By Matt Skoufalos
In the do-more-with-less era of healthcare, sustainability has transitioned from an aspirational public relations tool into a financial strategy that means even more to the bottom line as it does to marketing messaging. As broad a concept as the business cases to which it’s applied, the first steps towards sustainability must necessarily employ efficiency in the act of driving at system efficiency.
In the medical imaging space, both kinds of improvements are sought, as study volumes and patient wait times continue to increase amid a staffing shortfall. Addressing the totality of these issues to yield the most significant impact requires innovation and practicality, as decision-makers must select the variables that can yield the greatest amount of change before acting upon them.
“You can push the ceiling on innovation, but you have to raise the floor if you want to move the needle in the field,” said Vibhas Deshpande, vice president of sustainability innovation and strategic research at Siemens Healthineers Americas.
For the manufacturers of medical imaging devices, increasing equipment sustainability starts with contemplating the entire life cycle of a product, from its component materials to its end-of-life removal from service. Identifying the biggest impact of its carbon footprint can start with assessment of how raw materials are sourced, and in what quantities; the process by which those materials are transformed into devices or their component parts; and how the final products are delivered to customers.
Once a device reaches the end of its useful life, there’s additional considerations to be made about how it’s retired, refurbished, repurposed, or upgraded in the field, which can stretch the useful length of the resource well into a decade and a half or longer.
“The actual product stays operational for a long period of time,” Deshpande said. “Then you come to end-of-life, and that’s when the materials can go to recycling.”
On most consumption timelines, medical imaging devices make their heaviest impact during the 10-plus years of their useful life because they require significant amounts of energy to operate, and derive the most value for their purchasers by operating steadily, if not continuously.
“This is the biggest bucket we need to focus on,” Deshpande said. “We are doing what we can in our factories with new energy-efficient technologies, and new system designs, but use-phase energy consumption depends on utilization patterns during a scanner’s lifetime”
Among the improvements that manufacturers seek to drive in device efficiency are performance functions – such as the capacity of a device to be switched into an economy or low-power mode, and the efficiency with which a device can enter or exit such modes – followed by onsite utilization. In that sense, Deshpande said, improvements aren’t always driven by a strict reduction in energy use as much as by efficiently generating the desired clinical outcomes. Facilities can improve their resource efficiency by addressing everything from wait times to ease of scheduling to patient access.
“I always like to think of it as an efficiency metric,” Deshpande said. “If I only scanned 10 patients in a 24-hour period, it’s one thing. If I increase that by 10 patients in that same period, I use marginally more electricity but generate far more clinical outcomes.”
“It’s not only the product and product features, but machines have gotten so advanced that patient exams are not as long as they used to be,” he said. “There’s a lot of technological advancement: the longer the exam, the more energy it will use.”
“But utilization is also driven by how much time it takes to swap patients,” Deshpande said. “How long is the machine sitting idle, consuming energy that is not being used to drive an output? How is the patient workflow through the imaging suite? There are several ways you can speed up this entire process, thereby increasing your utilization rate.”
“Even in designing all these things, are you taking into account the technologist experience?” Deshpande asked. “What staffing models do you need for maximum patient workflow?”
Many of these improvements can be retrofitted to an existing operational structure, “but when you’re building a new facility, that’s the best time to do this,” Deshpande said. Such moments often offer points of entry into efforts that can wring efficiency improvements from the least likely of areas. As much as workflow can be enhanced by artificial intelligence (AI)-powered computing technologies, seemingly lower-tech questions – like the width of a hallway as it relates to rotating a patient table – also can have a significant impact.
Deshpande points to such a collaborative project between the Northwestern Medicine health system and Siemens Healthineers, where decision-makers conceptualized a new medical imaging facility by creating a digital twin of the space and simulating the patient experience there before fitting out the physical space.
“In the digital world, you can easily change, and add one more tech, one more table; close a wall off, and say, ‘Did this relieve my bottleneck?’” Deshpande said. “All of this operational optimization in the digital world before you start building the facility saves enormous costs downstream.”
“The environment in which an imaging device is located has an impact on utilization, so facilities should be designed to maximize patient throughput.”
Dr. Michael Markl, vice chair for research in the department of radiology at Northwestern University Feinberg School of Medicine, said the digital twin modeling experience helped visualize every detail of the patient journey virtually before fitting out the space. Those efforts are expected to reduce per-patient energy consumption by some 30 percent.
Through the comprehensive digital twin process, “you could really mimic or simulate things with the patients, staffing, techs, nurses, physicians,” Markl said, “and that, to me, is the real-world scenario.”
“Making small tweaks to the protocols to make them more efficient, we can increase access to the facility, and then that efficiency itself is more understood,” he said. “That simulation was done before the facility even opened, and that informed the construction of the facility.”
The facility has been operational for two months, and Markl’s team is in the process of gathering data to validate its predictions, having specifically purchased MRI equipment that can measure the energy consumption to track its impact on patient flow, and compare it across its other facilities.
Philosophically, the impact of simply taking those measurements – called “the observer effect” in physics – alters the outcome of how systems operate. Practically, it could also help communicate the significance of efficiency and sustainability to imaging facility staff, much in the same way that power consumption readouts on other appliances does.
