Triggers for Surges: The Role of Advanced Data

Precision matters when hospitals are responding to surges in inpatient demand. Many hospitals learn the hard way just how expensive it can be when there is no effective process for responding to surges as they can result in lost transfers, lost direct admissions, lost admissions from ED walkouts, sometimes even canceled surgical cases, to say nothing of the negative impact to the patient experience, level of clinical care and hospital reputation. Yet hospitals that have woken up to the need for surge planning know getting the response right is just as important. Triggering surge actions when they aren’t necessary or targeting the wrong areas for action can also be expensive and can undermine staff engagement with surge planning. Advanced data systems can take hospitals to the next level of economic and operational performance by identifying triggers for surge response activation that are early, accurate, specific, and targeted.

Even without advanced data, implementing a surge plan with appropriate triggers and actions beats having no plan at all! But as we look at all the classic situations where bottlenecks cause delays and overcrowding, we see just how much can be achieved with advanced data systems that offer accurate and timely insights.

Emergency Departments
Surge triggers in the ED will typically involve how many patients are waiting to be seen, how many are currently being treated, and how many are “boarding” – admitted patients waiting for inpatient beds. These measures are good for raising the alarm when there is already a problem. However, many of the actions to address and alleviate surges require significant lead time, such as reassigning nurses or calling them in for extra shifts. Advanced data systems can forecast ED demand days in advance based on historical demand, weather patterns, seasonality and local events to predict the number of patients and mix of acuities arriving hour-by-hour. Combining this with simulation modeling produces predictions days ahead of time to warn of impending high demand situations. Additionally these predictions will be for specific bed types, highlighting whether it is critical care beds, telemetry beds, or med-surg beds that will be most in need.

Inpatient censuses
Inpatient census is another common trigger for surge responses. Once again, hospitals typically have triggers that reflect a state of bed shortage and overcrowding only once the crisis has occurred. Opening additional nursing units and beds takes time, as does calling in staff, working with case managers to prioritize discharges, and other measures to address census crunches. Advanced data approaches combine forecasting with simulation modeling of the entire hospital or health system. This allows hospitals to mobilize early and to focus upon specific levels of care. For instance, there are times when hospitals experience a shortage of critical care beds but not other bed types. Such events require targeted action rather than an overall surge response, and advanced data systems can predict these events well ahead of time.

Advanced data approaches
Advanced data approaches can combine several key elements, such as data from disparate hospital IT systems (e.g., health records, physician order entry systems, bed management and finance). They integrate these disparate data sources into a single data warehouse. They can run thousands of simulations with real data, to quantify not only expected metrics, but variability. They allow “what if” scenario testing to establish whether specific actions will work to improve operations, avoiding putting staff through trial and error initiatives. Complex forecasting can bring in arrivals through all sources, whether it’s emergencies, direct admits, or planned surgeries. Holistic modeling across an entire system can allow decisions to fully realize synergies across sites. Dashboards break down walls between disciplines and departments, allowing everyone to share the same data and the same forecasting in real time. And these systems allow for radical transparency, drilling down to the level of individual encounters behind the metrics to achieve trust and buy-in.

All of these features are important for improving healthcare operations generally. When it comes to census surges specifically, these capabilities will powerfully augment traditional triggers to ensure surge responses are early, accurate, specific, and targeted.