Nurses feel “empowered” by integrated patient discharge analytics technology that uses artificial intelligence to analyze administrative tasks such as coordinating discharges, ordering tests and writing prescriptions, says Jean Halpin, chief operating officer at Grant Medical Center.
Recently, it has been shown that many nurses do not trust AI. However, at Central Ohio Health System, nurses are embracing discharge automation – largely due to the efficiency of discharge planning, reduced manual workload and improved rounding experience that the technology enables, according to Halpin.
By shortening the hospital discharge process and freeing up beds, the health system not only increases access to care but also realizes cost savings through analytics that detect gaps in care plans, sends orders and manages milestones, says Mudit Garg, CEO of Qventus, which developed the software.
Garg says OhioHealth is expected to provide care to an additional 3,500 patients in the first year of using early discharge planning and prioritization features within its electronic health record processes.
“The result is a significant impact on both cost savings and operational improvements for OhioHealth,” he explained, equating to approximately $500,000.
In a joint interview, Halpin and Garg described the key drivers for improving patient experiences and increasing operational efficiency with AI-powered hospital care coordination technology.
Q. Has OhioHealth’s staff productivity and overall quality of care helped address burnout and understaffing?
Halpin: Absolutely. The burden of administrative work reduces the amount of time our healthcare teams spend with their patients, which is crucial to establishing positive relationships between nurses, doctors, and patients.
AI tools have enabled our staff to perform at their best rather than spending most of their day filling out paperwork and searching for answers in research. Our staff can not only see more patients, but also take better care of them, dedicating extra time that they didn’t necessarily have before.
I think we’re seeing this technology empower a lot of our employees.
Q. Do nurses operate early discharge planning tools?
Halpin: Yes, our nurses are taking full advantage of the AI tools we are introducing to better support them in their daily administrative work.
Many have experienced burnout and the burden of coordinating discharges. With seamless integration with our electronic health records, our nursing staff feels motivated to prioritize clinical interactions and patient care, while Qventus can handle more time-consuming administrative requests.
Q. What factors were addressed in care coordination or other operational or clinical aspects that reduced the length of hospital stay?
Halpin: A key factor was identifying gaps in patient flow.
By analyzing our data, Qventus was able to see areas of improvement in our daily operations. Tasks such as coordinating discharges to rehabilitation centers, ordering tests, prescribing medications, and more consume the majority of our healthcare teams’ time, and Qventus has alleviated a significant portion of this administrative burden.
For example, if there is a delay in discharge coordination, it can unnecessarily extend a patient’s stay, which is an industry-wide problem. By addressing all of these gaps in patient flow, we were able to accelerate the pace of care, allowing patients to be admitted earlier so they could be assessed and discharged when they were ready to go home; this accounted for almost 1,400 days less in excess patient stays.
Garg: By embedding EDP Intelligence analytics and workflow prioritization capabilities into OhioHealth’s existing EHR processes, we were able to predict potential discharge dates and patient management, allowing healthcare teams to review and adjust procedures based on their clinical knowledge and reducing manual tasks overall.
EHR integration streamlines workflows, reduces the cognitive burden on the healthcare team, and increases the efficiency of care.
There are hundreds of different tests and procedures that must be performed in a timely manner to discharge a patient from the hospital in a timely manner. For example, assessing whether a patient is ready to return home or to a nursing facility may require insurance payer and coordination between the family and the facility.
The technology predicts a patient’s discharge date, where they can go after leaving the hospital on their first day, and then continually adjusts to the patient’s clinical condition as it evolves. The clinical team reviews recommendations [in making care decisions].
Q. How has increasing the number of inpatient beds improved access to care?
Halpin: We have all witnessed long wait times in emergency rooms, but when you take a closer look, a significant portion of this wait time is due to the long hospital discharge process.
While you wait for a bed to become available in the emergency department, patients waiting to be admitted for extended care are delayed because a patient on the floor was not discharged in a timely manner.
By optimizing patient flow through the operate of artificial intelligence, we speed up the coordination process and better predict the days of patient discharge from the hospital, which shortens the waiting time for admission or admission to the emergency department.
Garg: By optimizing discharge planning and shortening the length of hospital stay, beds were quickly made available to novel patients.
This increased turnover means OhioHealth can see and treat more patients in need without having to take on additional beds. In addition to treating thousands of patients, this tool will simultaneously save patients 400,000 additional hospital hours.
More beds also reduced overcrowding in emergency departments, reduced the workload on medical staff and improved resource allocation.
Q. How do you measure improvement in care coordination? Why is it significant?
Halpin: For us, improving care coordination means more time with patients and less time spent in front of a screen searching for answers, which makes a large difference in the experience of our patients at OhioHealth.
The longer a patient waits to be seen in the emergency department, the worse their expectations will be.
By accelerating the pace of care by safely reducing obstacles to patient flow, we are seeing more patients, which is one way to measure improvement. Some of our teams that Grant Medical Center has the most impact on are our physical therapy, imaging and lab teams, for example, who can refer to recommendations in patient charts to determine which patients may be a priority for testing and which are ready to go home and return as outpatients.
Garg: We measure success using 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 healthcare staff are also crucial metrics.
AI provides OhioHealth with access to real-time and predictive analytics, enabling continuous optimization as Qventus learns and becomes increasingly integrated with the OhioHealth healthcare system.
Improving care coordination brings enormous benefits – it improves patient outcomes by providing timely and appropriate care and minimizing delays, resulting in a polished treatment process from admission to discharge.
Q. What feedback can OhioHealth provide on saving 60% on staff rounds time?
Halpin: Most of our rounding time for our staff involves discussing our patients’ estimated discharge date and next step in care, which changes daily based on progress. This discussion includes reviewing patient data and referencing research to make a shared decision among nursing staff, physicians, and support teams such as physical therapy, lab, imaging, and others.
To speed up the process, this technology uses data collected from our electronic health record (EHR) for each patient to recommend next steps and coordinate discharge by comparing similar cases and other studies.
This allows our healthcare teams to quickly review recommendations during each patient’s round and determine whether they disagree with them, significantly reducing the amount of manual work associated with reviewing charts and lab results, saving our teams valuable time and allowing them to get back to caring for their patients.
The HIMSS AI in Healthcare Forum will be held September 5-6 in Boston. Learn more and sign up.