Category: Company News

 

Artificial intelligence has quickly become one of the defining conversations in healthcare. 

From clinical documentation and diagnostic support to predictive analytics and virtual care, AI is already beginning to change how care is delivered. But an equally important question is whether our healthcare environments are ready to support what comes next.

This article is drawn from our presentation at the recent 2026 European Healthcare Design (EHD) Conference in London, UK, where we examined how AI will transform not only healthcare delivery, but also the planning, design and operation of healthcare facilities.

AI is taking off. Hospitals are still building the runway.

While the conversation around AI often centres on software, it should also centre on infrastructure. The next generation of hospitals will not simply contain AI—they will need to be designed to support it.

Healthcare has made significant progress in digitization. Many Canadian hospitals now have electronic medical records, connected medical devices and systems that continuously generate data.

Yet AI readiness is not about having vast amounts of data. It is about whether that data can support real decisions and improved workflows that support patient care.

Today, hospitals face three fundamental challenges.

First, although data is captured throughout the organization, systems still struggle to reliably share and reconcile information across departments, vendors and care settings.

Second, even when information does flow from system to system, it often fails to place the data within the clinical context to make a meaningful impact to  the right person, in the right place, at the right moment..

Finally, many organizations continue to treat digital systems as separate technologies rather than part of the clinical care delivery model  itself.

For clinicians, improving AI readiness has the potential to reduce cognitive burden, support safer decision-making and improve clinical outcomes.

For healthcare organizations, the impact of AI allows us to plan for Hospitals that are better able to absorb surges in demand, respond to crises and evolve as technology continues to advance. The opportunity is significant—but hospitals are still building the runway.

Understanding where AI is heading

Not every AI application places the same demands on healthcare infrastructure.

Today, language-based AI is the most mature. It excels at working with text, documents, coding and summarization, and many of these applications can operate effectively using cloud computing.

The next wave is multimodal AI, which combines text with images, audio, video, and data from sensors. These systems require more processing power, tighter integration across devices and increasingly responsive infrastructure.

Beyond that lies embodied AI—systems capable of perceiving and acting within the physical environment. These applications demand the highest levels of reliability, the lowest latency and carefully designed fail-safe systems.

As AI moves from language to rich sensory information and, ultimately, to action in the physical world, the infrastructure supporting it becomes increasingly important.

Where hospitals will feel AI first

The impact of AI will not be uniform across healthcare. Different clinical environments will adopt different capabilities based on their operational needs, clinical priorities and infrastructure requirements.

Emergency departments
Emergency departments are likely to experience some of the earliest operational benefits.

Rather than relying solely on standardized triage protocols, future AI systems may compare presenting symptoms against large clinical datasets to support triage, forecast waiting room pressures, anticipate bed demand and improve patient flow.

Preparing for that future begins with the triage area itself. Sensor-rich assessment spaces, stronger integration with emergency medical services and well-defined data governance strategies will all become increasingly important.

The takeaway is straightforward: AI readiness in emergency departments starts with the triage environment and the data pipelines surrounding it.

Surgery
Operating rooms are already among the most digitally advanced spaces in hospitals.

Today's robotic-assisted surgery enables highly precise, minimally invasive procedures. Looking ahead, AI has the potential to assist surgeons through real-time image analysis, anatomical recognition and decision support, helping improve accuracy while keeping clinicians firmly in control.

Unlike traditional robotic systems, AI-assisted surgery is designed to augment clinical decision-making rather than replace it.

Because these applications are highly sensitive to latency and reliability, they also have some of the most demanding infrastructure requirements. Low-latency networking, local processing and dependable data become essential design considerations.

Mental health
Behavioural health presents a different opportunity.

AI tools may help identify patterns associated with agitation, self-harm risk, or attempts to leave a care area unsafely (elopement) earlier than traditional monitoring methods. Combined with adaptive lighting and audio systems, these tools may support earlier intervention and more effective de-escalation.

However, we believe the greatest value will come from supporting staff—not from autonomous decision-making.

Planning considerations therefore extend beyond technology to include privacy, governance, appropriate use of cameras and microphones, and workflows that ensure information reaches caregivers when it is needed most.

