Copient Health uses machine learning to identify OR block time likely to go unfilled. It then gets the released time into the hands of other providers who can use it by nudging block holders to release the identified time and by giving facility schedulers real-time information on recapturable time.  It also provides an AI query tool allowing authorized facility users to ask unlimited questions about their data and have the AI model take actions on their behalf.

Copient Health uses machine learning to identify OR block time likely to go unfilled. It nudges block holders to release the identified time, then gets the released time into the hands of other providers who can use it.  It also includes a set of real-time analytics to support decision-making around block management. The result is increased utilization, improved OR margin, better patient access, and satisfied providers.

Apella is a technology company that leverages cutting-edge artificial intelligence, computer vision, and predictive modeling to help healthcare providers utilize their operating rooms more effectively. The company offers a suite of tools designed to increase utilization, improve efficiency, and maintain quality.

One of the key features of Apella's technology is its predictive scheduling tools. These tools use advanced algorithms to provide accurate case durations and highlight underutilized OR time, enabling hospitals to proactively optimize their OR schedules and increase case volume. For instance, Apella's technology identified and allocated 500 new hours of block time within the orthopedic surgery department at a leading academic medical center.

In addition to predictive scheduling, Apella offers real-time management tools that provide a live view into operating rooms. These tools help orchestrate the flow of resources throughout the OR, improving efficiency and reducing turnover times. In one case, Apella's technology helped a multi-specialty community-based hospital reduce turnover times by 15%.

Apella also provides targeted insights for process improvement. These insights identify areas for improvement in quality processes that are often unmeasured. For example, Apella's terminal cleaning evaluation identified that 38% of terminal cleans were missed over a three-month period at a multi-specialty, community-based hospital. Furthermore, it was found that OR lights were only cleaned 61% of the time, and cleaning under OR pads took place 31% of the time.

Apella's technology offers a comprehensive solution for operating room management, helping hospitals increase utilization, improve efficiency, and maintain quality through the use of artificial intelligence, computer vision, and predictive modeling.

• identifies in advance portions of block days likely to go unfilled using machine learning
• automatically nudges providers/schedulers to release the time they won't fill
• eliminates inefficient back-and-forth between facility and surgical office by automating the request process
• provides in-depth analytics not available from a customer's EHR

• Guaranteed ROI
• Integrates financial metrics like contribution margin into block decisions.
• Simple, affordable monthly subscription with no upfront cost and no long-term commitment
• Leverage existing workflows; no need to learn a new application
• Modular; use only what you need
• Appropriate for hospitals and ASCs