Faculty Members Receive AFP Innovation Fund Awards for Digital Projects
The AHSC AFP Innovation Fund competition is a collaboration between the Ministry of Health and Long-Term Care (MOHLTC) and the Ontario Medical Association (OMA). It provides short-term (one or two-year) seed funding to support innovative projects that will transform health-care delivery in Ontario.
According to the AHSC AFP Innovation Fund Framework and Guidelines, projects are particularly innovative if they:
- Have a definite potential to impact health care delivery
- Are implementable and contains realistic goals
- Have clear, measurable metrics for success
- Offer opportunities to translate new knowledge into medical practice
- Are transferable to other institutions, or regions, or the province.
Our Department is very proud to announce that seven of our faculty members were awarded this grant for their research projects (listed alphabetically by last name).
Dr. Sebastian Hobson, Dr. Eliane Shore and Dr. Mara Sobel
Project Title: Development of the Obstetric Patient Portal: Bridging the Gap in Patient Education
Project Summary: This project will develop and then assess the impact of an obstetrical patient education platform as an adjunct to clinical care in pregnancy. We have already developed two patient portals for Induction of Labour and Caesarean Section which are available on the TVASurg platform where they are open access and freely available to all patients. Our goal is to continue to develop the Obstetric Patient Portal which is a comprehensive and interactive patient education platform with text and 3D animations to optimize patient comprehension and satisfaction. Focus groups will inform each module’s specific content and comprehensive validity. This novel patient education platform aligns with the University of Toronto strategic plan by utilizing contemporary tools to expand patient understanding of their health.
Dr. Jamie Kroft and Dr. Adam Rosen (PGY3)
Project Title: Pregnancy outcomes following medical versus surgical treatment of ectopic pregnancy
Project Collaborators: Dr. Michael Ordon, Dr. Nir Melamed and Refik Saskin
Project Summary: Two percent of pregnancies implant outside of the uterus, most commonly in the fallopian tube. This condition, known as ectopic pregnancy, can be life threatening for women, accounting for six percent of maternal deaths. Treatment of ectopic pregnancy involves interruption of the pregnancy, either medically or surgically. Medical treatment of ectopic pregnancy is generally the preferred approach since it’s more conservative. We hypothesize the use of medical treatment can result in improved future fertility outcomes by preserving the fallopian tube. However, it is unclear if this could predispose a patient to greater complications/worsened reproductive outcomes arising from treatment failure and increased recurrence rate. We also don't know if women who come from different backgrounds, income groups or locations within Ontario are treated differently for this condition within the Province. This project will look at how women in Ontario are currently treated for ectopic pregnancy, and the fertility outcomes and complication rates associated with each treatment type. This information will help women make individualized decisions about their treatment based on their own values and will help health care resource planners address gaps in care.
Dr. Nucelio Lemos
Project Title: The Impact of Telemedicine on Management of Chronic Pelvic and Pudendal Pain: Lesson from the COVID Pandemic
Project Summary: Chronic pelvic and pudendal pain (CPPP) is a debilitating condition affecting about 20% of women of reproductive age. Despite its prevalence, it is a globally neglected health problem. In Ontario, there are only 3 CPPP management programs, and the wait times for patients can range from six months to two and a half years. Lengthy wait times for treatment lead to deterioration in patients’ health, functioning and quality of life. The COVID-19 pandemic has limited the access to outpatient care across all specialties. On the other hand, the pandemic led to the rapid adoption and adaption of Telemedicine by many healthcare providers. In our Chronic Pain Clinic, telemedicine has allowed us to see more patients than usual and clear the backlog of patients waiting to be seen. Our initial impression is that most of the patients can be diagnosed and receive an effective treatment plan without the need for an in person visit, while those who need an exam are seen much faster. The goal of this study is to determine if telemedicine is an effective way to diagnose and manage patients with CPPP, reduce wait times, and increase patient satisfaction and overall well-being.
Dr. Amanda Selk
Project Title: Check Your Vulva - A Patient Education and Virtual Vulva Care Pilot Project
Project Collaborators: Dr. Karen Wong, Dr. Evan Tannenbaum, Dr. Michelle Jacobson, Dr. Paulina Cybulska, and Dr. Trevor Champagne
Project Summary: Vulvar conditions are extremely common but are often under diagnosed and under treated. Vulvar disease education is lacking in residency training programs. There are very few specialized vulvar clinics in the world, and there are often long wait times to access these clinics. Some vulvar conditions cause irreversible anatomic scarring which can be prevented if the conditions are diagnosed and treated early. Many vulvar conditions affect quality of life and women often suffer in silence. Vulvar cancers are increasing but are often diagnosed late. The vulvar self exam (VSE) was originally developed to assist with earlier cancer detection. At Women's College Hospital (WCH) we plan to pilot an innovative patient education and virtual care project called "Check Your Vulva." The project will feature advertisements at the Bay Centre for Birth Control (BCBC) directing patients to web and mobile app based education explaining the VSE. Those who self-identify lesions will be able to send photos electronically to a nurse practitioner who can then electronically consult the vulvar clinic if needed. Patients with concerning lesions will be sent to a rapid referral clinic for possible biopsy and rapid diagnosis thus improving access to care.
Dr. Mara Sobel
Project Title: Digital pathology to provide rapid, automatic endometrial cancer diagnosis
Project Collaborators: Dr. Dafna Sussman and Dr. Gulisa Turashvili
Project Summary: Endometrial cancer, or cancer of the inner lining of the uterus, is the most common gynecologic cancer in Canadian women. It often presents with abnormal uterine bleeding (AUB) and has a high (>90%) 5-year survival rate when detected early. Women with AUB undergo an office endometrial biopsy, which has a high (95%) detection rate for endometrial cancer. A pathologist examines tissue sections from the biopsy under a microscope in order to accurately diagnose cancer and differentiate it from non-cancer cases. Visual assessment of biopsies is a time-consuming task. Time lags in pathology review can lead to delays in diagnosis as well as patient anxiety. A critical solution is through digital image processing using artificial intelligence (AI) algorithms to improve pathologists’ workflow, thereby improving patient care and lowering patient anxiety. In this project we will use AI to develop a novel automatic algorithm to expedite endometrial biopsy diagnosis. Development of this algorithm requires a large digital collection of endometrial biopsy images, which currently does not exist. As such, we will also develop a digital image repository, which will later be available for educational purposes.
Dr. Tim van Mieghem
Project Title: Artificial Intelligence assisted prenatal diagnosis of fetal anomalies in the first trimester of pregnancy: clinical validation and implementation
Project Summary: In Canada, at least 10,000 pregnancies are complicated by birth defects each year. Fetal anomalies are typically detected in the second trimester of pregnancy during a routine anatomy screening ultrasound scan. Advances in ultrasound technology have made it possible to detect many fetal anomalies earlier, in the first trimester of pregnancy. However, in contrast with many other countries, first trimester anatomy screening is currently not offered to low-risk pregnancies in Canada because most ultrasound units do not have the required time and expertise for this. Our goal is to develop an artificial intelligence algorithm that can detect fetal anomalies on routinely obtained first trimester ultrasound images. This algorithm will facilitate the work for sonographers and radiologists and improve the accuracy of fetal anomaly diagnoses in early pregnancy. This will lead to more ultrasound units offering first trimester anatomy screening and earlier diagnosis of anomalies. The latter will benefit patients by making genetic testing easier and will allow for earlier fetal treatment in case of fetal anomalies, but also prevent unnecessary anxiety and referrals when no anomalies are found.
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