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Discovering role interaction models in the Emergency Room using Process Mining.
Alvarez, Camilo; Rojas, Eric; Arias, Michael; Munoz-Gama, Jorge; Sepúlveda, Marcos; Herskovic, Valeria; Capurro, Daniel.
Afiliação
  • Alvarez C; Computer Science Department, School of Engineering, Pontificia Universidad Católica de Chile, Chile. Electronic address: cealvarez@uc.cl.
  • Rojas E; Computer Science Department, School of Engineering, Pontificia Universidad Católica de Chile, Chile. Electronic address: eric.rojas@uc.cl.
  • Arias M; Computer Science Department, School of Engineering, Pontificia Universidad Católica de Chile, Chile. Electronic address: m.arias@uc.cl.
  • Munoz-Gama J; Computer Science Department, School of Engineering, Pontificia Universidad Católica de Chile, Chile. Electronic address: jmun@ing.puc.cl.
  • Sepúlveda M; Computer Science Department, School of Engineering, Pontificia Universidad Católica de Chile, Chile. Electronic address: marcos@ing.puc.cl.
  • Herskovic V; Computer Science Department, School of Engineering, Pontificia Universidad Católica de Chile, Chile. Electronic address: vherskov@ing.puc.cl.
  • Capurro D; Internal Medicine Department, School of Medicine, Pontificia Universidad Católica de Chile, Chile. Electronic address: dcapurro@med.puc.cl.
J Biomed Inform ; 78: 60-77, 2018 02.
Article em En | MEDLINE | ID: mdl-29289628
ABSTRACT

OBJECTIVES:

A coordinated collaboration among different healthcare professionals in Emergency Room (ER) processes is critical to promptly care for patients who arrive at the hospital in a delicate health condition, claiming for an immediate attention. The aims of this study are (i) to discover role interaction models in (ER) processes using process mining techniques; (ii) to understand how healthcare professionals are currently collaborating; and (iii) to provide useful knowledge that can help to improve ER processes.

METHODS:

A four step method based on process mining techniques is proposed. An ER process of a university hospital was considered as a case study, using 7160 episodes that contains specific ER episode attributes.

RESULTS:

Insights about how healthcare professionals collaborate in the ER was discovered, including the identification of a prevalent role interaction model along the major triage categories and specific role interaction models for different diagnoses. Also, common and exceptional professional interaction models were discovered at the role level.

CONCLUSIONS:

This study allows the discovery of role interaction models through the use of real-life clinical data and process mining techniques. Results show a useful way of providing relevant insights about how healthcare professionals collaborate, uncovering opportunities for process improvement.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Informática Médica / Pessoal de Saúde / Papel Profissional / Atenção à Saúde / Serviço Hospitalar de Emergência / Mineração de Dados Limite: Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Informática Médica / Pessoal de Saúde / Papel Profissional / Atenção à Saúde / Serviço Hospitalar de Emergência / Mineração de Dados Limite: Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article