RESUMEN
Data Science emerged as a new cross-disciplinary discipline at the intersection of statistics, computer science, and expertise in a specific domain, such as health and biology. The data science field, alongside other data-related professions, is continuously evolving. We conducted a study examining tasks assigned to first-year internship students pursuing a Master's degree in Health Data Science, exploring the missions, technologies employed and skills required, and internship alignment with students' training through semi-structured interviews with 32 participants. Three quarters of the students were placed in teams within the public sector. Among these entities, there were 11 hospitals and 12 universities. Although the majority of students did their internship as part of a methodological team, they often had a healthcare professional on their team. Nearly half of the missions involved descriptive analysis, followed by 9 missions focused on etiology or prediction and 8 missions on implementing a data warehouse. The majority of students had to perform data management and produce graphs, while only half conducted statistical analysis. The findings highlighted that data management remains a major challenge, and it should be taken into consideration when designing training programs. In future, it remains to determine whether this trend will continue with second-year students or if, with experience, they are more often assigned statistical analyses.
Asunto(s)
Ciencia de los Datos , Ciencia de los Datos/educación , Internado y Residencia , Humanos , Francia , Universidades , Curriculum , Informática Médica/educación , Educación de Postgrado , Entrevistas como AsuntoRESUMEN
Intensive care units (ICUs) provide care for critical patients at high risk of morbidity and mortality, and require continuous monitoring of clinical, biological and, imaging parameters. Collaborative ventures have enabled the emergence of large open access databases for the secondary use of Electronic Health Records (EHRs). The objective of this work was to evaluate the availability of scripts and datasets in publications based on ICU open-access databases. We included 910 original articles based on four ICU open-access databases (Amsterdam University Medical Centers Database, eICU Collaborative Research Database, High time resolution ICU dataset, and Medical Information Mart for Intensive Care). The majority of the studies did not provide their data management scripts (n=839, 92.9%), neither the analysis script (n=843, 93.4%) in the article. Attempts to contact the 845 corresponding authors in question resulted in 89.11% (n=753) of our e-mail requests going unanswered over a two-month period. We received 51 automated messages (55.43%) indicating that emails have not been delivered, while 6 messages (6.52%) redirected to alternative email addresses. Only 20 corresponding authors (18.18%) answered, finally providing the requested materials. Despite scientific journals recommendations to share materials, our study unveils the absence of crucial components for the replication of studies by other research teams.