AI’s Impact on Healthcare Real Estate

The introduction of AI-enabled clinical protocols has significantly impacted the delivery of healthcare and clinical services. AI presents equally exciting opportunities for health systems’ real estate leaders.

Although venture capital investment in AI for real estate lags other industries (see Figure 1), AI can play a significant role in the delivery of facilities management and project management services within the healthcare industry.

Figure 1: VC Investments in Artificial Intelligence by Industry - Real Estate is Lagging

AI can help “real estate companies gain over 10% or more in net operating income through more efficient operating models, stronger customer experience, tenant retention, new revenue streams, and smarter asset selection,” according to a recent McKinsey article.

Health care real estate leaders seem well-positioned to leverage the power of AI, given the vast amount of data that flows into and out of facilities. And the timing could not be more advantageous, as labor shortages and capital constraints continue to put pressure on healthcare executives to find operational efficiencies. A significant amount of the workforce will leave the industry in the next five years: According to Zippia, by 2030, all Baby Boomers will be eligible to retire.

CBRE GWS Chief Digital and Technology Officer Kapil Lahoti observes that AI will continue to play an increasing role in real estate and healthcare facility management: “We must come up with solutions to get ahead of the labor problem. That's why I see AI becoming the omnipresent facility manager.”

Figure 2: Imagine AI, the Omnipresent Facilities Manager

AI: the Good, the Bad and the Data

The use of AI brings significant opportunities for improved data analytics and more efficient work processes. However, it also comes with challenges, such as data integrity, data privacy, implementation cost and increased need for highly skilled labor.

Data quality has become a key concern, according to Mike Denney, SVP, Chief Real Estate Officer at Providence Health & Services, who underscores the importance of first consolidating and homogenizing data. Denney emphasizes data standardization at Providence, which operates 52 hospitals and over 1,000 clinics across seven states. With a large portfolio spread across varying geographies and asset types, ensuring that the data is standardized is the first challenge to solve. Denney and his team are completing an initiative to consolidate disparate operations data across all service lines before expanding their AI integration beyond basic contract/document reviews and predictive staffing. According to Denney, “Once we have our all of our remaining data consolidated in a consistent format, we can deploy additional programs to leverage the benefits of utilizing AI across the system.”

To mitigate data privacy risks, health systems can implement strong encryption and access controls, use diligent vendor selection and stay updated on healthcare privacy regulations. Additionally, AI should be monitored to avoid perpetuating biases, prejudice and misinformation. Senior Director of Real Estate and Facilities at Mass General Brigham, Jay Phillips states, “We ensure we work with datasets that are free of these bias and prejudices. It's a very important piece and a prerequisite for the adoption of AI for us.”

A clear strategy and roadmap for adoption will ease the process by identifying areas where AI can bring value. Small-scale pilots can test AI’s feasibility and effectiveness, provide staff training and education opportunities and engage stakeholders to foster a culture of understanding, acceptance and buy-in.

A challenge facing many healthcare executives is distinguishing AI’s real potential and the hype. Providence’s Chief Data Officer and Group Vice President Mark Premo relies on two key principles: “First is to educate health system leadership with a minimum necessary understanding so they are able to spot real opportunities for AI applications. Given the reality of how busy hospital executives are, we should not assume they understand or are paying attention to the state of AI in healthcare.”

Premo’s second principle is “very similar to approaching any form of technology. Focus on the problem to be solved. It could be an administrative problem, a clinical problem or a facility problem. And as part of the problem-solving process, AI can be viewed simply as another tool available to help solve these problems. But not every problem is an AI problem so we need to be smart about when to use AI.” For Providence, Premo notes that “as we add AI to the problem-solving mix, we often engage a partner who has already solved a similar problem. We then collaborate on potential solutions which may involve an AI application. This is often an iterative and experimental process as we close in on a solution.”

AI and Healthcare’s Built Environment

Once potential challenges have been addressed, artificial intelligence can positively impact healthcare real estate management services, including predictive maintenance, energy management, security, space optimization, enhanced cleaning, asset management and communication.

Predictive Maintenance

AI supports facility upkeep through predictive maintenance. AI can predict when equipment might fail or require maintenance by analyzing data from various sources, such as equipment sensors, maintenance records and historical data.

This allows facility managers to proactively schedule maintenance tasks, reduce downtime and optimize the lifespan of their equipment. It can also streamline the work order process. Lahoti notes that “there are many times when you have duplicate work orders. They get logged multiple times and sometimes get dispatched multiple times. AI can make sure we remove duplicates and provide one work order for each task.”

Predictive maintenance allows facilities to preemptively address potential problems, saving time and money.

