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Sarah Hallen

Biographic Data

ID9115182
NAMESarah Hallen
GIVEN NAMESSarah
FAMILY NAMEHallen
SIGNATUREHALLEN S
AFFILIATIONSMaine Medical Center
ORCID0000-0002-9890-9532
VERIFIEDYes
TOTAL WORKS3
TOTAL CITATIONS0
WORKS AS AUTHOR3
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2015
LATEST PUBLICATION YEAR2024
H-INDEX0
  • Creating Optimal Clinical Learning Environments Through Interprofessional Bedside Rounding Models

    Open Access•Sarah Hallen, Melissa I Zelaya et al.•ARTICLE•Academic Medicine•2024

    The Interprofessional Partnership to Advance Care and Education (iPACE) model was developed and implemented at Maine Medical Center in 2017 as part of the Accreditation Council for Graduate Medical Education’s Pursuing Excellence in Clinical Learning Environments (CLE) demonstration project. The model is based on the belief that, in optimal CLEs, residents are trained in team-based, interprofessional collaborative care and use clinical care exper…

  • Interprofessional bedside rounding improves quality of feedback to resident physicians

    Lesley B Gordon, Melissa Zelaya-Floyd et al.•ARTICLE•Medical Teacher•2022

    Purpose Obtaining high quality feedback in residency education is challenging, in part due to limited opportunities for faculty observation of authentic clinical work. This study reviewed the impact of interprofessional bedside rounds (‘iPACETM’) on the length and quality of faculty narrative evaluations of residents as compared to usual inpatient teaching rounds.Methods Narrative comments from faculty evaluations of Internal Medicine (IM) reside…

  • Physicians' perceptions of the value of prognostic models

    Open Access•Sarah A M Hallen, Sarah Hallen et al.•ARTICLE•Health Expectations•2015

    BACKGROUND: The communication of prognosis in end-of-life (EOL) care is a challenging task that is limited by prognostic uncertainty and physicians' lack of confidence in their prognostic estimates. Clinical prediction models (CPMs) are increasingly common evidence-based tools that may mitigate these problems and facilitate the communication and use of prognostic information in EOL care; however, little is known about physicians' perceptions of t…

No prominent works on this page.

  • Physicians' perceptions of the value of prognostic models

    Open Access•Sarah A M Hallen, Sarah Hallen et al.•ARTICLE•Health Expectations•2015

    BACKGROUND: The communication of prognosis in end-of-life (EOL) care is a challenging task that is limited by prognostic uncertainty and physicians' lack of confidence in their prognostic estimates. Clinical prediction models (CPMs) are increasingly common evidence-based tools that may mitigate these problems and facilitate the communication and use of prognostic information in EOL care; however, little is known about physicians' perceptions of t…

  • Interprofessional bedside rounding improves quality of feedback to resident physicians

    Lesley B Gordon, Melissa Zelaya-Floyd et al.•ARTICLE•Medical Teacher•2022

    Purpose Obtaining high quality feedback in residency education is challenging, in part due to limited opportunities for faculty observation of authentic clinical work. This study reviewed the impact of interprofessional bedside rounds (‘iPACETM’) on the length and quality of faculty narrative evaluations of residents as compared to usual inpatient teaching rounds.Methods Narrative comments from faculty evaluations of Internal Medicine (IM) reside…

  • Creating Optimal Clinical Learning Environments Through Interprofessional Bedside Rounding Models

    Open Access•Sarah Hallen, Melissa I Zelaya et al.•ARTICLE•Academic Medicine•2024

    The Interprofessional Partnership to Advance Care and Education (iPACE) model was developed and implemented at Maine Medical Center in 2017 as part of the Accreditation Council for Graduate Medical Education’s Pursuing Excellence in Clinical Learning Environments (CLE) demonstration project. The model is based on the belief that, in optimal CLEs, residents are trained in team-based, interprofessional collaborative care and use clinical care exper…

Medicine (3 works) · Psychology (3 works) · Computer Science (2 works) · Interprofessional Education and Collaboration (2 works) · Medical education (2 works) · Rounding (2 works) · Chemistry (1 work) · Clinical Reasoning and Diagnostic Skills (1 work) · Confidence interval (1 work) · Data science (1 work)

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