"While there is some skepticism among nurses, I believe that when applied in the right settings, artificial intelligence is far from a threat," says Hadassah Backman, CEO of Guardoc, a clinical data integrity company.

In particular, she says she's most hopeful about AI's power to act as a force multiplier, alleviating digital workloads so nurses can focus on the quality of patient care. 

Backman says she understands the weight of the administrative burden nurses experience thanks to her hands-on experience in emergency room and hospice care as a registered nurse and clinical risk consultant. 

She says one of AI's biggest potentials is its ability to cross-check charting work, improve the accuracy of patient data and flag issues.

"We are seeing the promise of AI come to life, making striking improvements in reducing charting errors, and freeing up nurses' time."

She's not the only one: Mercy's Chief Nurse Executive Betty Jo Rocchio, DNP, said as when she keynoted the HIMSS AI in Healthcare Forum this past month. To improve nursing workforce experiences and address staffing challenges, that health system deployed an automated nurse-credentialing system and began leveraging AI to improve emergency department handoffs across Mercy's 51 hospitals. 

"We have to have the analytics" to show that over the past two years, its AI-enabled workforce initiatives achieved a more resilient staff, increased retention and saved millions of dollars," said Rocchio.

In this Q&A, Guardoc's Backman describes how other healthcare organizations are also reducing charting errors by as much as 50% per nurse – improving patient outcomes and saving organizations money that can be reinvested in quality improvement and operational efficiency.

Q. Healthcare is facing a shortage of nurses, but nurses are facing a number of daily operational challenges that are driving many away. Where does the shortage leave patient care and what do nurses need most from healthcare organizations?

A. I can tell you from my own experience as an ER nurse that the ongoing nursing shortage is leaving patient care in a pretty precarious spot. 

While the profession has always had its challenges, the pandemic induced a widespread nursing shortage, which has only been exacerbated by an aging population demanding more healthcare. All of these factors combined is why we are looking at the biggest nursing shortage in our country’s history.

With fewer nurses on staff, those who remain are stretched incredibly thin, juggling more responsibilities than ever before, drowning in paperwork, at times dealing with unsafe working conditions and pulling longer shifts. This all takes away from their time, attention and human ability to provide the very best in patient care.

Nurses need more support from their healthcare organizations in various forms – compensation, staffing, patient load support and for the mountains of manual compliance auditing and paperwork nurses have to spend many hours on each month.

Q. What are the key areas healthcare organizations need to address to improve clinical data integrity?

A. Improving clinical data integrity is one big unlock for supporting the nursing workforce today, and I see so much potential in AI’s ability to bring much needed support in this area. The biggest areas that need to be addressed, and can be with AI, are in integrating disparate data systems, supporting the compliance process and improving data accuracy.

We aren’t talking about AI taking over nurses' jobs. 

Right now, there is no central hub of patient information across healthcare organizations, so there is no easy way to understand a patient’s full history when they are treated. Getting all that data talking to each other would paint a much clearer picture and ease the intense information-gathering process that currently falls to nurses.

Nurses are also spending precious time making sure every encounter meets strict regulations. Automating some compliance processes could free them up and reduce human error. To improve accuracy, advanced AI systems can also analyze patient data and automatically populate charts, reducing the risk of human error. 

Imagine AI tools that cross-check medication orders with patient history, flag potential issues and ensure that everything is accurate before a nurse even sees it. 

Q. Which technologies are you most hopeful about in terms of clinical risk management, and why?

A. In my own work building Guardoc we’ve seen the power and potential AI holds for the future of healthcare. AI can help in areas like minimizing charting errors by cross-checking things like medication orders against patient history and flagging potential issues.

It can reduce compliance reporting and documentation management, reducing the risk of human error in these critical but tedious tasks while creating more comprehensive patient records. By integrating data from various sources, healthcare providers have a more complete picture of a patient's history and needs.

Q. How has artificial intelligence reduced charting errors and are nurses that are testing clinical data validation models receptive to using them?

A. In the last eight months, we’ve been testing our clinical risk technology across six U.S. healthcare organizations. The clinics using our product have experienced improvements like:

• A 50% reduction in average charting errors per nurse.
• An 86% decrease in errors affecting patient outcomes.
• Two clinics experienced a 100% citation-free state survey, a dramatic improvement from previous records of over 23 documentation-related errors.
• A projected 90% annual reduction in hours nurses spend on auditing.

These early results give me so much hope and optimism for what AI can bring to the future of healthcare and how we can look to improve nurses' roles, their overall work-life balance and the patient care they are able to provide.

Q. How does clinical validation technology improve an organization's revenue management?

A. First off, automating and improving the clinical documentation and compliance process helps prevent costly errors that can come from humans. Errors in compliance aren’t just a casual misstep. They can result in big financial losses for healthcare organizations in the form of penalty fees, lawsuits, and slowed or paused reimbursement (on average $40B per year across the industry) which puts facilities and nurses' wages at risk. 

By automating compliance checks and improving data accuracy, clinical validation technology can help organizations avoid penalties and secure payments they might otherwise miss out on.

It also streamlines the auditing process. Right now, nurses are spending a ton of time manually ensuring that every patient encounter meets regulations. Automating more of this process not only reduces the risk of mistakes but also frees up nursing staff to focus on patient care instead of paperwork.

All in all, clinical-validation tech has the potential to both prevent revenue losses and help organizations more efficiently capture the revenue they're entitled to. It's not just about making more money though – it's about making sure healthcare providers have the resources they need to keep providing quality care.

Andrea Fox is senior editor of Healthcare IT News.
Email: afox@himss.org
Healthcare IT News is a HIMSS Media publication.