, improving clinical decision-making, and strengthening patient safety. Objective: To analyze the profile of obstetric care visits classified by risk and discuss the contribution of computerized systems to the organization of the nursing work process in obstetric care. Materials and Methods: This descriptive, retrospective study with a quantitative approach analyzed 489 obstetric care records classified according to a reception and risk assessment protocol. Data were extracted from a computerized health information system, organized in electronic spreadsheets, and analyzed using descriptive statistics. Variables included risk classification, main complaints, clinical conditions, and care outcomes. Results: A total of 489 obstetric visits were analyzed. Green (42.9%) and yellow (37.6%) classifications predominated, followed by orange classification (18.6%). The most frequent complaints were abdominal pain, uterine contractions, and vaginal bleeding. Pain was reported in 60.7% of cases, while uterine contractions were observed in 11.9% of pregnant women. General health status was considered good in 99.6% of the records. Hospital discharge and admission were the most common outcomes, demonstrating the service's capacity to effectively manage obstetric demands. Scientific Contribution: The findings reinforce the relevance of computerized risk classification systems in obstetric care by improving record standardization, supporting nursing decision-making, enhancing patient safety, and strengthening the management of healthcare processes. Furthermore, the study provides evidence on the epidemiological profile of pregnant women receiving obstetric emergency care. Conclusion: Computerized risk classification protocols contribute to the early identification of obstetric emergencies, improve care flow organization, and support nursing practice. These systems represent a strategic resource for enhancing the quality of care, patient safety, and healthcare management in obstetric services.