Qventus launches expanded version of AI-driven Inpatient Solution 

The solution, now fully integrated into EHR workflows, can help to reduce the length of stays and mitigate the risk of complications.

Soumya Sharma July 26 2024

Qventus has introduced the third generation of its Inpatient Solution, an artificial intelligence (AI)-based software designed to automate discharge planning and care coordination within hospital settings.  

The solution is now fully integrated into electronic health record (EHR) workflows to address critical challenges in healthcare operations, such as reducing the length of stays, mitigating complication risks, and enhancing overall staff efficiency. 

Qventus said that its Inpatient Solution has demonstrated significant impact, with health systems reporting a reduction in excess days by 20% to 35% and a decrease in the length of stays by up to one day.  

OhioHealth, an early adopter of the solution, observed a considerable increase in bed capacity and care coordination efficiency, leading to a saving of nearly 1,400 excess days and an estimated $550,000 in the first month alone. 

The company cited that the healthcare industry is currently facing a projected shortfall of 450,000 bedside nurses by 2027, compounded by increasing emergency department boarding times.  

To address such issues, the company said its solution, leveraging AI, can identify and address gaps in care plans, ensuring efficient sequencing of care steps and supporting optimal patient flow. 

The solution can be deployed to reduce the time care teams spend on manual processes, which can unnecessarily extend patient stays.  

In the broader context, inefficiencies in manual processes could result in an estimated 34 million excess days across 34 million inpatient admissions, equating to a $34bn financial burden, the company noted.  

Qventus' new offering enhances workflow efficiency by keeping care team members within their existing EHR systems.  

It delivers real-time insights and uses machine learning models to help set discharge dates and make disposition decisions.  

The embedded ML algorithm also assists in determining the sequence of patient care, aiding in proactive capacity management and timely discharges. 

In addition, the solution's intelligence engine plays a crucial role in detecting care plan gaps, prompting providers for essential orders, and automating milestones, which saves time for care teams.  

Qventus CEO and co-founder Mudit Garg said: “By integrating AI intelligence seamlessly into the EHR, we ensure every patient has the benefit of an early, accurate discharge plan with barriers proactively surfaced for care team members via automations, reducing manual workload, and improving patient flow. 

“It’s incredibly rewarding to see our solution help health systems improve care infrastructure, increase capacity, and make meaningful steps toward decreasing the burden on our frontline care teams.” 

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