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Development and usability testing of a patient digital twin for critical care education: a mixed methods study.
Rovati, Lucrezia; Gary, Phillip J; Cubro, Edin; Dong, Yue; Kilickaya, Oguz; Schulte, Phillip J; Zhong, Xiang; Wörster, Malin; Kelm, Diana J; Gajic, Ognjen; Niven, Alexander S; Lal, Amos.
Afiliación
  • Rovati L; Department of Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, United States.
  • Gary PJ; School of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy.
  • Cubro E; Department of Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, United States.
  • Dong Y; Department of Information Technology, Mayo Clinic, Rochester, MN, United States.
  • Kilickaya O; Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN, United States.
  • Schulte PJ; Department of Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, United States.
  • Zhong X; Department of Quantitative Health Sciences, Division of Clinical Trials and Biostatistics, Mayo Clinic, Rochester, MN, United States.
  • Wörster M; Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL, United States.
  • Kelm DJ; Center for Anesthesiology and Intensive Care Medicine, Department of Anesthesiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Gajic O; Department of Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, United States.
  • Niven AS; Department of Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, United States.
  • Lal A; Department of Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, United States.
Front Med (Lausanne) ; 10: 1336897, 2023.
Article en En | MEDLINE | ID: mdl-38274456
ABSTRACT

Background:

Digital twins are computerized patient replicas that allow clinical interventions testing in silico to minimize preventable patient harm. Our group has developed a novel application software utilizing a digital twin patient model based on electronic health record (EHR) variables to simulate clinical trajectories during the initial 6 h of critical illness. This study aimed to assess the usability, workload, and acceptance of the digital twin application as an educational tool in critical care.

Methods:

A mixed methods study was conducted during seven user testing sessions of the digital twin application with thirty-five first-year internal medicine residents. Qualitative data were collected using a think-aloud and semi-structured interview format, while quantitative measurements included the System Usability Scale (SUS), NASA Task Load Index (NASA-TLX), and a short survey.

Results:

Median SUS scores and NASA-TLX were 70 (IQR 62.5-82.5) and 29.2 (IQR 22.5-34.2), consistent with good software usability and low to moderate workload, respectively. Residents expressed interest in using the digital twin application for ICU rotations and identified five themes for software improvement clinical fidelity, interface organization, learning experience, serious gaming, and implementation strategies.

Conclusion:

A digital twin application based on EHR clinical variables showed good usability and high acceptance for critical care education.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Qualitative_research Idioma: En Revista: Front Med (Lausanne) Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Qualitative_research Idioma: En Revista: Front Med (Lausanne) Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza