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Big Data, Artificial Intelligence Ease Healthcare Construction Symptoms

By Lisa Feeley, CSSMBB, Vice President, Transwestern

Big Data, Artificial Intelligence Ease Healthcare Construction SymptomsLisa Feeley, CSSMBB, Vice President, Transwestern

With billions of dollars wasted annually in the healthcare industry, hospital administrators are focusing on identifying ways to reduce waste, improve efficiency, and maximize value. As hospitals and healthcare provid­ers expand to bring services closer to the consumer, the development of new medical facilities presents an opportunity to embrace efficiency throughout the operation.

Many hospital systems will look for state-of-the-art technologies to enhance designing and constructing facilities that optimize patient outcomes and satisfaction, as well as staff productivity. One successful method is implementing “lean” design and construction that can be used in conjunction with big data and artificial intelligence. Both technologies will enhance the speed and accuracy of decision-making by hospital owners and the architecture, engineering, and construction industry.

The lean process can be applied to everything from the construction supply chain through delivery and project activation. However, the most crucial consideration is designing healthcare facilities that can be easily adapted for capacity, delivery of care, and future technology. Much of today’s waste is created when construction and development teams have not fully anticipated the need for future conversion. While still in their infancy, big data and artificial intelligence promise to have a significant impact on cutting construction costs and expediting the delivery of facilities.

Big data opens doors for detailed analysis of space utilization. 

Construction companies can analyze data on the project timeline and cost to enable hospital systems to make better decisions on how to build new facilities

Evaluating patient volume and traffic patterns enable hospital systems to make informed decisions on the number and types of rooms needed, reducing the likelihood that the facility would need to be renovated down the line to accommodate for changes in growth or demographics. Before even beginning construction, big data can be used to study the different orientations of a building and how it impacts lighting to help reduce energy consumption, an improvement that has an immediate impact on the bottom line.

The growth of the information we can cull from big data has led to increased use of prefabricated modules in healthcare facilities. Construction companies can analyze data on the project timeline and cost to enable hospital systems to make better decisions on how to build new facilities. They have historically designed a single module for identical spaces that are repeated throughout the facility, like restrooms. Now, however, they can also create a base module that can serve any medical use, including rehabilitation, tertiary care, level 1 trauma, or a suburban micro-hospital. Prefabricated modules can considerably increase the speed to market for a new project, and they also typically reduce the cost for extensive healthcare facilities.

Similarly, artificial intelligence can directly improve materials management, inventory, and procurement. Construction companies could potentially project inventory levels in real-time to direct procurement decisions, ensuring crews always have the right amount of supplies. It will sharpen the entire supply chain to keep projects on schedule and condense the construction timeline.

Robotics is already impacting the construction of healthcare facilities. Hospitals have recognized the need for robotics in back-of-house space by designing robot-ready corridors to allow bedside monitoring and delivery of supplies. Some construction companies are using robotics to build walls faster and more efficiently, cutting 20% to 30% from construction schedules and eliminating quality inconsistencies and assembly errors.

Regardless of how many robots are used, construction will always have human oversight, and hospital developers should view the project management team as a potential avenue to increase overall efficiency. Optimizing project management productivity is key to driving down project costs and schedules. Every hospital system has unique challenges, including facility locations, diverse patient populations, varying budgets, and different processes for decision making and approvals, making it challenging to form consistent methods of measuring the performance of healthcare construction operations. That said, there are certain best practices that hospital systems can adapt to foster a highly productive project management team.

Systems with smaller projects in the $1 million range should be able to assign a project manager roughly 20 projects, depending on the complexity, and this scales inversely as project size increases. For those in the $50 million range, a single manager would likely only be able to oversee two projects at a time effectively. For example, one hospital system has implemented a lean approach to its capital planning and contract proposal processes, allowing it to complete 144 projects among 16 project managers. Of those projects, 15% were more than $15 million, and 60% were less than $1 million. This highly productive team showcases that lean processes with explicit initiation, approval, and funding empower project managers to be more efficient than their counterparts.

Although healthcare construction is involved, big data and artificial intelligence have plenty of runways to continue treating inefficiencies and unnecessary waste throughout the construction process. The growth of these technologies will only further efforts to make healthcare more accessible to consumers by delivering high-quality healthcare facilities in a more cost-effective and timely manner.

Lisa Feeley is a Vice President at Transwestern Commercial Services. She specializes in project and construction management for healthcare facilities nationwide. She has more than 30 years of experience and is a Six Sigma Master Black Belt.

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