AUTOMATION PLATFORM

Identify issues.

Managing operations requires the ability to identify and predict issues, whether in the past, present, or future, before they occur. To do this, you need a variety of technologies, including integration with EHRs and other systems, sophisticated data analytics, AI and machine learning for real-time identification and prediction, and situational awareness capabilities for real-time visibility at multiple organizational levels.

Orchestrate actions.

But identifying issues alone isn’t enough. You also need to be able to help frontline teams and ancillaries take steps to address or avoid the issues. You can reduce the cognitive burden on teams and decrease process variability by hardwiring processes. Doing so requires technology for real-time communication and collaboration between departments, last-mile integration, prioritized task lists, and in some cases complete automation of key steps. Additionally, habit formation techniques like nudges and rewards help ensure that the processes stick.

Manage accountability.

Finally, to drive continuous improvement, you need to manage accountability across teams. This means identifying when a process isn’t working — both over time and in real-time — and taking action to correct course. The technology required to do this includes sophisticated data science analytics, such as statistical outcomes analyses, as well as automated escalation pathways to ensure critical issues are being surfaced to managers in real-time.

Reduce frontline burden through automation

AI-based algorithms automate manual processes such as predicting EDD and discharge barriers for inpatient units, and surges in the ED. These engines use a library of ML models to predict issues before they occur and power real-time orchestration workflows to address or avoid the issues.

Embed behavioral science to drive workflows

The engines hardwire the concepts of behavioral science into processes, driving and influencing desired actions and behaviors at the individual and organizational levels.

Monitor process variations for targeted action

Sophisticated statistical analytics run in the background and detect process variations. The engines automatically suggest actions when processes slip, and can also identify opportunities for positive reinforcement.

Simple, easy to use applications feature a modern design with embedded intelligence for driving workflows and uncovering insights.

The Qventus Platform includes a range of user applications with embedded intelligence and workflows across both web and mobile platforms.

ML model outputs are typically not surfaced directly to end users. Instead, Qventus delivers prescriptive recommendations that clearly communicate specific or suggested actions for end-users to take. This makes it easy for users to understand what to do next to address or avoid operational issues, reducing the cognitive burden on frontline teams.