Harvard Catalyst Program for Diversity Inclusion (PFDI) Faculty Fellowship
Junior Faculty Support Opportunities
2021-2023 Faculty Fellowship To Be Awarded
Extended Submission Deadline: Friday, March 5, 2021
February 26, 2021
Harvard Catalyst Program for Diversity Inclusion (PFDI) Faculty Fellowship (formerly Harvard Catalyst Program for Faculty Development and Diversity Inclusion (PFDD) Faculty Fellowship) is a two-year, non-degree Faculty Fellowship Program for Harvard junior faculty designed to address faculty need for additional support to conduct clinical and/or translational research and to free junior faculty from clinical and teaching demands at a key point in their career development. Each Faculty Fellow will receive $100,000 over a two-year period to support their scholarly efforts. Faculty Fellows are required to devote appropriate time toward the development of their academic career, to meet regularly with their mentors, and to present at the annual Minority Health Policy Meeting. For more information about Catalyst see: http://catalyst.harvard.edu
Doctoral degree (e.g. MD, PhD, DO, DMD, DDS). Harvard appointment at the level of instructor or assistant professor. Applications will also be considered from clinical or research fellows who are in the process of appointment/promotion to instructor and/or assistant professor at Harvard. U.S. Citizenship or Permanent Residency.
2020-2022 PFDI Faculty Fellows
2020-2021 HARVARD CATALYST PROGRAM FOR DIVERSITY INCLUSION (PFDI) FACULTY FELLOWSHIP RECIPIENT
Hermioni Amonoo, MD, MPP, Assistant Professor of Psychiatry at Brigham and Women’s Hospital
Department Chair: David A. Silbersweig, MD, Stanley Cobb Professor of Psychiatry, Brigham and Women’s Hospital
Mentor: Jeffery C. Huffman, MD, Professor of Psychiatry, Massachusetts General Hospital
Project Title: Development of a positive psychology intervention to improve mood and health related quality of life in patients post hematopoietic stem cell transplantation- Proof of Concept Trial
Project Description: Allogeneic hematopoietic stem cell transplantation (HSCT) is a potentially curative treatment for some hematologic malignancies. Notwithstanding the promising nature, the transplantation process and recovery is intensive and fraught with potential life-threatening complications during recovery. Hence, HSCT recipients have a high burden of distress and quality of life (QOL) deficits. Most efforts to achieve optimal psychological weli-being in this population have targeted the reduction of distress (e.g., depression). However, positive psychological well-being ( e.g., optimism), can buffer against this distress and has been prospectively associated with improved QOL and survival in this population. Positive psychological interventions (PPis), which utilize systematic activities (e.g., recalling positive life events) to promote psychological well-being, have consistently and durably enhanced psychological health and QOL in medical settings, but have never been used in HSCT patients. Given the need for new programs to promote well-being and recovery after HSCT, the proposed project will develop and test a novel PPI in this population to fill this unmet need. I will develop the PATH (Positive psychology for Allogeneic Transplantation of Hematopoietic stem cells) intervention via a review of the literature and application of theoretical frameworks, then test its acceptability (via quantitative participant ratings and qualitative feedback at exit interviews) in a one-arm proof-of-concept trial (N= l0; Aim 1). Next, I will test its feasibility and preliminary efficacy on health outcomes in a pilot randomized controlled trial (N=60; Aim 2). In sum, the HMS-PFDD Award will prepare me to become an independent investigator and leader who develops novel evidence-based supportive oncology interventions.
2020-2022 HARVARD CATALYST PROGRAM FOR DIVERSITY INCLUSION (PFDI) FACULTY FELLOWSHIP RECIPIENT
Randy Miles, MD, PhD, Assistant Professor of Radiology at Massachusetts General Hospital
Department Chair and Mentor: Constance D. Lehman, MD, PhD, Professor of Radiology, Massachusetts General Hospital
Project Title: External Validation and Clinical Assessment of a Deep Learning Risk Prediction Model for Mammography Interpretation
Project Description: While recent studies evaluating artificial intelligence (AI) demonstrate promising results, it is imperative that AI tools are thoroughly assessed prior to widespread use to avoid past mistakes with implementation of conventional computer assisted detection (CAD), which led to increased healthcare costs despite only marginal benefit. Current AI studies largely share the following that may limit maximal clinical utility: 1) requirements for large, well-curated datasets to train and validate algorithms, which may not be representative of real-time clinical imaging data 2) validation using internal data sets only, limiting generalizability to diverse patient populations, equipment manufacturers, and/or clinical settings, and 3) lack of evidence on how AI tools can be implemented to maximize clinical impact. We have previously published on our AI model using deep learning techniques, developed from institutional data using 223,109 consecutive screening mammograms performed in 66,661 women from January 1, 2009 to December 31, 2016, that predicts breast cancer risk, based on a woman’s current mammogram. Our model obtained an AUC of 0.82(95%CI:0.80,0.85). Personalized risk prediction scores determined by our model can potentially be used by radiologists to improve radiologist’s interpretative performance, if provided at the time of mammography interpretation. To inform clinical implementation of our model, we aim to 1) validate our AI model utilizing imaging data from a large, diverse external dataset and 2) quantitatively determine the effect of our model on radiologist interpretative performance. Together, this work has the potential to positively impact breast cancer screening by providing a framework for clinical implementation of our model to improve radiologist performance.
Biography: Randy C. Miles MD, MPH, is an Assistant Professor in the Department of Radiology at Massachusetts General Hospital. He is originally from Green Level, NC. He completed his B.S. in Chemistry from Hampton University graduating Summa Cum Laude with Honors. Subsequently, he obtained his MD from Mayo Clinic College of Medicine, where he co-led health missions to underserved regions in Haiti and the Dominican Republic. His international public service led him to obtain a MPH from Chan Harvard School of Public Health, where he was awarded the Zuckerman fellowship. During this time, he learned about racial disparities in breast cancer mortality and discovered his passion for improving breast cancer care in traditionally underserved groups. His clinical practice as a board- certified radiologist, specializing in breast imaging, includes image interpretation of digital mammography, digital breast tomosynthesis (“3D mammography”), breast ultrasound (including automated breast ultrasound (ABUS)), and breast MRI. He also performs image- guided procedures including breast biopsies, aspirations, wire/seed localization, and lymphoscintigraphy. His clinical, research, and public health efforts center around improving breast cancer outcomes primarily through 1) identifying barriers to breast cancer screening, 2) creating patient-centered initiatives to improve access to breast imaging services, and 3) examining how to improve delivery of high quality, guideline- concordant breast care for all patients using artificial intelligence. Within the breast imaging division, he has a leadership role in community health, where he has led research efforts focused on reduction of breast cancer screening barriers, appropriate utilization of supplemental screening tools, and assessment of online patient educational materials for factors related to health literacy. In addition, he currently works with international hospitals to improve all facets of care in breast imaging related to physician training, workflow optimization, and patient experience.
To read about PFDI Faculty Fellows Alumni, please click on the name.