Pediatrics
Many emerging pediatric applications focus on improving the patient experience.

Conversational companions, interactive projection systems and adaptive rehabilitation games may help reduce pain and anxiety, personalize education, and encourage participation in therapy by responding to a child's age, abilities and clinical needs.

These applications also introduce new planning considerations. Patient rooms may require additional digital endpoints—including tablets, speakers, projectors, cameras and microphones—to support increasingly interactive care environments.

Virtual care
AI is also extending care beyond hospital walls.

Predictive scheduling, automated triage, ambient documentation and continuous remote monitoring have the potential to reduce friction before appointments while identifying patient risks earlier between visits.

The technology itself is only part of the challenge.

Successful virtual care depends on reliable device onboarding, identity management, broadband connectivity, and seamless integration with electronic health records and clinical workflows. Sensors may be located in patients' homes, but care coordination and escalation pathways remain firmly connected to the hospital.

AI resides everywhere

One of the common misconceptions about AI is that it resides exclusively in the cloud.

In practice, where AI operates depends on the application.

Training large AI models requires enormous computing resources and will continue to occur in large data centres. Once trained, however, AI models can operate in many different environments.

Where AI "lands" is a choice driven by latency, uptime, data privacy and the criticality of care.

Some applications are well suited to cloud environments; for example, gaming consoles in pediatric treatment. Others require computing close to the point of care to deliver the speed and reliability clinical workflows demand. Still others will operate entirely within the walls of the hospital to maintain local control over performance and data―in our minds, surgery is far too critical to sit anywhere other than the hospital, in order to better control the latency and reliability of data.

Rather than relying on a single AI platform, hospitals will increasingly operate multiple AI systems working together across cloud, local and hybrid environments.

Planning hospitals for an AI-enabled future

As AI capabilities mature, the planning implications extend well beyond software.

Organizations considering on-premises AI will need to think differently about power, cooling and physical space.

Greater computing capacity increases electrical demand and backup power requirements. Heat generated by dense computing environments becomes a facility design issue rather than simply an IT issue, making technologies such as direct-to-chip liquid cooling increasingly important. Higher-density equipment may also influence structural planning and floor loading.

In other words, there is no one-size-fits-all approach to healthcare data centre design.

The right solution depends on the clinical applications being supported and the operational requirements they create.

Four principles for planning intelligent care environments

While no one can predict exactly how AI will evolve, these four planning principles can help healthcare organizations prepare for what comes next.

  • Design care spaces to generate data. AI depends on timely, reliable information. The physical environment should support high-quality data capture from the outset.
  • Treat digital systems as essential infrastructure. Reliable networks, sensors, computing capacity and data governance are becoming as fundamental to hospital performance as traditional building systems.
  • Protect capacity for change. AI capabilities will continue to evolve. Planning flexibility into today's facilities creates opportunities to adopt tomorrow's technologies without major disruption.
  • Plan for distributed intelligence. AI will not exist in a single location. Healthcare organizations should expect intelligence to operate across cloud, local and hybrid environments depending on clinical needs.

Ultimately, AI-ready infrastructure means more than installing new technology. It means creating hospitals with the digital resilience to deliver safe, effective care with AI, without AI, and during the transition between the two.

That is the opportunity before us—and one of the defining challenges for healthcare planning in the years ahead.

 Authors:

 
 

Megan Angus, RN, MBA, Lean, EDAC, Principal
Senior Vice President, Strategy and Digital Services | Vice President, Angus Connect

 
 

Daniel Tannous, P.Eng., ing.,
Senior Manager, Angus Connect

 
 

The World Architecture Festival has selected the CN Tower Lower Observation Level project as a finalist in its 'Interiors - Public Buildings' category.

We congratulate superkül and the project team for the honour of this international distinction. Widely recognized as one of architecture's premier international events, the World Architecture Festival celebrates outstanding design from around the world. A WAF shortlist places projects among the year's most notable architectural achievements. The awards ceremony will take place November 18 - 20, in Fort Lauderdale, Florida, USA. 

