Through the following Experimental Outreach Projects, the PMO team aims to augment the output of the Department by building stronger, multidisciplinary links across the University of Ottawa community.

Working with current University of Ottawa students, either through the Faculty of Engineering’s Makerlab or through Software Engineering Capstone projects, provides an opportunity for the DFM to continue to innovate in new areas through reciprocal learning arrangements, while the DFM Dragon’s Den challenge provides an opportunity to work with Family Medicine professionals on solutions that will address challenges in the primary care field. Through these projects, the DFM is committed to being an equal partner in developing new solutions and maximizing opportunities for change.

Undergraduate exam portal interface with question and multiple-choice answers

UG Exam Database Project

Medical students studying within the University of Ottawa’s Department of Family Medicine are currently responsible for satisfactorily completing exams every 12-weeks during their academic calendar. These exams are administered by the Undergraduate team within the Department of Family Medicine using exams developed and stored within an Excel spreadsheet. This spreadsheet uses carefully developed calculations within the spreadsheet to maintain student data and exam submissions. In order to make this exam process more efficient and secure, the UG Exam Database project aims to develop an accessible, password-protected exam database that would enable the Undergraduate Director and Admin to sort, filter and create exams using a built-in search engine. Through the development of this new Database project, special attention will be given to maintaining historical exam data and analysis. This project aims to develop a secure database that allows its admin users the ability to select exam questions using filters like date and question topic.  

The UG Exam Database project will be undertaken by a group of 4th year University of Ottawa students who will be collaborating with Department of Family Medicine staff as part of their Capstone project. Work on this project will begin in January 2023 and will be ongoing under the direction of our Education team.

Graphic of a city simulation game with detailed urban layout

SimCity Ottawa Project

Inspired by the popular life simulation video game franchise The Sims, the SimCity Ottawa project is a game developed to simulate life as a family physician and presents the player with options that require them to balance the competing demands of work and life. This educational game was developed in partnership with Department of Family Medicine leaders as a Capstone project by a team of University of Ottawa engineering students. In the Sim City Ottawa game, players are asked to set parameters for their life at the beginning of the game: will they be practicing in a clinic, emergency room, hospital coverage, specialization and what will their personal life look like? Following this, players will be asked to select 4 core values that will either positively or negatively affect their Sim as the player makes choices and moves through the game. The overall educational purpose of this game is to help players understand work/life balance and help them reflect on the cumulative effects of everyday decisions.  

Work on the SimCity Ottawa project began in 2022 and will continue into 2023 with a new team of undergraduate students taking over the development of the SimCity Ottawa game. under the direction of Dr. Kheira Jolin-Dahel and Dr. Jonah Marek.

Illustration of a patient and medical professional in a consultation setting.

Addressing the Unattached Patient Project

The National Capital Region is approaching 100k or 10% of the population that cannot find a primary care physician. While there is the Provincial portal to add your name to the list, unfortunately, this results in extremely long wait times. At the end of it all, patients looking for doctors' resort to Google and search in expanding concentric circles from their home address in the hopes of finding doctors accepting new patients. To compound this problem, many doctors are approaching retirement age, with some accelerating their retirement due to the stresses of COVID. However, due to the complexity of some practice plans and the financial model in the province, the retiring doctors are finding it challenging to locate a doctor to take over their practice. This additional difficulty will only exacerbate the problem.

The Department of Family Medicine continues to crowdsource an innovative solution that helps address this critical need and advance the discipline of family medicine.

In doing so we have and continue to develop several applications (See CHAT application project below) that could allow more doctors to practice and see more patients through a combination of remote or telemedicine and new technologies.

Screenshot of a chat application interface with a conversation bubble with people in the middle.

CHAT (Continuity Health Attachment Technology) Application

In an effort to address the significant challenge of matching patients with primary care physicians, we have developed the CHAT application. CHAT is an innovative health information technology system serving to map patients regionally to a provider based on both patient and provider preferences. As pitched by the winning team at the Department of Family Medicine’s inaugural Dragon’s Den, the CHAT app has been designed to ensure that all Canadian residents who want a Primary Care Physician have access to one. As primary care is increasingly evolving towards a patient-centered approach, the app pays close attention to personalized detail for providing a best-match attune to patient needs and preferences. Allowing the patient to make the match promotes autonomy to choose who provides their care and breaks down some of the existing barriers and health disparities because PCPs express a greater disinterest in accepting patients with high needs, including chronically ill patients and seniors.

Illustration of two healthcare professionals with a growth chart and medical icons

Resident Intervention

Considering the ever-changing nature of educational institutions, it will be critical for teaching staff to anticipate and address problems before they arise. This project proposes a systematic strategy that will identify medical residents in need of intervention as early as possible. Using Machine Learning, Deep Learning, and Natural Language Processing (NLP) algorithms, the aim is to simplify processes by automating the identification of such occurrences, enabling more immediate intervention and support for residents.