skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Developing DELPHI expert consensus rules for a digital twin model of acute stroke care in the neuro critical care unit
Abstract Introduction Digital twins, a form of artificial intelligence, are virtual representations of the physical world. In the past 20 years, digital twins have been utilized to track wind turbines' operations, monitor spacecraft's status, and even create a model of the Earth for climate research. While digital twins hold much promise for the neurocritical care unit, the question remains on how to best establish the rules that govern these models. This model will expand on our group’s existing digital twin model for the treatment of sepsis. Methods The authors of this project collaborated to create a Direct Acyclic Graph (DAG) and an initial series of 20 DELPHI statements, each with six accompanying sub-statements that captured the pathophysiology surrounding the management of acute ischemic strokes in the practice of Neurocritical Care (NCC). Agreement from a panel of 18 experts in the field of NCC was collected through a 7-point Likert scale with consensus defined a-priori by ≥ 80% selection of a 6 (“agree”) or 7 (“strongly agree”). The endpoint of the study was defined as the completion of three separate rounds of DELPHI consensus. DELPHI statements that had met consensus would not be included in subsequent rounds of DELPHI consensus. The authors refined DELPHI statements that did not reach consensus with the guidance of de-identified expert comments for subsequent rounds of DELPHI. All DELPHI statements that reached consensus by the end of three rounds of DELPHI consensus would go on to be used to inform the construction of the digital twin model. Results After the completion of three rounds of DELPHI, 93 (77.5%) statements reached consensus, 11 (9.2%) statements were excluded, and 16 (13.3%) statements did not reach a consensus of the original 120 DELPHI statements. Conclusion This descriptive study demonstrates the use of the DELPHI process to generate consensus among experts and establish a set of rules for the development of a digital twin model for use in the neurologic ICU. Compared to associative models of AI, which develop rules based on finding associations in datasets, digital twin AI created by the DELPHI process are easily interpretable models based on a current understanding of underlying physiology.  more » « less
Award ID(s):
2123900
PAR ID:
10440643
Author(s) / Creator(s):
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more » ; ; ; ; ; « less
Date Published:
Journal Name:
BMC Neurology
Volume:
23
Issue:
1
ISSN:
1471-2377
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; ; (, Biomolecules and Biomedicine)
    Digital twin technology is a virtual depiction of a physical product and has been utilized in many fields. Digital twin patient model in healthcare is a virtual patient that provides opportunities to test the outcomes of various interventions virtually without subjecting an actual patient to possible harm. This can serve as a decision aid in the complex environment of the intensive care unit (ICU). Our objective is to develop consensus among a multidisciplinary expert panel on statements regarding respiratory pathophysiology contributing to respiratory failure in the medical ICU. We convened a panel of 34 international critical care experts. Our group modeled elements of respiratory failure pathophysiology using directed acyclic graphs (DAGs) and derived expert statements describing associated ICU clinical practices. The experts participated in three rounds of modified Delphi to gauge agreement on 78 final questions (13 statements with 6 substatements for each) using a Likert scale. A modified Delphi process achieved agreement for 62 of the final expert rule statements. Statements with the highest degree of agreement included the physiology, and management of airway obstruction decreasing alveolar ventilation and ventilation-perfusion matching. The lowest agreement statements involved the relationship between shock and hypoxemic respiratory failure due to heightened oxygen consumption and dead space. Our study proves the utility of a modified Delphi method to generate consensus to create expert rule statements for further development of a digital twin-patient model with acute respiratory failure. A substantial majority of expert rule statements used in the digital twin design align with expert knowledge of respiratory failure in critically ill patients. 
    more » « less
  2. ; ; ; ; ; ; ; ; ; ; et al (, Disaster Medicine and Public Health Preparedness)
    Abstract Background: A Mass Casualty Incident response (MCI) full scale exercise (FSEx) assures MCI first responder (FR) competencies. Simulation and serious gaming platforms (Simulation) have been considered to achieve and maintain FR competencies. The translational science (TS) T0 question was asked: how can FRs achieve similar MCI competencies as a FSEx through the use of MCI simulation exercises? Methods: T1 stage (Scoping Review): PRISMA-ScR was conducted to develop statements for the T2 stage modified Delphi (mD) study. 1320 reference titles and abstracts were reviewed with 215 full articles progressing for full review leading to 97 undergoing data extraction. T2 stage (mD study): Selected experts were presented with 27 statements derived from T1 data with instruction to rank each statement on a 7-point linear numeric scale, where 1 = disagree and 7 = agree. Consensus amongst experts was defined as a standard deviation ≤ 1.0. Results: After 3 mD rounds, 19 statements attained consensus and 8 did not attain consensus. Conclusions: MCI simulation exercises can be developed to achieve similar competencies as FSEx by incorporating the 19 statements that attained consensus through the TS stages of a scoping review (T1) and mD study (T2), and continuing to T3 implementation, and then T4 evaluation stages. 
    more » « less
  3. ; (, bioRxiv)
    Abstract Biology faculty have consensus-based guidelines based on Vision and Change principles about what to teach introductory biology majors. In contrast, faculty have not reached a consensus concerning the learning goals for introductory non-majors courses. Yet, more than 8 out of 10 undergraduates are not science majors. The goal of this study was to develop and evaluate learning objectives for non-majors introductory biology courses. We performed a modified-Delphi study of learning objectives (LOs) for non-majors biology. We engaged a total of 38 biology faculty experts from institutions across the US in three iterative rounds to identify, rate, discuss, and re-rate >300 LOs for non-majors biology courses. Faculty provided feedback to determine whether the LOs are critical for students to learn and if the LOs encompass what students need to learn about this issue, as well as if anything is missing. As a result of expert evaluation, 60.7% of LOs (164) were deemed critical. Experts also suggested 22 additional new LOs. 
    more » « less
  4. ; ; ; ; ; ; ; ; ; ; et al (, Frontiers in Medicine)
    BackgroundDigital twins are computerized patient replicas that allow clinical interventions testingin silicoto 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. MethodsA 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. ResultsMedian 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. ConclusionA digital twin application based on EHR clinical variables showed good usability and high acceptance for critical care education. 
    more » « less
  5. ; ; ; (, ACM)
    Digital Twin (DT) technology offers real-time monitoring, simulation, optimization, and precise forecasting. However, its theoretical framework and practical implementation, particularly in digital random controlled trials (RCT), remain underdeveloped, limiting its full potential. Therefore, we seek to develop an application of digital twins with the virtual reality using data from four longitudinal RCT in Massachusetts. As case studies, we create digital twins of two individuals from these RCT. This application of digital twins provides an avenue for a more personalized healthcare experience for patients, the enhancement of medical simulations, and a visualization for predictive analytics. In the future, we will move from virtual reality to extended reality with AI-generated digital twin models. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email