The CN Tower's Lower Observation Level was completed and unveiled in January 2026, as part of the attraction's 50th anniversary celebrations. The refurbished area comprises 10,600 square feet, including both indoor and outdoor viewing areas, a glass floor, stairwells, washrooms, and the SkyPod elevator lobby. Earlier this year, the project won an IES Toronto Section Award for Excellence in Lighting.

The Lower Observation Level work marks the first major upgrade to Level 2 since the Tower opened in 1976. HH Angus provided comprehensive mechanical, electrical, lighting, and communications engineering services as part of the transformation. You can read more about our scope of work here.

 

 
 

Angus Connect's ICAT/IMIT team is helping lead the charge in designing one of British Columbia's first 'smart hospital' facilities - the new Surrey hospital and BC Cancer Centre (NSHBCCC). 

Currently in design, the Fraser Health Authority’s next-generation healthcare facility represents a pivotal step toward fully connected, digitally enabled care environments in Canada.

Shaping the Smart Hospital Vision

Our approach integrates digital strategy, data-driven decision support, and clinical readiness from day one. Incorporating principles from the new CSA Z8005:24 – Special Requirements for Digital Infrastructure and Digital Health Care Technologies, the project team is embedding best practices in interoperability through systems integration design, extensive stakeholder engagement, and future-proof planning to ensure that digital systems enhance, rather than complicate, care delivery.

This facility will leverage technology not as an overlay but as an integrated layer of care — connecting patients, staff, and the building itself to improve safety, efficiency, and experience.

Technology Highlights

  • Infrastructure for Automated Guided Vehicles (AGVs): Planned integration of autonomous vehicles to move multiple material streams across the hospital, improving logistics efficiency and staff safety.
  • Wearable Bio-Tracking Devices: Continuous patient monitoring before and after procedures will enable faster clinical intervention and better outcomes.
  • Smart Operating Rooms: Featuring digital integration, disinfection lighting, multi-angle clinical cameras, and real-time remote collaboration for advanced training and tele-surgical support.
  • Telemedicine for Surgery and Trauma: Virtual surgical consults and remote specialist access will expand capacity and ensure timely intervention in critical situations.
  • Real-Time Location Tracking: Ultra-wideband (UWB) asset and staff tracking within one-metre accuracy will enhance workflow optimization and safety.

 A Response to Today’s Healthcare Challenges

As Canadian patients face long wait times — averaging 28.6 weeks between referral and treatment in 2025 [1] — the need for technology to extend access, enhance capacity, and personalize care has never been greater. While most Canadians still prefer in-person visits, many Canadians believe that virtual and digitally supported care can improve access to specialists and reduce delays [2].

The Fraser Health region—including Surrey Memorial Hospital, the largest acute-care site in the region with over 650 acute-care beds and the province’s busiest emergency department—continues to face immense pressure from rapid population growth, aging demographics, and limited inpatient capacity. The new Surrey hospital and BC Cancer Centre directly helps to address these pressures by creating a digitally inclusive, patient-centric model of care that enhances operational flow, improves visibility across the care continuum, and optimizes real-time use of available beds and resources.

Angus Connect Team Approach

Across the country, Angus Connect has built a reputation for bridging people, process, and technology to deliver operationally ready, data-driven environments. Our multidisciplinary team — including engineers, designers, BIM, clinicians, engineers, project managers, and change management— has guided more than a dozen of Canada’s largest healthcare capital projects. From integrating real-time patient flow systems to enabling digital command centres, our work demonstrates how thoughtful digital design translates directly into better patient outcomes and workforce resilience.

Looking Ahead

The new Surrey hospital and BC Cancer Centre will set a new benchmark for smart healthcare facilities in Canada — a fully electric, digitally equipped hospital where interoperability, automation, and human-centered design converge to transform care.

By embedding digital health planning into the foundation of capital design, Angus Connect is not only building infrastructure — we’re helping define the next generation of care delivery across Canada.

