Clearly coordinated patient throughput is vitally important to the overall efficient management of the hospital and to the quality of patient care. Although inpatient bed capacity management has been challenging throughout the pandemic, inpatient flow management has historically been a challenge even during ‘normal times’.The inherent complexity of inpatient care and the resulting rather disconnected discharge processes have been key barriers to improving patient progression and throughput. However, one positive outcome of the past 18 months has been the increased acknowledgement of the need for a better way and the corresponding adoption of technology leveraging real-time data plus predictive and prescriptive analytics that puts the power of decision making in the right hands at the right time. With this technology, hospitals are able to predict future admissions and discharges, balance beds across the network, hospital, and unit, and confidently make strategic decisions to get the right patients in the right bed at the right time.Join this session to get a glimpse into tools that are successfully enabling hospital operational teams to move away from reactive capacity planning and toward proactive problem-solving. Hear how these tools have been effective in improving patient flow by reducing wait times at key steps along the patient journey and mitigating the chaos historically inherent in managing bed capacity.
Key learning objectives include:
Identify the current challenges of capacity management - underlying math to match supply with demand - for health systems to maximize the use of assets to create value for patients and themselves.
Understand how AI-driven, intelligent systems can optimize the matching of supply and demand - during both “crisis” and “normal” times, without the extensive capital and resources needed by a command center.
Describe how UCHealth taps into knowledge from IT platforms to improve census predictions and real-time decisions about patient placement, staffing, surges and diversion prevention.