RESUMEN
INTRODUCTION: In the health care area, tuition is an essential part to provide the instrument that proves the graduates have acquired the necessary skills in their specialties. OBJECTIVE: Evaluation of the improvement in quality of resources for residents after standardized digital training program with rubrics. METHODS: Prospective observational study of first year medical residents in seven medical specialties in four different training centers. Five dimensions were considered to scale the quality of medical resident research: Validation of rubric in investigation methodology topics for each block in b-learning mode; initial and ending evaluation; colloquium investigation rubric; results of final investigation; satisfaction survey of 360 degrees. The instruments were validated using the delphi method with a minimum agreement of 0.8. We considered global values greater than 80 points as good quality. RESULTS: 85 medical residents participated and obtained a final average of 80.62 (±9.59), and the satisfaction of the course was qualified as excellent/good in 82.5%. A positive relation was observed between the scope of the evaluation and the level of satisfaction. Mean quality score for the course was good. There is no relationship between the research experience of the students and the final average r = 0.123 (p = 0.291). CONCLUSIONS: The implementation of research seminars in b-learning mode results in improving the education program for health residents after a training program with a rubric system and their acquiring research skills, and, as a consequence, the final product also showed better quality, even when the student did not have any experience in a scientific publication.
RESUMEN
BACKGROUND: Patient safety is a priority issue in health systems, due to the damage costs, institutional weakening, lack of credibility, and frustration on those who committed an error that resulted in an adverse event. There is no standardized instrument for recording, reporting, and analyzing sentinel or adverse events (AE) in primary care. Our aim was to design and validate a surveillance system for recording sentinel events, adverse events and near miss incidents in primary care. METHODS: We made a review of systems for recording and reporting adverse events in primary care. Then, we proposed an instrument to record these events, and register faults in the structure and process, in primary health care units in the Instituto Mexicano del Seguro Social. RESULTS: We showed VENCER-MF format to 35 subjects. Out of them, 100% identified a failure in care process, 90% recorded a sentinel event, 85% identified the cause of this event, 75% of them suggested some measures for avoiding the recurrence of adverse events. We used a Cronbach's alpha of 0.6, p=0.03. CONCLUSIONS: The instrument VENCER-MF has a good consistency for the identification of adverse events.
Introducción: la seguridad del paciente es un tema prioritario en los sistemas de salud por el gasto que genera, el desgaste institucional, la falta de credibilidad y la frustración del personal que comete los eventos adversos. No existe un instrumento estandarizado y sistemático para registrar, reportar y analizar los eventos adversos en unidades de atención primaria. El objetivo fue validar un sistema de vigilancia para el registro de eventos centinelas, adversos y cuasi fallas en atención primaria. Métodos: se revisaron sistemas de registro y notificación de eventos adversos en atención primaria. Asimismo, se diseñó una propuesta de instrumento para el registro en unidades de atención primaria en el Instituto Mexicano del Seguro Social que integrara fallas en la estructura y en el proceso. Resultados: se le presentó el caso del formato VENCER-MF a 35 sujetos. El 100 % identificó una falla en el proceso de atención médica, 90 % registró un evento centinela, 85 % identificó el origen de este y el 75 % sugirió medidas para evitar la recurrencia de eventos adversos. Se obtuvo un alfa de Cronbach de 0.6, con una p = 0.03. Conclusión: el instrumento VENCER-MF tiene una consistencia buena para la identificación de eventos adversos.