Authors:

 
 

Megan Angus, RN, MBA, Lean, EDAC, Principal
Senior Vice President, Strategy and Digital Services | Vice President, Angus Connect

 
 

Vishal Bhana, B.Eng., P.Eng., RCDD, CDCDP, Associate
Senior Manager, Angus Connect

 
 

Kyra McLellan, B.Eng., M.A.Sc., E.I.T
Senior Designer, Healthcare

 
 

References:

[1] [2] Moir, M., & Esmail, N. (2025). Waiting Your Turn: Wait Times for Health Care in Canada, 2025 Report. Fraser Institute. | Fraser Institute. https://www.fraserinstitute.org/studies/waiting-your-turn-wait-times-for-health-care-in-canada-2025

[3] Virtual care is real care: National poll shows Canadians are overwhelmingly satisfied with virtual health care. Canadian Medical Association. (2020, June 8). https://www.cma.ca/latest-stories/virtual-care-real-care-national-poll-shows-canadians-are-overwhelmingly-satisfied-virtual-health  

 
 
 

Infrastructure and building owners continue to face a familiar challenge: delivering increasingly complex projects within constrained budgets and schedules while meeting ever-higher expectations for performance, sustainability, quality, and stakeholder value.


Despite advances in technology and project management practices, cost overruns and schedule delays remain common. Traditional delivery methods, particularly Design-Bid-Build (DBB), often separate design decisions from construction expertise, making it difficult to manage risk, optimize value, and maintain cost certainty throughout the project lifecycle.

Over the past three decades, alternative delivery models such as Design-Build (DB), Design-Build-Finance-Maintain (DBFM), Alliance Contracting, Progressive Design-Build (PDB), and Integrated Project Delivery (IPD) have emerged to address these challenges. While each model has unique characteristics, many share a common principle: creating greater alignment among stakeholders through collaboration and early engagement.

One of the most powerful concepts to emerge from this evolution is Target Value Delivery (TVD).

TVD represents a fundamental shift in project delivery thinking. Rather than designing a project and then determining its cost, TVD establishes the project's value objectives and allowable cost at the outset and continuously validates design decisions against those constraints throughout the project lifecycle.

TVD was adapted for construction projects from Lean Product Development used in manufacturing. TVD is supported by the Lean Construction Institute. 


What Is Target Value Delivery?

Target Value Delivery is a Lean-based project delivery approach that focuses on maximizing value while maintaining alignment with cost and schedule objectives. Unlike traditional approaches, where estimating often follows design development, TVD integrates cost, schedule, scope, and value considerations from the earliest stages of project planning.

The objective is straightforward:

Design and deliver the project to meet the owner's value objectives within an agreed allowable cost and delivery timeline.

This approach requires continuous collaboration among owners, designers, constructors, suppliers, and operators throughout the project lifecycle.


Why Traditional Delivery Models Struggle

Traditional Design-Bid-Build delivery remains widely used across both public and private sectors. While it can be effective under the right circumstances, it brings with it several challenges:

  • Design and construction expertise are often separated.
  • Owners typically retain the majority of project risk.
  • Cost certainty is limited during early design phases.
  • Value engineering frequently occurs late in the process after significant design effort has already been invested.
  • Budget overruns and schedule extensions often result in redesign, scope reductions, or compromised project objectives.

In many cases, value engineering becomes a reactive exercise aimed at reducing cost rather than a proactive process focused on optimizing value.

TVD seeks to address these shortcomings by embedding cost and value considerations into decision-making from the very beginning.


The Three Cost Levels in TVD

A defining feature of TVD is the establishment of three interconnected cost benchmarks.

Allowable Cost

The Allowable Cost represents the maximum amount the owner can justify spending to achieve the project's business objectives and expected value. This cost is driven by the business case rather than by the design itself.

Expected Cost

The Expected Cost represents the anticipated cost of delivering the project based on current assumptions, market conditions, and available information. This cost reflects what the project would likely require if delivered using conventional methods and assumptions.

Target Cost

The Target Cost is the collaboratively developed cost objective established by the project team. It becomes the working cost target against which design and construction decisions are continuously evaluated.

The relationship between these three costs creates constructive tension within the project team. When the Expected Cost exceeds the Allowable Cost, the team must seek innovative solutions that preserve value while reducing cost.

This process occurs before major design commitments are made, reducing the need for late-stage redesign and traditional value engineering exercises.


Target Value Delivery Throughout the Project Lifecycle

  1. Business Case Development

Every project begins with a business case that defines the owner's vision, objectives, and desired outcomes.

