Length of stay (LOS) has long been a critical metric for hospitals and health systems, with significant implications for their financial performance. New data underscores just how impactful even small reductions in LOS can be for a healthcare organization’s bottom line.
According to a Kaufman Hall 2024 report, optimizing length of stay is one of the top characteristics of financially high-performing hospitals. The report describes improving length of stay as a “no-regret strategy” — an operational priority that is highly likely to yield substantial benefits for the time and resources invested.
The Kaufman Hall analysis found that if a hospital were able to achieve a one-day reduction in length of stay, by reducing excess days, it could realize three distinct financial benefits.
For example, a 425-bed hospital could save over $20 million in operating expenses. It could open up space for additional admissions — for example, at $4,500 per admission, this could equate to around $20 million in additional margin. And the same 425-bed hospital in the case of this example could avoid new construction, which could run $2-3 million per bed in capital costs.
Collectively, these three financial upsides demonstrate the immense value that improvements in length of stay can deliver. As the report notes, hospitals have long struggled with this metric, as many complex factors can influence a patient’s time in the hospital. Effective patient status tracking, utilization management, care transitions, and discharge planning all play crucial roles.
Unfortunately, the roles most focused on length of stay — such as case managers and care coordinators — have been among the hardest hit by staffing shortages, especially at smaller hospitals. This, combined with a lack of real-time data integration, has compounded the workflow bottlenecks that can lead to delayed discharges.
The report suggests that hospitals putting the right structures, processes, and technologies in place to optimize length of stay are gaining a distinct financial advantage.
The latest data from Kaiser Family Foundation says that it costs $3,025 in average adjusted expenses per inpatient data at hospitals. That means just one patient staying an unnecessary day at the hospital for each of the 365 days per year totals $1.1 million in additional expenses for the hospital.
This is where artificial intelligence (AI) solutions are poised to have a transformative impact.
AI-powered platforms like Xsolis’ Dragonfly Navigate can leverage predictive analytics to forecast a patient’s expected length of stay and discharge disposition from shortly after admission. By continuously monitoring a patient’s clinical status and comparing it to historical data, these AI tools can continually reassess those predicted discharge targets throughout the encounter, as more information becomes available.
Armed with this intelligence, care teams can be more proactive in their discharge planning, utilize objective data points to align on the most urgent priorities, and more easily maintain coordination around a patient’s post-acute needs and treatment status. Integrating AI into length of stay management allows hospitals to be more proactive, rather than reactive. It enables them to optimize patient flow, reduce unnecessary days, and avoid the substantial financial penalties associated with extended stays.
Perhaps most importantly, AI-powered length of stay management supports better quality of care by reducing the administrative burdens placed on clinicians and giving them more time to focus on ensuring their patients receive the right level of care at the right time. Reducing unnecessary hospital days is not just good for the bottom line, it also translates to lower risks of hospital-acquired infections, medication errors, and other adverse events that can compromise patient outcomes and stand in the way of the patient achieving their healthcare goals.
As the healthcare industry continues to grapple with rising costs and value-based reimbursement models, the ability to accurately predict and effectively manage length of stay will only grow in importance. AI-powered solutions that enable hospitals to streamline discharge planning and more easily track and address the root causes of avoidable days represent a critical tool in the quest for greater financial sustainability and improved patient outcomes.
Learn more about the Dragonfly Navigate product line, Xsolis’ AI-driven solutions that offer a better way to manage length of stay.
