Process mining is the research domain focusing on the development of innovative methods
to gather insights from event logs. It has been used for various use cases within the …

Process mining applies robust methodologies using data mining and machine learning for
pattern recognition, using models that represent the process flow identified by the sequence …

Background Accumulated electronic data from a wide variety of clinical settings has been
processed using a range of informatics methods to determine the sequence of care activities …

In the literature, there are three major concepts used to model resilience and safety
performance:(i) integrated resilience engineering (IRE),(ii) work motivational factors,(iii) …

La ciencia de datos es una disciplina dedicada a analizar y procesar datos con el propósito
de convertirlos en conocimiento accionable. En el área de la salud, la ciencia de datos ha …

In the mental health sector, Psychological Therapies face numerous challenges including
ambiguities over the client and service factors that are linked to unfavourable outcomes …

Objective The purpose of this study is to evaluate the effectiveness of hospital appraisals,
specifically the Performance Appraisal for Tertiary Public Hospitals (PATPH), and to …

THE HEALTHCARE SYSTEM in Latin America (LATAM) has made significant improvements
in the last few decades. Nevertheless, it still faces significant challenges, including poor …

Rapid ethnography and data mining approaches have been used individually to study
clinical workflows, but have seldom been used together to overcome the limitations inherent …

In the COVID-19 context, hospitals across the globe endeavour to manage the
unprecedented flow of patients. Challenges are related to the unexpected increase in …