“Your MRI tech and your assistant is supposed to care about the patient, and not really how much energy is being consumed,” Markl said. “If the scanner said where you’re at with the protocol you’ve selected, and how it changes if you drop something out, I think that would create a lot of awareness.”
Driving greater efficiency improvements through broader awareness includes acknowledging that healthcare is itself, as an industry, one of the leading carbon emitters on the planet.
“If healthcare was a country, it would be fourth or fifth in global emissions,” Markl said. “Radiology owns a large chunk of that emissions because we run and operate imaging equipment that consumes a lot of energy.”
By modality, the biggest energy consumer is MRI, Markl said; operating one MR machine generates the power consumption equivalent of 25 single-family households; scaled up, the imaging infrastructure of a facility like Northwestern’s equates to powering a small village. Simply powering down the devices when they’re not in use, or switching to a low-power option, would cut that consumption by a quarter to a third, but this is often not done out of convenience, or necessity to conduct an imaging study on an emergency basis, he said.
“The other option is just running the system more efficiently,” Markl said. “Can you optimize the scan protocol to make it more efficient? If you could shorten the scan, the power consumption would be lower. Then, can you minimize idle time between patients?”
Beyond facility and institutional efficiencies, Markl supports the expansion of MR life cycles through component and system refurbishment programs, which not only save money, but help keep systems in service longer, which has a downstream effect on patient access.
“That’s a good incentive for the organization or the vendors,” he said.
Markl also spoke about the less-contemplated notion of improving sustainability efforts by patient education efforts that would increase awareness about imaging procedures.
“If you’re getting an MRI, you want the MRI because you want to know what’s going on,” he said. “Nobody really talks to the patient about it. A lot of the conversations have been between the vendors and the societies, and the stakeholders and patients are not as involved as they could be.”
Dr. Susie Yi Huang, a radiologist at Mass General Hospital and associate professor at Harvard Medical School, supports the variety of efforts undertaken system-wide “to try to find common ground for people to understand what sustainability means” in the medical imaging space.
“Many people, especially in this generation, are extremely cognizant of the environmental impact of medical imaging technology,” Huang said. “High-efficiency MRI – getting scan slots to be shorter – also speaks to radiology across the board. As medical demand grows with our aging population, our need to provide timely and quality care with our patients really has come into focus.”
In a healthcare industry that’s broadly tasked to wring as much value as possible from every process, environmental benefits typically are discussed secondarily to economic incentives. Yet Huang said that her examinations of the topic have illustrated the greater degrees of operational freedom energy consumption mitigation strategies derive from simply scheduling and scanning patients more efficiently.
“In addition to improving revenue by doing more scans per day, you may be able to show improvement in energy efficiency,” she said. “Here at Mass General, we’re embarking to get all of our scan slots down to 20 minutes in the next year.”
To get there, the hospital is thinking through both physical and virtual improvements to its operations. This includes AI-optimized image acquisition and reconstruction methods, which Huang said “allow us to scan faster with more robust processes than we had immediately.” Meanwhile, on the reporting side, AI-powered computing processes help synthesize results through large-language models embedded in dictation software. Such models can also be used to summarize reports, which also helps save time in the interpretation and delivery of study results.
At Assembly Row, a mixed-use development just outside of downtown Boston, Mass General is working through some of its top-to-bottom efficiency analyses in an ambulatory imaging setting designed to hit that 20-minute study window.
By setting up three identical 3T Siemens MRI systems in sequence, Huang’s team could prep one patient while another was being scanned, and wheel the next patient in while the previous patient finished up. Leveraging these identical configurations allowed staff to catch up on time at a facility-wide level, with the aim of showing cost savings by virtue of the revenue increase that patient throughput improvements generated. Power meters installed on the systems helped show the path of energy consumption at every step of the most common outpatient imaging studies, quantified it, and compared that consumption against a control facility operating four MRI systems on a single-scanner model.
“We showed that we could reduce turnaround times from seven to 10 minutes down to three to five minutes,” Huang said, “and when you aggregate that over multiple exams and patients, you can eke out more scan slots.”
“That shows the opportunities that cost savings can actually bring about energy savings,” she said. “We were doing the same patient volumes with the three scanners [at Assembly Row] as compared to the four at the control. It is a bit more resource intensive, but you are gaining in terms of efficiency.”
Demonstration projects like the Assembly Row ambulatory center or the Northwestern digital twin power consumption modeling study illustrate how collaborative approaches to medical imaging sustainability can yield the greatest results. Institutional partnerships underscore the shared responsibility of tackling the issue as well as how they can yield dividends enjoyed by stakeholders across the board.
“The moment we think of this as someone else’s problem, we’re not going to solve the problem,” Deshpande said. “In all my interactions with institutions that own our equipment, I never had the sense that they were suggesting [that sustainability] was only the manufacturer’s responsibility.”
“This is one space where, if we do not work together, we are very unlikely to succeed,” he said. “We all need to be working closely if we want to move the needle. If we say it’s someone else’s responsibility, we will not make meaningful progress.”