Within a TVD environment, this phase includes:

  • Early feasibility analysis
  • Development of reliable cost models
  • Preliminary risk assessment
  • Early engagement of key stakeholders
  • Establishment of the Allowable Cost and Target Value

One of the most important differences from traditional delivery models is the involvement of construction and implementation expertise much earlier in the process.

  1. Validation Phase

Validation is one of the most critical phases of TVD.

During validation, the project team continuously assesses whether the proposed solution can achieve the owner's objectives within the established cost and schedule constraints. This phase includes repeated Go/No-Go decision points that allow stakeholders to evaluate project viability before significant resources are committed. Unlike traditional stage-gate, or end-of-phase reviews, validation in TVD is a continuous process rather than a one-time event.

  1. Design and Construction

Throughout design and construction, cost, schedule, and value are continually monitored and validated.

Design decisions are evaluated against their impact on:

  • Project value.
  • Cost performance.
  • Schedule performance.
  • Risk exposure.
  • Long-term operational objectives.

Continuous estimating becomes a critical management tool, allowing the team to identify potential deviations early and take corrective action before they become significant issues. The objective is not simply to reduce cost but to maximize value within agreed project constraints.

  1. Post-Project Evaluation

The TVD process continues beyond project completion.

Lessons learned, performance outcomes, cost data, and schedule performance should be captured and analyzed to improve future projects and strengthen organizational benchmarks. This continuous learning cycle is consistent with Lean principles and supports long-term organizational improvement.


Lean: The Foundation of Target Value Delivery

TVD cannot succeed without Lean thinking.

While TVD establishes the project's cost and value objectives, Lean provides the management system that enables project teams to achieve them. At its core, Lean seeks to maximize value while minimizing waste.

Within the context of project delivery, this means:

  • Optimizing the entire process rather than individual components.
  • Focusing on value generation for the owner and end users.
  • Eliminating activities that do not contribute value.
  • Improving workflow reliability.
  • Promoting transparency and collaboration.
  • Pursuing continuous improvement.

Lean transforms project teams from independent organizations pursuing individual objectives into a unified team focused on a shared outcome.


Conditions for Successful TVD Implementation

Based on experience across collaborative delivery models, several conditions consistently determine whether TVD succeeds or fails.

  1. Early Stakeholder Engagement. Owners, designers, constructors, suppliers, operators, and maintainers must be engaged as early as possible. The greatest opportunity to influence cost and value exists during the earliest project phases.
  2. Clear Definition of Value. Success depends on establishing a common understanding of what constitutes value. Different stakeholders often define value differently. Alignment must occur before major decisions are made.
  3. Reliable Cost Information. TVD relies on accurate and continuously updated cost information. Cost models must be transparent, credible, and supported by all stakeholders.
  4. Strong Owner Leadership. Owners must actively participate in decision-making and value definition. TVD is not a process that can be delegated entirely to consultants or contractors.
  5. Trust and Transparency. Collaboration requires trust. Open communication, transparent cost information, and shared problem-solving are essential to maintaining team alignment.
  6. Experienced Project Leadership. Project managers play a critical role in facilitating collaboration, managing stakeholder expectations, and maintaining focus on project objectives. Experience with Lean principles and collaborative delivery environments is often a significant contributor to project success.
  7. Continuous Validation. Project assumptions must be challenged and validated continuously. Frequent Go/No-Go reviews help identify risks early and prevent costly downstream impacts.
  8. Alignment of Commercial Structures. Contracts and commercial arrangements should support collaboration rather than encourage siloed behaviour. The most successful TVD projects align incentives around overall project performance rather than individual organizational outcomes.


Common Misconceptions About TVD

Several misconceptions continue to limit adoption of Target Value Delivery. It’s important to understand that:

  • TVD is not simply another form of value engineering.
  • It is not solely a cost-reduction exercise.
  • It is not a procurement model.
  • And it is not limited to Integrated Project Delivery projects.

Rather, TVD is a management philosophy and decision-making framework that can be applied across a range of collaborative delivery environments.

