When working to improve patient flow, it is vital to recognize that the different parts of a hospital are deeply interconnected. The nursing units where overcrowding is most evident may not be the units where the mismatch between demand and capacity is causing the problem. Further, patients have complex journeys through their hospital stays, and do not simply move “downstream” from ED to ICU to the floor. In order to improve patient flow in hospitals, sophisticated data analytics are needed to guide decisions on beds and staffing, and to target efforts on length of stay. And to deliver meaningful, actionable information, such analytics must be “holistic”. By holistic, I mean that analytics must encompass the entire interconnected picture of a hospital or even a system, as well as the full complexity of patient movements.
Those of us who work in patient flow have long realized that we cannot address any one part of the hospital in isolation. When tasked with “fixing the ED” to reduce crowding, walkouts, and ambulance diversion, and to improve door-to-doctor time, we know that process changes in the emergency department alone won’t get us to where we need to be. In most cases, emergency departments with significant crowding and delays are that way because beds in the emergency department during peak hours are filled with patients who are admitted and who are waiting to be moved to inpatient beds. Thus, freeing up inpatient capacity is key to unblocking the emergency department.
The same things hold true for other parts of the hospital. We cannot address problems in intensive care units without addressing the floor. We cannot address the PACU without addressing the intensive care units.
We also know that to fix problems in one part of the hospital we have to look both “upstream” and “downstream” to ensure we are actually addressing the real problem and not a symptom. The ICUs may be full because there aren’t enough telemetry beds for patients to move out to, not because there are too few ICU beds.
However, the picture is far more complicated than words like “upstream” and “downstream” can convey. Patients may move from the floor up to the ICU or go from the ICU to the OR, and sometimes they are directly discharged home from the ICU.
The true complexity of all the different patient journeys between different parts of the hospital has to be adequately represented if we are to target our true goals: namely, how often do we want to be able to place patients in the right level of care and the right nursing unit and how much of a delay are we willing to tolerate.
Nineteenth century approaches cannot yield the quantitative answers needed to fix flow. Walking around and looking at units that are full or at beds that are empty does not adequately explain what actions are required. Midnight and noon census, basic arithmetic and spreadsheets all fall short, as does queuing theory alone, which simplifies patients’ journeys into flow between compartments based on formulas and probability distributions.
We need computationally intensive advanced data modeling, such as discrete event simulation and what-if scenario testing, if we are to make the best use of our beds. Truly holistic models represent all the different parts of the hospital, including the ED, the OR, PACU, ICUs, floor; they take into account multiple sites across health systems; they factor in real-life constraints from hospital policies; and they represent the full complexity of patient journeys which crisscross throughout institutions. Only such holistic approaches can accurately represent the complexity we wish to manage. And only such approaches can provide us the operational clarity we need to improve patient access, and to better align staffing structure for overall financial performance.
In the broader culture, when the word holistic comes up, it can come across as a throw away adjective, used to sell everything from skin care products to dog food. But in hospital administration, a 21st century data analytics platform that offers a holistic view for operational planning and management is far from being a consumer luxury. It is an essential requirement for delivering efficient, effective patient care.