At its best, the health care system is a finely-tuned machine. Seasoned doctors, thoughtful nurses, and diligent administrative staff work together smoothly, prioritizing patient outcomes and operational efficiency, keeping safety and wellness as their highest goal.
Yet despite the hard work each of these professionals puts into their jobs, the demands of modern health care too often outpace the tools that medical workers have been given. When combined with persistent workforce shortages that are particularly pronounced in remote and underserved areas, it becomes increasingly clear that the best efforts of medical workers nationwide cannot balance out the rising administrative and operational complexities health care workers confront every day.
The latest symplr State of Healthcare Supply Chain Survey, conducted in February, confirms this. Respondents sounded the alarm on two critical fronts: margin pressures and the perennial struggle with staffing and resource allocation. Among the nearly 100 supply chain leaders surveyed, 63% earmarked cost savings as their organization’s top priority for this year, highlighting the urgent need for streamlined operations amidst tightening budgets. Meanwhile, 32% said that their supply chain teams have yet to rebound to pre-pandemic staffing levels, underscoring the persistent battle to adequately equip health care systems for the challenges ahead.
Other studies back up the concerns voiced in the survey, making it clear that it’s not just one part of the health care system that faces such challenges. For example, the 2023 NSI National Health Care Retention & RN Staffing Report paints a stark picture of the workforce crisis gripping the industry, with over three-quarters of hospitals facing nurse vacancy rates exceeding 10%. These shortages not only strain existing staff but also imperil patient care, compounding organizational hurdles.
These challenges do not have to be permanently debilitating to the health care industry. The expanded use of artificial intelligence in the workplace is one way that we can work to improve patient outcomes and avoid health care worker burnout. Companies that integrate AI into their software will be able to ensure that health care systems can deploy talent wisely, allowing them to focus on patient care first and foremost.
How can AI be helpful to health care workers?
If you ask the average person about what artificial intelligence means to them, they will immediately jump to generative AI programs like ChatGPT. In reality, AI is a far broader category of software that simulates intuition to handle complex tasks. Through machine learning and AI that is deployed smartly, intentionally, and safely, we can streamline processes and create efficiencies that empower health care workers to focus their time where it is most needed—caring for patients.
This potential is reflected in the areas of optimism that health care supply chain leaders have for the future of their industry. In February, they indicated that “leveraging technology to transform manual processes and accelerate supply chain workflows” is among the biggest opportunities to improve supply chain ops. In addition, 84% of health care leaders said in 2023 that consolidating software at their organization would help clinicians redirect a substantial amount of time to patient care, and 80% said working with disparate systems complicates their job. Properly developed AI software solutions will help health care organizations consolidate and simplify paperwork and help workers reach more patients in less time.
The opportunity for AI to improve health care workers’ lives is not without risk. Entrusting such important work to automated systems will, of course, need to be done in a thoughtful manner. It’s important that health care leaders ask the right questions and follow a thoughtful process as they integrate AI into their operations.
There’s no one-size-fits-all AI solution to health care
As a longtime software executive, I’ve learned that customers know their organizations better than you do. It’s important to start by understanding the gaps that a customer needs to fill and the inefficiencies they hope to address before prescribing an AI-powered solution. Above all else, changing a software system for an organization as large as even one hospital must be a methodical process.
Deploying powerful technology without a strategy for how it will function in a broader health care system can make it ineffective or even detrimental. For health care systems integrating AI into their operations, it’s important to find a partner that is experienced with this work. The good news is that while many people think of AI as a completely new technology, many great companies have been working with earlier iterations of AI for decades. In my 20 years in the tech sector, I’ve seen it integrated into operations at many different companies to great success.
Industry leaders have been developing machine learning for years and are familiar with its capabilities and nuances. Many of our customers aren’t even aware that it’s part of the software powering their operations. The next generation of health care solutions that incorporate machine learning will be more client-facing—but that doesn’t mean it will disrupt health care workers’ understanding of their jobs. Instead, work will simply become easier and more streamlined, saving man-hours while making staff more efficient and sustainable.
This is the kind of subtle yet transformative change that can happen when AI is deployed correctly in our health care systems. It’s important to be incredibly thoughtful with such changes in the health care space. That’s because the health care system depends on patient trust. Patients and their loved ones must trust doctors to deliver high-quality care and protect their well-being. The bond between patient and caregiver needs to be treasured.
I’m confident that AI technology can improve care and strengthen this sacred bond. Deploying it is a meaningful responsibility and a delicate task. Health care leaders must work with technologists to ensure that AI is used to address real problems with as little disruption as possible. Together, we can ensure that our hospitals continue to work for patients, today and tomorrow.
BJ Schaknowski is the CEO of symplr, a health care technology company that provides software solutions for 9 of 10 hospitals in the U.S.
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