Energy Management

AI can analyze energy consumption data and suggest ways to make buildings more energy efficient. This not only reduces costs but also lowers health systems’ carbon footprints. Sample tasks include the following:

• Energy Monitoring and Analytics. Collect and analyze real-time data from energy meters, HVAC systems, lighting systems and other energy-consuming equipment. This helps in identifying energy-usage patterns, detecting anomalies and providing actionable insights to optimize energy consumption.
• Building Automation. Control and optimize the operation of HVAC systems, lighting and other energy-consuming devices based on real-time occupancy, weather conditions and other factors. This ensures that energy is used efficiently, preventing unnecessary consumption, reducing energy costs and supporting grid stability.
• Energy Efficiency Recommendations. Analyze data and provide recommendations for energy-saving measures—like upgrading equipment, optimizing schedules or implementing renewable energy sources—to help healthcare facilities make informed decisions to improve their energy consumption.

Security

AI-based security systems can include video surveillance, access control measures, threat detection and emergency response to provide a higher level of security.

• Video Surveillance. Monitor live or recorded video feeds to detect and alert security personnel about suspicious activities, unauthorized access or potential threats. This can prevent incidents or improve response time.
• Access Control. Use facial recognition, biometric authentication or behavior analysis to verify the identity of individuals, preventing unauthorized access to restricted areas.
• Threat Detection. Use data from various sensors like motion detectors, temperature sensors, and sound detectors to identify potential threats such as fires, leaks or abnormal behavior. Early detection enables prompt response and mitigation of risks, safeguarding healthcare providers and patients.
• Emergency Response. Monitor emergency calls, dispatching resources and providing real-time guidance to security personnel during critical situations, which improves response time and coordination.

Space Optimization

AI can analyze how space is used in a facility and suggest design improvements, leading to more efficient space use and reducing costs.

• Occupancy Monitoring. Track the occupancy of different spaces within a healthcare facility in real-time. This data can identify underutilized exam rooms or overcrowded spaces, allowing healthcare providers to optimize the allocation of resources and adjust space configurations accordingly.
• Workflow Optimization. Analyze data on staff and patient movement and interactions to identify bottlenecks or workflow inefficiencies. By optimizing the flow of people and resources, AI streamlines operations, improves productivity and can lead to improved design of clinical spaces.
• Predictive Analytics. Predict future space requirements using historical data on space utilization, user behavior and trends. This can inform the overall portfolio strategy and helps healthcare systems plan for future needs, such as expansion, reconfiguration or downsizing. Mass General Brigham’s Phillips says that his team “can take some of the analytical data we have for real estate transactions and market data and bring it to the next level. We can use AI to help us make better decisions in real time.” He cites examples such as market studies and patient attachment analytics to ensure that they “build the right facilities of the right type in the right locations and that are not duplicative.”
• Room Booking and Scheduling. Perhaps one of the easier functions to implement for healthcare systems, AI-powered systems can automate and optimize the booking and scheduling of exam rooms. This ensures efficient utilization of available space, reduces wait times and improves the patient experience.

Enhanced Cleaning

In the era of COVID-19 and other pandemic-level illnesses, AI technology can help healthcare facilities to enhance cleaning and disinfection, track cleaning frequency and ensure compliance with health and safety guidelines.

Cleaning Schedule Optimization

AI algorithms can analyze data on facility usage and foot traffic to optimize the cleaning schedule and allocate resources efficiently to ensure that high-traffic areas receive the appropriate level of cleaning.

Predictive Maintenance of Cleaning Equipment

AI can analyze sensors in cleaning equipment to predict potential failures or maintenance needs. This allows facility managers to proactively schedule maintenance tasks, ensuring that the equipment is in good working condition and minimizing downtime.

Robotic Cleaning

AI-powered robots can perform automated cleaning tasks, such as vacuuming, mopping or scrubbing floors, freeing human staff for other tasks. These robots can navigate the facility autonomously, avoiding obstacles and efficiently covering large areas and at off-peak times that are most convenient and effective.

Smart Waste Management

AI-powered waste management systems can monitor trash levels in bins and optimize collection routes. This prevents overflowing while reducing carbon footprint by eliminating unnecessary pickups.

Asset Management

AI can track and manage assets in real-time, providing accurate inventory data and reducing the risk of loss or theft.

Communication

AI-powered chatbots can handle common queries from employees or visitors, providing instant responses and freeing up human staff for more complex tasks. Communications can also be personalized and specific to a patient’s inquiries, assisting with triage and symptom assessment or providing medication reminders. Chatbots can also reduce wait times and improve access to healthcare information, improving the patient experience.

From predictive maintenance and energy management to space optimization and enhanced cleaning, AI offers a range of applications that can drive efficiency, cost savings and better outcomes. However, challenges such as data integrity, privacy concerns and the need for skilled personnel must be carefully addressed to ensure successful implementation. With thoughtful planning and strategic adoption, healthcare facilities can use AI to transform their operations and deliver exceptional patient care.

Written with the assistance of CBRE’s Ellis AI and modified by the author.