The SIDM Diagnostic Fellowship has been an excellent experience. The exposure and mentorship that we have received from experts in the field has been invaluable. SIDM staff are dedicated to developing the next generation of researchers, and their enthusiasm is contagious.

Najlla Nassery, MD, MPH

The 2023-2024 Fellows in Diagnostic Excellence
  • Anna Costello, MD

    Pediatric Rheumatology Fellow
    Children's Hospital of Philadelphia

    Fellowship Project

    Anna will attempt to better understand the factors that result in diagnostic delay in patients with Juvenile Idiopathic Arthritis. She hopes this research will guide quality improvement efforts to enable access to rheumatology services for appropriate patients and educational efforts to improve the timely recognition of JIA by non-rheumatologic clinicians.

  • Jessica Dreicer, MD

    Assistant Professor of Medicine
    University of Virginia School of Medicine

    Fellowship Project

    Jessica's project will focus on Deepening our understanding about the relationship between diagnostic and prognostic reasoning and use this knowledge to improve prognostic decision making.

  • Vadim Dukhanin, MD, MHS

    Assistant Scientist
    Johns Hopkins Bloomberg School of Public Health
    Baltimore, MD

    Fellowship Project

    Identify and document strengths, weakness, opportunities, and threats (SWOT) to implementing solutions to diagnostic disparities in routine healthcare delivery. Moving from documenting diagnostic disparities to widescale sustainable implementation of solutions requires closing critical gaps in our understanding of barriers and facilitators to such implementation. Findings of SWOT to implementing diagnostic disparities solutions would inform interested parties on potential recommendations and action steps and areas for alliances and collaborations.

  • Neha Bansal Etherington, MD, FACP

    Board Certified Internists, Clinical Assistant Professor

    Fellowship Project

    Dr. Etherington project focuses on curriculum development and assessment, particularly in the areas of clinical reasoning and clinical uncertainty. She aims to develop and evaluate a curriculum on communication of diagnostic uncertainty with the goals of improved communication of diagnostic uncertainty to patients and inclusion of patients as a part of the diagnostic team.

  • Jenny Sloane, MS, PhD

    Cognitive Psychologist, Health Services Research Fellow
    Center for Innovations in Quality, Effectiveness, and Safety
    Baylor College of Medicine

    Fellowship Project

    Dr. Sloane seeks to gain a better understanding of the diagnostic journey of patients with “diagnostically challenging conditions”, such as celiac disease. The ultimate goal of this research is to develop, test, and validate electronic trigger(s) to proactively identify patients who have a high likelihood of having certain diagnostically challenging conditions.

  • Stephen Smith, MD

    Assistant Professor
    Staff Head, Neck & Endocrine
    University of Toronto Department of Laboratory Medicine & Pathobiology

    Fellowship Project

    Inattention blindness is a known and described phenomenon when humans fail to perceive an unexpected observation - in plain sight without visual deficits or obscurations, as a result of lack of attention. Surgical pathologists rely on visual evaluation of tissues for diagnosis: the focus of this project is to discern whether surgical pathologists may experience inattentional blindness when either (1) prompted by clinical history contrary to obvious histologic findings; or (2) required to assert a diagnosis in a time-sensitive period (limited timing to review).

    We will utilize digital imaging to manipulate digital histologic slides, variably prompting pathologists with both accurate and inaccurate contexts, as well as adjusting the time period allowed for histologic evaluation before opinion, in order to "induce" this phenomenon.

  • Justine Staal, MSC, PhDC

    PhD-student and Teacher in Academic Skills
    Erasmus MC

    Fellowship Project

    Popular media like to report that artificial intelligence (AI) might soon replace human clinicians, though reality is that we are far from ready to broadly implement such algorithms in clinical practice. Important barriers remain that prevent successful human-AI collaboration, such our limited understanding of how clinical reasoning can best be supported by AI and a lack of trust in artificial intelligence. With this project, we will set out to identify minimal necessary characteristics to 1) support and improve clinicians’ diagnostic process and 2) establish trust in AI, which will lead to the development of recommendations for optimal conditions for human-AI collaboration.

  • Alberta Tran, PhD, RN

    Senior Research Scientist
    MedStar Health Research Institute and MedStar Institute for Quality and Safety
    Hartford “Age-Friendly” Fellow

    Fellowship Project

    Dr. Tran seeks to understand and leverage opportunities to better engage nurses, who make up the largest component of the healthcare workforce, in diagnostic improvement efforts for the older adult population. Her project aims to 1) identify examples of nurses' contributions to diagnostic safety in older adults and 2) co-design a nurse-led diagnostic safety checklist to improve diagnostic communication between older adults, their families/caregivers, and healthcare team members in hospital settings.

  • Yuxin "Daisy" Zhu, PhD

    Assistant Professor
    Johns Hopkins Armstrong Institute for Patient Safety and Quality
    Department Neurology
    Department of Biostatistics

    Fellowship Project

    Develop prediction algorithm to quantify misdiagnosis-related harm using hospital-level data without data sharing. The algorithm will be developed using state or national EHR or claim data, and will address the issue of return visits “crossing-over” to different hospitals.