 
 
 

Lessons Learned

Monitoring and evaluating projects provides valuable insight that helps us improve future project delivery. Lessons learned are important for all delivery methods, but they are particularly critical in collaborative delivery models such as TVD, Design-Build-Finance-Maintain (DBFM), Alliance Contracting, and Progressive Design-Build (PDB). Based on recent project experience, several key practices consistently contribute to successful outcomes:

Team awareness
The better the team understands how the project is organized and how decisions are made, the more effectively they can contribute to achieving the target value, maintaining alignment with the allowable cost, and managing project risks.

Open and direct communication
 A defined communication channel should be established early in the process and shared by all stakeholders. This ensures transparency, supports timely decision-making, and minimizes the risk of misunderstandings or issues falling through the cracks.

Document control
Whether documents are being exchanged for review, coordination, approval, or formal submission, a clearly defined process and centralized document management system should be established. Designating a single point of control for document distribution helps ensure that information is handled consistently, routed appropriately, and maintained within the correct project records.

Risk management
A defining characteristic of collaborative delivery models is the redistribution or sharing of project risk among stakeholders. As a result, engineering teams often assume greater responsibility for managing and mitigating risks throughout the project lifecycle.

Effective risk management begins with the early identification of potential risks, regardless of their likelihood or potential impact. Establishing risk ownership, maintaining a comprehensive risk register, and implementing a process for regular monitoring and updating are essential practices.

Open issues log
Fast-track and TVD projects often require design to be advanced based on assumptions that may evolve as more information becomes available. This reality increases the importance of maintaining an active open issues log throughout the project lifecycle.

The open issues log should be managed alongside the risk register and regularly communicated to project stakeholders. Including open issues with design packages, when appropriate, helps ensure that all parties are fully aware of unresolved matters and the potential future adjustments that could affect project scope, cost, schedule, or performance.

Streamlining projects
Organizations managing multiple projects under similar delivery models can benefit significantly from standardizing processes and workflows across projects. Establishing consistent approaches from proposal development through project closeout promotes efficiency, improves knowledge transfer, and enables lessons learned to be applied in real time rather than only at project completion.

This continuous improvement mindset supports greater consistency, strengthens project governance, and creates opportunities to share successful practices across project teams. In our experience, this represents one of the most effective pathways to long-term success in collaborative project delivery.


Conclusion

Target Value Delivery represents a significant evolution in project delivery thinking.

Rather than accepting cost overruns and schedule extensions as inevitable outcomes, TVD challenges project teams to define value early, establish realistic cost constraints, and continuously validate decisions throughout the project lifecycle. When supported by Lean principles, strong leadership, transparent cost management, and genuine collaboration, TVD provides a practical framework for delivering better outcomes for owners, designers, constructors, and end users alike.

The ultimate objective is not simply to deliver projects at lower cost. It is to deliver the highest possible value within the constraints that matter most.

 
 
 
Zoomed in headshot of Mohamed Kamel with grey background.

Mohamed S. Kamel, ing., P.Eng., PMP 
Project Director & Senior Associate
HH Angus and Associates

 
 
 

CaGBC Webinar - HH Angus and ZGF Architects on BC's Zero- Carbon Hospital

Discover how a fully electric hospital in British Columbia is reducing carbon and advancing resilience, ecological restoration, and community health.

Join us for CaGBC’s webinar exploring the Cowichan District Hospital Replacement Project— Canada's first hospital to achieve Zero Carbon Building – Design Standard™ certification and a project targeting one of the country's most ambitious low-carbon healthcare outcomes.

HH Angus' Ryan Kennedy and Dave Abuza join Ayme Sharma (ZGF Architects) to share insights from a project that demonstrates what's possible when healthcare, sustainability and engineering come together from day one.

As the project's mechanical and electrical engineers, our team is working with the broader design and construction team to deliver a low-energy, zero-carbon solution for a next-generation healthcare facility targeting full electrification, while supporting exceptional patient care.

If you're involved in healthcare infrastructure, sustainability, or building decarbonization, this session is a must for practical insights on zero carbon building design.

Click below for CaGBC’s webinar registration page: https://www.cagbc.org/learning/attend-an-event/accelerating-to-zero/

Click here to read more about our scope of work on the project.