The following is a guest article by Jason Harber, COO & Chief Strategy Officer at Hospital IQ.
For hospital leaders, operational decision-making is one of the most difficult and stressful responsibilities they face daily. The daily challenge for hospital leaders is ensuring their hospital has the required resources to adequately accommodate patient demand at all times and in all scenarios. These decisions hugely impact the organization’s success and sustainability and the patients it serves.
Managing inpatient capacity is multi-faceted and requires complex, cross-unit balancing and coordination of bed availability, patient throughput, and staffing needs to meet immediate patient demand in real-time and to ensure it can be met in the days to come.
In light of everything the healthcare industry has weathered over the past few years, it has become apparent that the shift from reactive decision-making to proactive planning is necessary. If unable to manage capacity and staffing proactively, hospitals risk experiencing bottlenecks that hinder access to care for the communities they serve. As a result, the impacts spread throughout the enterprise in the form of longer wait times, long lengths of stay, diversions, or patients inevitably going without the treatment they sought. However, through the strategic and intentional use of AI-enabled automation, hospital leaders can better ensure they have the ability to be properly and proactively prepared for patient demand today, tomorrow, or a week from now.
Optimizing Capacity by Making Data Work Smarter, Not Harder
There is much-untapped value to be revealed by simply optimizing the use of your hospital’s internal data and existing health technology solutions. The key is to leverage AI-enabled automation and data-driven insights, which can generate a real-time, accurate comprehensive view of current and upcoming demand, and the state of your capacity (bed, operating rooms, staff) enterprise-wide. Collective, comprehensive, real-time visibility into the operational state of the hospital makes it easy for care teams to coordinate resources and capacity in the most efficient, effective, and sustainable manner possible that supports all units and teams. By aggregating data that already exists from the EHR, workforce management, and all other existing systems – automated data intelligence solutions enable constant monitoring and analysis that would be unachievable otherwise.
AI-enabled automation and advanced data intelligence equip care teams with the foresight to know what is coming. By providing real-time insights and automated suggested actions based on those insights, leaders become equipped with the information they need to optimize capacity and proactively prepare for predicted challenges before they arise. For example, an organization could receive a notification when data forecasts that bed availability or staffing isn’t going to meet patient demand, allowing leaders to adjust and align resources, act on priority discharges, and avoid a capacity crisis before it materializes, as was the case for one Indianapolis health system looking to optimize staffing. This organization was able to create 250 days of usable capacity and reduce patient moves within the same level of care by over 60%, which drove over one million dollars in annual savings.
Another example can be seen in the hospital division of one of our partners, Health First. They used AI-enabled automation and proactive, predictive insights in their health system to optimize discharge planning by making it easy to identify high-priority patients and discharges each day. According to Dr. Brian Boggs, Vice President at Medical Affairs, “Hospital IQ’s platform predictions provided remarkable value in identifying high-priority patients, saving us considerable time prioritizing today’s patient discharges and enabling us to pre-plan tomorrow’s discharges.” As a result, without having to manage discharges with inefficient manual processes, the health system eliminated over 500 avoidable days monthly and reduced the length of stay by six hours per patient on average. The time saved from automation optimized Health First’s day-of operations and allowed them to pre-plan for tomorrow’s discharges too – equipping Health First with the insights needed to operate as a data-driven, predictive, proactive, intelligent organization.
Operational decision-making holds more weight than ever before, from making intelligent decisions about staffing, resource allocation, discharge planning, and of particular importance, best practices for managing inpatient capacity. Without visibility into future capacity constraints, hospitals lack the intelligence needed to operate adequately within their means now and to feel confident in their ability to do so in the near future.
Proactive, data-informed operational decision-making is quickly becoming a necessity for hospitals, Amidst industry concerns around limited staff bandwidth, patient access, financial insecurities, and more – augmenting operational decision-making through AI-enabled automation gives hospitals the tools to maintain sustainable, efficient, and innovative organizations, and to ensure their patients can get the care they need, when they need it, despite many of the market factors that have long hindered their ability to do so.
