Discharge Planning

Discharge planning is crucial for smoothly transitioning patients from hospital care to the next stage of their recovery. This process requires collaboration among patients, caregivers, and providers to create a personalized plan that ensures continuity of care after hospitalization.

Effective discharge planning must consider the patient’s care needs, preferences, and concerns. When done well, it helps prevent readmissions and alleviates strain on both patients and hospitals. However, balancing clinical judgment with patient data can challenge care teams already burdened with heavy workloads.

Jean Halpin, COO at Grant Medical Center, shared how the organization has integrated AI tools to predict discharge dates and automate parts of the discharge planning process, helping to streamline patient care.

Challenges of Effective Discharge Planning

Halpin emphasized that a streamlined discharge process is essential for reducing wait times and improving patient engagement. Yet, various factors influence how quickly patients are discharged, particularly in emergency rooms where delays can affect overall patient flow.

“Most of the wait time we experience as patients boils down to a lengthy discharge process that isn’t effectively moving patients,” Halpin explained. “It’s a domino effect. Someone waiting in the ER for a bed is delayed because another patient hasn’t been discharged when they should have been.”

To address these inefficiencies, Grant Medical Center implemented the Qventus Inpatient Solution. This tool integrates with electronic health records (EHRs) to analyze patient data—such as clinical notes, history, and labs—and provides recommendations on discharge timing. These insights have helped reduce ER wait times and improved patient flow.

Integrating AI into Clinical Workflows

Adopting AI in healthcare comes with integration challenges, particularly ensuring that tools enhance, rather than hinder, clinicians’ workflows. Halpin noted that the Qventus tool minimizes disruptions by seamlessly pulling EHR data to generate an estimated discharge date, allowing care teams to focus on patient care without extra administrative burdens.

“As a patient’s health changes, the [discharge] date can fluctuate, but AI uses its data to predict the most accurate day based on similar cases,” Halpin explained. “The care teams can then review the date and determine whether they agree, without having to sift through records to develop their own recommendation.”

Halpin also highlighted the value of AI in reducing the administrative load. Tasks like coordinating discharges to rehab facilities, ordering tests, and prescribing medication consume significant time, and automating these functions allows care teams to focus more on direct patient care.

Embracing AI to Alleviate Healthcare Worker Burdens

For healthcare systems adopting AI, accurately assessing its impact is critical. At Grant Medical Center, leadership is measuring success by evaluating employee satisfaction, patient outcomes, and administrative improvements—such as time and cost savings.

“By improving our patient flow, we reduced unnecessary stays by nearly 1,400 days. Patients are happy to go home on time, and our care teams can focus on working at the top of their license,” said Halpin.

Despite the benefits, Halpin stressed that implementing AI requires thoughtful onboarding to ensure staff are comfortable with the new tools. Training and support are key to making the transition seamless and enabling teams to see how AI can enhance their workflows.

“Health system leaders should embrace advancements that help alleviate burdens for workers,” she said. “Once teams understand the tool, they can prioritize patient care while AI handles the time-consuming admin tasks.”

Halpin concluded that embracing AI in discharge planning not only improves operational efficiency but also empowers healthcare teams to deliver better, more focused care.