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Artificial Intelligence, Big Data, and Healthcare Design

An aging population and a rise in chronic conditions such as diabetes are expected to lead to a higher demand for all types of healthcare services in upcoming decades. As healthcare continues to be one of the fastest-growing industries worldwide, there will also be an increasing demand for knowledgeable healthcare designers. In the U.S. there is a definitive need to replace aging 1970s-era hospitals, to expand the available medical facilities to care for the aging baby-boom generation, and to make new medical technologies more widely available. This has led to costing upward of $200 billion for new healthcare facilities are being rapidly constructed across the country in the last five years (Fails Management Institute, 2017). These new hospitals are likely to remain in place for decades, and it is vital that they are well-designed to account for the most current evidence-based standards in medical care.


This once-in-a-lifetime construction boom provides an opportunity to rethink hospital design, and to consider how better designs can contribute to improved patient outcomes and staff experiences. Just as contemporary medicine has moved toward evidence-based approaches in which clinical choices are informed by rigorous research, healthcare design today is increasingly guided by empirical studies on the effectiveness of hospitals’ physical environments. A growing body of evidence indicates that the design of medical facilities plays an important role in the success of patient treatment, the quality of patient–staff interactions, and the cost-effectiveness of healthcare.

During the last fifteen years the evidence-based-design approach has made significant inroads in the healthcare design industry. However, there is still something of a lack of rigorous post-occupancy-evaluation studies of healthcare facilities, when compared to studies of other types of buildings. Despite the well-document benefits of post-occupancy studies for hospital owners, design firms, and patients, the move toward evidence-based design in healthcare has been hampered by the inertia of the industry and a lack of well-trained researchers. Issues such as disputes over who should bear the cost of empirical studies, the difficulty of gaining IRB approval for data collection, and the duration and complexity of these studies have contributed to the slow adoption of evidence-based standards.

Most existing post-occupancy design studies in hospital settings involve limited quantitative data, mostly involving surveys of patients and staff members alongside a few environmental measurements such as lighting and noise levels. In the current technological age we can do better than that. The question that motivates this research, therefore, is how can we make use of cutting-edge data-gathering technology to better evaluate the effectiveness of hospital designs?

The goal of this research is to analyze the applicability of various cutting-edge data technologies for post-occupancy design studies in hospital settings. The researchers hypothesize that by using new approaches, such as automated data-collecting devices, can make a wealth of new information available for healthcare design researchers. This will allow for more in-depth analysis of design effectiveness and better resource optimization in hospital construction and operations.​


In the current project, the primary objective is to create a set of sensors that can be installed during the last phase of hospital construction, or that can be added by hospital managers after occupancy. The sensors will collect large-scale, anonymous data on the following measurements:


1) Patients’ sleep patterns.

2) Walking/circulation patterns of patients, visitors, and staff members.

3) Light and noise levels in patient rooms.

4) Airborne dust levels.

5) Patient falls or mobility problems.

6) Use of windows and curtains/blinds.

7) Medical errors by nurses.

Oakville Trafalgar Memorial Hospital, Image Credit: Parkin Architects Limited 

Credit to: Design & Augmented Intelligence Lab 

Research Team: Dr. Kalantari (PI), Robin Snell, Dr. Gnawali 

Industry Partner: Parkin Architects Limited

Year: Since 2017 

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