The patient discharge process tests a health system’s efficiency and patient experience. Many health care facilities struggle to have cohesive processes due to a lack of communication, speed, and organization. The nonprofit, Central Florida-based health system, Health First, has integrated artificial intelligence into its discharge process in order to better connect all those involved for increased efficiency.
Problems in the patient discharge process arise when communication is lost, information is scattered, and many teams are involved. Moreover, many facilities utilize a paper-based system and overtime copies are replicated and become outdated. This leads to underprepared staff and a poor patient experience. In cases such as these, artificial intelligence (AI) can be deployed in the discharge process in order to inform health care providers, ensure record accuracy, improve time management, and to provide better services.
Health First has partnered with Hospital IQ, a vendor of predictive hospital operations software. The AI-based system informs health care providers with real time information by providing situational awareness for future issues, managing discharge activities, and giving insight into current problems.
Health First consists of four hospitals and 900 beds in total. It is crucial that patients are prioritized in order to ensure a timely discharge and future availability. An automated system such as Hospital IQ would provide care teams with information on capacity, allowing them to act before issues arise.
Division Director of Patient Throughput at Health First, Patricia Canitano said, “By integrating machine learning based AI in forecasts with our own data collected across our four hospitals, Hospital IQ predicts future patient demand while automatically prioritizing specific patients for discharge.” Through automated processes, all care teams that previously lacked communication can receive real-time updates to quicken the discharge process.
Health First has reported that after two years of using Hospital IQ, it has eliminated 517 avoidable days monthly, reduced length of stay by 6 hours on average per patient, and eliminated 200 hours of data collection per week. It also saved over an hour per person per shift and was able to discharge two more patients daily on average.
With many health systems still at max capacity, and providers being stretched to their limits, a streamlined discharge process becomes even more crucial, and AI and machine learning may hold the key.