But what if we could prevent these closures before they happen?<\/p>\n\n\n\n
That\u2019s the question driving Dr. Salimur Choudhury, a computer scientist at Queen\u2019s University and founder of the GOAL Lab (short for Global Optimization, Analytics, and Learning). His lab builds decision-making tools powered by algorithms, data, and AI, tools that could help healthcare administrator decide, in real time, how to deploy limited resources where they\u2019re needed most.<\/p>\n\n\n
![\"\"](\"https:\/\/cmblog.neuroscience.queensu.ca\/wp-content\/uploads\/2025\/07\/Dr.-Salimur-Choudhury.png\")
\u201cOne of my research priority areas is optimizing health care resources,\u201d he said. \u201cOver the past few years, we\u2019ve been developing data-intensive, data-driven methods to support health care policymakers.\u201d<\/p>\n\n\n\n
At its core, Choudhury\u2019s research addresses a deceptively simple question: how do we allocate scarce resources – physicians, supplies, or even transportation routes – in a way that supports real people in real time?<\/p>\n\n\n\n
Some of his most urgent work focuses on ER closures in Northern Ontario. With limited staff supporting a vast geographical area, hospitals in the north frequently shut their emergency departments on evenings and weekends. For patients, these closures can mean driving for hours to find help, often in hazardous winter conditions. \u201cWe\u2019re analyzing patterns in ER visits and studying which emergency rooms are closing and when,\u201d he explained. \u201cThe idea is to use data to guide decisions, to figure out when and where closures can be avoided.\u201d<\/p>\n\n\n\n
But the barriers to care in Northern communities go beyond hospital staffing. They also include the seasonal roads that connect them. Many remote areas rely on winter roads\u2014temporary routes built over frozen lakes and waterways \u2014that are only operational for a few weeks each year. Climate change is shortening these windows by causing warmer winters and unpredictable freeze-thaw cycles, cutting off critical links between patients and healthcare. Choudhury\u2019s lab is using geospatial and climate data to anticipate these risks. \u201cWe are combining satellite imagery and trying to analyze which winter roads are disappearing,\u201d he said, \u201cbecause if and when that road is closed, the ER will also close, and that may impact the service delivery.\u201d<\/p>\n\n\n
![\"\"](\"https:\/\/cmblog.neuroscience.queensu.ca\/wp-content\/uploads\/2025\/07\/winter-road.jpg\")
By identifying communities at risk of being stranded, his team aims to help decision-makers plan ahead, reallocating resources before patients are left without options. To make this relocation possible, his lab is building mathematical models that support regional coordination, enabling better use of travel nurses, shared staff pools, and dynamic scheduling, all grounded in patient and hospital data. While access to these data remains a challenge, Dr. Chourhury\u2019s team is painstakingly gathering what it can from public sources.<\/p>\n\n\n\n
But Choudhury isn\u2019t stopping at ERs. In another project, his team is helping reduce administrative burden in family medicine. \u201cIn family health teams, physicians often spend a lot of time filling out forms, but not all of them need to be completed by doctors,\u201d he said. \u201cWe\u2019re looking at how we can redistribute that work to other allied professionals.\u201d<\/p>\n\n\n\n
By analyzing health records from the Queen\u2019s Family Health Team and partnering with a start up company , the lab developed an AI-based autofill system for medical referral forms, saving time for doctors and potentially improving workflow across team-based care. \u201cThe time savings for physicians were significant,\u201d Choudhury said.<\/p>\n\n\n\n
These innovations point to a broader shift that Choudhury is pursuing \u2014 one where intelligent systems don\u2019t just offer recommendations, but take action to solve and prevent problems in real time. <\/p>\n\n\n\n
\n\u201cWhat I\u2019m envisioning is called decision intelligence,\u201d he explained, \u201cwhere systems don\u2019t just analyze data and generate algorithms but actually make the decisions themselves.\u201d<\/p>\n<\/blockquote>\n\n\n\n
This vision may sound futuristic, but his team is already working on it. In one project, they\u2019re building a tool that converts natural language (plain, human descriptions of a problem) into the mathematical equations needed to solve it. For example, someone might type out their scheduling or logistics challenge, and the algorithm would automatically generate an optimization model and code, ready to run.<\/p>\n\n\n\n
\u201cThe idea is that a user could describe their problem in natural language,\u201d he said, \u201cand the system would generate the equations and code needed to solve it.\u201d<\/p>\n\n\n\n
Ultimately, these tools are designed to help healthcare leaders and government agencies make faster, smarter and more equitable decisions, especially in communities where resources are stretched. But for research like this to drive real-world change, it has to reach the people in charge of policy and planning. That\u2019s why Choudhury is strategic about where he publishes his work.<\/p>\n\n\n\n
\u201cWhen you develop a particular methodology, some of it needs to be published in computer science journals,\u201d he said. \u201cBut we also need to reach the right audience, and healthcare policymakers may never read a standard computer science journal.\u201d<\/p>\n\n\n\n
To bridge this gap, Choudhury not only publishes in technical outlets, but he also seeks opportunities in health-sector venues where clinical leaders and system planners are more likely to engage. These opportunites include journals, conferences and collaborations with clinicians. By tailoring communications to this audience, Choudhury ensures his research doesn\u2019t just push the boundaries of algorithm design, but informs better care, smarter systems and more responsive policy.<\/p>\n\n\n\n
Despite the complexity of his work, Choudhury is focused on practical impact. He partners with hospitals, startups and government agencies, and trains the next generation of researchers in this field. And he continues to ask how novel algorithms can help to solve systemtic problems in healhcare.<\/p>\n\n\n\n
\u201cWe\u2019re trying to find small algorithmic approaches,\u201d he said, \u201cand connect those dots to make a meaningful difference.\u201d<\/p>\n\n\n\n
In a healthcare system buckling under pressure, these small things might just be the breakthroughs we need. But the significance of this work goes far beyond technical achievement. By designing systems that can allocate resources intelligently, deliver care more efficiently, and anticipate infrastructure-related challenges before they become crises, Choudhury\u2019s research lays the foundation for a healthcare system that is more equitable, accessible, and resilient \u2014 one that serves everyone, no matter their postal code.<\/p>\n\n\n\n
\n\n\n\n\n
- Rural Ontario Municipal Association. (2024). Fill the gaps: Bringing care closer to home in rural and northern Ontario<\/em>. https:\/\/www.roma.on.ca\/sites\/default\/files\/assets\/IMAGES\/Home\/ROMA%20Report%20-%20Fill%20the%20Gaps%20Closer%20to%20Home%20January%2021%202024%20FINAL%20Draft-Reduced.pdf<\/a><\/li>\n<\/ol>\n\n\n\n
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