For several months, Massachusetts voters have been inundated by media coverage regarding Question 1 on nurse staffing. This has divided us into two passionate groups: for and against. Are the differences irreconcilable? Not necessarily. The key is to understand the real cause of the nurse staffing problem.
When nurses have too many patients, they can’t do their best work. That problem arises largely because the number of patients being taken care of by nurses fluctuates widely and frequently. That makes it hard for managers to adjust nurse staffing levels from day to day. Responding to these swings in workload by moving staff around has been shown to be ineffective. So hospital managers have to choose between having overworked nurses at certain times (thereby increasing the risk of medical errors, readmissions, and long waiting times in emergency departments) and having other times when scarce and costly nursing resources are not fully utilized. For us voters, that’s a no-win choice: either overload nurses or tolerate periods of wasteful over-staffing, which raises health care costs.
The question that almost nobody asks is why patient volumes vary so widely and frequently. Most people think the variation has to do with unpredictable emergency volumes — groups of patients that suddenly show up. That’s not the case. The surprising answer is that hospital managerial decisions, not fluctuating emergency patient arrivals, cause many of these swings in patient load and, therefore, swings in the nursing workload.
Here is what the science says: management-induced variation happens when a hospital schedules an inconsistent number of elective admissions; for example, scheduling 20 patients on Monday and three on Tuesday. It also happens when a hospital puts patients in the wrong places, admitting patients to inappropriate hospital wards or keeping patients longer than necessary. For example, placing less sick patients in the ICU or into other monitored beds instead of a regular bed artificially increases demand for nursing care. Such misuse of nurses due to unwise management decisions is widespread.
The proper solution to the staffing problem is to streamline the use of nursing resources. Doing exactly that in many hospitals has led to increased patient and nurse satisfaction, significant quality improvements, and reduced costs, all at the same time. For example, by smoothing patient flow, Cincinnati Children’s Hospital was able to increase the number of patients treated, while using fewer nurse-staffed beds than expected. By leveling scheduled admissions, they were able to avoid building and staffing 75 new inpatient beds, thereby reducing the need for additional nurses and saving millions. In Boston Medical Center’s step down unit, smoothing eliminated 55 percent of peaks and valleys, thereby efficiently utilizing and freeing up nursing resources and saving $130,000 annually in one unit alone. A safety-net hospital in New Jersey, Newark Beth Israel Medical Center, significantly freed up nurses, reduced patient length of stay, and reduced emergency department wait time for monitored beds by 500 percent, just by introducing proper patient admission/discharge criteria, making sure that patients were in the right places for their medical needs.
The conflict surrounding Question 1 incorrectly assumes that the current state of health care delivery is unchangeable. That forces us into an unfortunate (and unnecessarily limited) choice between sub-optimal care and unaffordable care. Neither a yes nor a no vote on Question 1 will resolve the dilemma between nurse overloading and health care cost. The real solution is to reduce artificial fluctuations in nurse workload through better management of elective care and patient flow. Doing that would help both sides to achieve their common goal — safe nurse staffing and affordable care — at the same time. Not doing so will cause Question 1 to haunt future ballots.
Eugene Litvak is president of the nonprofit Institute for Healthcare Optimization and an adjunct professor at the Harvard School of Public Health.