Causal evidence in health decision making: methodological approaches of causal inference and health decision science

Development and usability testing of a patient digital twin for critical care education: a mixed methods study

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.