Not all patient volume surges are alike. With so many differences among patients and illnesses, different levels of acuity, and specialty nursing requirements, when volume picks up, critical bottlenecks will appear in different parts of the system each time. Which part of the system reaches overload first? Which overload is the worst? Which has the greatest impact upon clinical care, hospital operations, and finances? These questions must be asked afresh each time a surge situation develops.
To illustrate this, consider a hospital with “boarders” – admitted patients waiting for a bed – in the Emergency Department (ED), with ambulances diverting to other hospitals, and patients walking out without even being seen by a physician because it’s taking too long. These are all costly scenarios for a hospital from both a financial, as well as a delivery of care perspective. But is it effective to send case management out to all nursing units and spend hours working to get patients home a day or even a few hours earlier in order to free up needed beds? What if, upon deeper examination, it turns out the bottleneck is only with telemetry beds and that there is actually no shortage of ICU or med-surg beds? Imagine how much more effective it would be to focus the efforts of case management on only the type of beds in short supply.
Let’s look at specific sets of actions that can be taken that are associated with the entry points to the hospital, or “front end.” Most hospitals and systems receive incoming patients through several channels: scheduled surgical and procedural cases, scheduled medical encounters (e.g., oncology), direct admissions (from physicians’ offices), transfers from other hospitals (typically for patients requiring a higher level of care), or, finally, ambulance and walk-in patients who arrive via the ED.
Talking specifically about the ED: During surges, with profound bed shortages, can demand for beds from patients arriving at the ED be managed? The answer is yes, but only with a coordinated strategy embraced at the very top levels of the organization, with very wide involvement among staff and providers, and most importantly with a set of tools to provide a timely, data-driven, decision-support framework.
There are two main strategies for managing demand for beds from the ED. The first is facilitating treatment discharges to reduce avoidable admissions. The other, more complex approach is directing admissions between hospitals within a multi-hospital system and success depends on these key tenets.
The right case at the right place
Many systems comprise a mix of hospitals, ranging from tertiary- or quaternary-care sites with extensive specialty coverage, through to community hospitals that may offer little more than general medicine, general surgery, and OBGYN coverage. Often the cost per bed-day matches the complexity of services available. Within the same system, the per-bed-day cost at the community sites might be half the cost of the “mothership” that has intensive capital investment in specialized equipment, as well as more intensive and specialized “human capital” on hand.
In purely financial terms, it would make sense for hospitals to direct patients with higher complexity illnesses towards the more resource-intensive hospitals, and those with simpler illnesses towards community hospitals. This would match the clinical capabilities of the facilities to the needs of patients. Further, it would match high costs per bed-day to cases with higher revenue per bed-day, allowing flagship hospitals within systems to provide greater care to the sickest patients.
Managing patient expectations
However, for some simple reasons this is often not the practice. Patients arrive at a particular hospital expecting that if they require admission they will be admitted at the same site. This may be because it is close to where they or their family live. Or it may be because the doctors who are mainstays of their care don’t have admitting privileges at other sites. It may simply be that they are most familiar with the hospital they came to.
Clearly an argument can be made for routinely routing patients according to acuity. And that argument takes on new force at times of high demand for beds. During surges, it is important not only to manage overall demand and supply, but to manage various specific types of demand. In practice, during surges, that will mean directing high- and low-complexity patients to different hospitals within a system.
Readiness of staff and processes
There is much heavy-lifting required to do this. Physicians, nurses, and other staff need to understand why patients are being transported between sites for admission. This is being done not simply for financial reasons, but to provide timely care to people who need it at the site most able to provide that care. Scripting needs to be developed and field tested. Elements of the scripting will generally include reassurances that member hospitals are part of the same system, with the same care processes, and that in a period of high demand they are being admitted to the site that has a bed clean and ready for them with nurses and doctors waiting to provide care.
There are different ways to segment which patients go to which hospitals. One approach is diagnosis-driven. For example non-ICU community acquired pneumonia cases may be admitted to community hospitals, while more complicated pneumonia cases come to the flagship. A different approach is to involve case management in directing the flow of patients between sites. This has the benefit of sparing physicians the effort of remembering and internalizing rules that are essentially administrative rather than clinical.
Awareness and support must extend to the very top leadership as well as governing boards. There will be complaints. If front-line staff and providers are not supported, efforts to route patients between sites will quickly degenerate into inconsistency and then failure.
During times of regular demand, a process for routing patients between sites can improve quality of care and can aid growth and financial strength for a health system. During surge periods, such a strategy goes further and can help weather the storm. Executing on such a strategy can be made far more effective by advanced operation management data platforms that can warn of impending surges, highlight where bottlenecks will occur first or worst, and indicate where opportunities lie for admitting patients across sites within a system.
For more on patient surges, check out my eBook: Using Predictive Analytics to Avoid Reactive Surge Management.