AI Case Study

Mercy Hospital Fort Smith improves patient flow and throughput in the ER to improves LWBS rates by over 30% using machine learning

Mercy Hospital Fort Smith improved emergency services using Qventus's AI platform. The platform monitors hospital data and external factors to predict demand which can be used to optimise staffing and acquiring resourcing. After implementing the platform Fort Smith branch moved from 29th to 3rd spot in customer satisfaction among Mercy group of hospitals.

Industry

Healthcare

Healthcare Providers And Services

Project Overview

"For most hospitals, the Emergency Department is the primary point of entry for patients, driving up to 70% of hospital admissions. The Qventus platform optimizes hospital operations in real-time. It continuously monitors hospital data and external factors, predicts issues, and prescribes immediate and accurate course corrections. The platform gives frontline teams the answers they need at their fingertips to take the right action at the right moment in time. The result is improved financial performance and enhanced patient and clinician experience."

"Qventus is an AI-based software platform that solves operational challenges across the hospital including emergency departments, perioperative areas, and patient safety.

Much like an air traffic control, we identify potential issues before they occur and recommend immediate and accurate course corrections."

Reported Results

According to Qventus:

* 30% decrease in left without being seen (LWBS) rate
* 24 minute reduction in length of stay (LOS)
* 20% reduction in door to doc time
* ED can accommodate 3,000 additional visits per year
* Projected $1.3 million in additional annual revenue and savings
* Increased patient satisfaction scores—(of the 31 Mercy hospitals in their system, Mercy Fort Smith moved from 29th to top three)

Technology

Function

Strategy

Data Science

Background

Mercy Fort Smith is a 336-bed acute care hospital which receives around 50,000 visits per year to its Emergency Department.

Benefits

Data