Q&A: Why OhioHealth Nurses Are Embracing AI-Driven Patient Discharges
Nurses feel “empowered” by integrated patient discharge analytics technology, according to Jean Halpin, director of operations at Grant Medical Center. The technology uses artificial intelligence to analyze administrative tasks such as discharge coordination, ordering tests and writing prescriptions.
Recently, it has become apparent that many nurses are wary of AI. But at the Central Ohio health system, nurses are embracing discharge automation — thanks in large part to the discharge planning efficiencies, reduced manual workload and improved rounds experience the technology enables, Halpin said.
By shortening the discharge process and increasing bed capacity, the health system not only increases access to care, but also realizes cost savings with analytics that detect gaps in care plans, expedite orders and manage milestones, said Mudit Garg, CEO of Qventus, which develops the software.
According to Garg, OhioHealth expects to treat an additional 3,500 patients in the first year of implementing early discharge planning and prioritization capabilities into the electronic health record workflows.
“The result is a substantial impact on both cost savings and operational improvements for OhioHealth,” he explained – which equates to about $500,000.
In a joint interview with Healthcare IT News, Halpin and Garg described the key factors that lead to improvements in patient experience and operational efficiency through AI-driven patient coordination technology.
Q. Have OhioHealth’s staff efficiency and overall quality of care delivery contributed to addressing burnout and staff shortages?
Halpin: Absolutely. The burden of administrative work reduces the amount of time our care teams spend with their patients, which is critical to building positive relationships between nurses, physicians, and patients.
AI tools have allowed our staff to operate at the highest level of their license instead of spending so much of their days filling out paperwork and searching for answers in research. Our staff can not only see more patients, but they can also care for them better, spending extra time that they may not have had before.
I think many of our employees are being re-energized by this technology.
Q. Have nurses embraced early discharge planning tools?
Halpin: Yes, our nurses embrace the AI tools we use to better support them in their daily administrative work.
Many of them have experienced the stress and coordination of discharging patients. Thanks to the seamless integration into our EHRs, our nurses can now prioritize clinical interactions and care for our patients, while Qventus handles the more time-consuming administrative tasks.
Q. What factors were addressed in care coordination or other operational or clinical aspects that reduced hospital admissions?
Halpin: The most important factor was identifying the gaps in patient flow.
By analyzing our data, Qventus was able to identify areas of improvement in our daily operations. Tasks such as discharge coordination to rehabilitation facilities, ordering tests, prescribing medications, and more take up a lot of time for our care teams, and Qventus has alleviated much of that administrative burden.
For example, if there were a delay in coordination of a discharge, which could unnecessarily extend a patient’s stay, which is a problem that affects the entire sector. By addressing all of these gaps in patient flow, we were able to accelerate the speed of care, get patients in earlier to be seen, and get them out the door as soon as they were ready to go home; that’s reduced the number of extra patient stays by almost 1,400 days.
Garg: By embedding EHR Intelligence insights and flow prioritization capabilities into OhioHealth’s existing EHR workflows, we were able to predict achievable discharge dates and patient appointments. This allowed their care teams to review and adjust the data based on their clinical expertise and reduce manual tasks overall.
Integration into the EHR streamlines workflows, reducing the cognitive burden on the care team and making care more efficient.
There are hundreds of different tests and procedures that need to be done in a timely manner to discharge a patient. For example, assessing whether a patient is ready to go home or to a nursing facility may require payer insurance and coordination between the family and the facility.
The technology anticipates the patient’s discharge date, where they can go after the hospital on the first day, and then continuously adapts to the patient’s clinical condition as it evolves. The clinical team reviews the recommendations (when making care decisions).
Q. How has increasing hospital bed capacity improved access to care?
Halpin: We’ve all seen the long wait times in the emergency room, but if you look closely, you’ll see that a large part of that wait is due to the lengthy discharge process.
While you wait in the emergency room for a bed to become available, patients in the emergency room waiting for long-term care are being delayed because a patient upstairs cannot go home in time.
By optimizing our patient flows using AI, we accelerate the coordination process and can better predict when our patients will be discharged, reducing the delay in care for patients waiting for a consultation or admission to the ED.
Garg: By optimizing discharge planning and reducing length of stay, we were able to free up beds for incoming patients more quickly.
This improved turnover rate means OhioHealth can admit and treat more patients in need without the need for additional physical beds. In addition to treating thousands of patients, the tool also saves patients an additional 400,000 hospital hours.
The increased bed capacity has also reduced overcrowding in emergency departments, reduced pressure on healthcare staff and improved resource distribution.
Q. How is improvement in care coordination measured? Why is it significant?
Halpin: For us, improving care coordination means spending more time with patients and less time behind the screen searching for answers, which is critical to our patient experience at OhioHealth.
The longer a patient has to wait in the emergency department, the worse the experience will be.
By accelerating care by safely reducing barriers to our patient flow, we see more patients, which is one way we measure improvement. For example, some of our most impacted teams at Grant Medical Center include our physical therapy, imaging, and laboratory teams, who can reference recommendations in patient records to determine which patients may be prioritized for testing and which are ready to go home and return as outpatients.
Garg: We measure success through key performance indicators such as reduced length of stay/excess days, reduced readmission rates, improved patient flow, and timely discharge planning. Improved patient satisfaction scores and reduced manual workload for care staff are also key metrics.
The AI provides real-time insights and predictive analytics to OhioHealth, enabling continuous optimization as Qventus learns by increasingly integrating into the OhioHealth care system.
The impact of improved care coordination is significant: it improves patient outcomes by ensuring timely, appropriate care and minimizing delays, resulting in a seamless experience from admission to discharge.
Q. What feedback can OhioHealth provide regarding saving 60% on staff turnaround time?
Halpin: A large portion of our staff’s turnaround time involves discussing the estimated discharge date for our patients and the next step in care, which fluctuates daily based on progress. This discussion includes reviewing patient data and referring to research to arrive at a shared decision among nursing staff, physicians, and support teams such as physical therapy, lab, imaging, and more.
To speed up this process, the technology uses the data collected from our EHR for each patient to make recommendations for next steps and coordinate discharge by comparing similar cases and other research.
This allows our care teams to quickly review the recommendations during rounds for each patient and determine whether or not they agree with them. This eliminates much of the manual work of reviewing charts and labs. This saves our teams valuable time and allows them to focus on patient care.
Andrea Fox is Editor-in-Chief of Healthcare IT News.
Email address: afox@himss.org
Healthcare IT News is a publication of HIMSS Media.
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