The modern healthcare industry is extremely labor intensive. To be effective, a modern nurse manager must balance patient care vs. staffing, procedures vs. patient load, and fiscal budgets in line with appropriate levels of care. Nurses are expected not only to understand the organization's fiscal concerns, but to manage them as well. While fiscal dollars spent on human resource management are the larger portion of the health care organization's budget, the use of a cogent and powerful budgetary management tool can help save thousands on an aggregate basis.
The Budgeting Process Cycle
Any budget is essentially a planning process that focuses on expenses and activities of the organization over a given period of time. The budget is designed to help plan for resource allocation and to control expenses when possible, to schedule adjustments or larger capital purchases, and to be used as an operational plan from which to work. To adequately organize a budget, the organization must have clear lines of authority as to responsibility. Managerial support is crucial, as is nursing input. The budget processing cycle is dependent upon the organization and the breadth of responsibility the nurse has. A floor charge nurse might receive a sum from the Head of Nursing, while the Hospital's Oncology Department might sublet some of their budget to a Nurse Manager (Finkler, 2007).
In general, the standard for budgeting for nurses is known as Hours Per Patient Day, or HPPD. Being a relatively general measurement, HPPD can be broken down further into the micro (e.g. minutes in a post-operative care unit) or as needed based on the typical patient care unit. Variances do, of course occur within any organization: human resource issues (illnesses, absences, partial-performance due to injury; administrative time and meetings; core patient populations, specific trauma or emergency needs, or other non-foreseeable, but regular issues that impact time) (Redman, 2003). HPPD is calculated through input from the finance or business department. The nurse manager needs to know the number of productive hours given to their department, with the breakdown of hours charged for vacation, sick time, and other utilized, but non-medically productive, hours. Additionally, the Average Daily Census (ADC) is used, which is the number of patients (usually at midnight) multiplied by the budget standard, equally the number of care hours budgeted per day. HPPD is thus calculated by taking the productive hours of the time frame divided by the average daily census for the same time frame. In this manner, the HPPD may be calculated for any time, making it a better comparative average when dealing with departments with disparate types of patient care. So, we have:
(Productive Hours For X Time)/(Average Daily Census For X Time) = HPPD (Hall, ed. 2005, pp. 28-9).
Productive and Non-Productive Time
Productivity is measured differently depending on the job classification. Some healthcare jobs, lab technicians, for instance, might have a more quantitative format of tests/hour or tests/shift. An accounting manager might have x number of files or billables/payables per shift. For the nurse, though, most experts say the best way to increase their productivity is to increase the amount of time they spend interacting and caring for patients. Patients do better clinically when more nursing hours are devoted to them, and now that we know greater nursing hours per patient day are statistically linked with lower rates of pneumonia, blood-stream infections, and other complications, it makes sense to understand the nurse's productive role in relation to patient care (Anderson, 2007). For the nurse manager, hours worked and available for patient care are categorized as productive time, while benefit time like vacation, sick leave, and education is considered non-productive time. Direct care is part of productive time as well, that is hands-on care with or for the patient. Indirect care is time spent on activities that are patient related but not done directly to or with the patient (charting, documentation, consulting, following up on issues, etc.) (Kelly, p. 215).
Again, forecasting is dependent upon the scope of the budget, but does have some commonalities regardless of the size of the unit or project. Forecasting budgets requires information: past data, productivity ratios, amount of funding, amount of staff, projected growth or reduction of processes, and actual skill sets of staff. For example, if a unit has a shortage of nurses and has a high budgetary expense for overtime or per diem nurses, then the average cost can be brought down by hiring and eliminating overtime. Forecasting formulas are typically based on historical information, though, with projections based on percentage change. Forecasting is both qualitative and quantitative. If trends are observed, for instance, then that trend should be projected into the future. We must also remember that forecasting is not an exact science in any field, there are too many variables that cannot always be predicted (staff turnover, major environmental accidents, equipment malfunctions, etc.). However, it is typically safe to say that the demographics of contemporary America show that the aging population is trending towards more health care need, more nursing advocacy and care, and greater stakeholder expectations of that care (Finkler, et.al., 2007, Chapter 21).
Variance analysis can be statistically complex, but in general it is a way to look at data and analyze the effectiveness of budgets, schedules, and productivity. Variance, in this case, are issues that are unpredictable and unplanned that have an effect on the outcome of productivity. For instance, variance analysis would look at the hours of care per patient day by acuity level and then look at the difference between actual and budgeted caregiving hours. If the actual caregiving hours are less than the budged amount, there is a favorable variance; if less, then a negative variance. Variance analysis helps the nurse manager understand the impact of rate, volume and efficiency in the health care process. One suggested formula for finding the efficiency variance is the following: EV = (AH-BH) x BR x AV.
This illustrates also the importance of budgeting and forecasting so the efficiency model will be more accurate (Brown, ed., 1992, p. 20).
Productivity should not simply be defined in fiscal terms for healthcare. As noted, there are short-term and long-term costs and benefits. In the short-term (say the weekly budget), x nurses might spend more than the budgeted time with a particularly sensitive patient issue. However, in the long-term, that patient's stay, quality of service, and indeed likelihood of quality care and advocacy, increases -- which decreases costs later. Comparisons help nurse managers understand productivity by comparing budget forecasts to reality and then planning accordingly. Productivity is also established by maintaining a culture of accountability -- variance is part of the life in healthcare, but open and honest communication is important to mitigate negative results. Looking at expenses appropriate helps productivity; why waste time analyzing the use of 15 copies that an employee used for a personal project rather than managing waste of expensive supplies or materials within patient care? However, regular monitoring of budgets, not micromanaging, but regular and fair monitoring can call attention to issues prior to any significant problems (Clark, 2005).
Everyone in the healthcare industry is affected by rising costs and rising expectations from stakeholders regarding care. Budgeting for productivity does not have to be complicated, nor does it have to be extremely detailed. The more complex it is the more time it takes away from patient care. Realistic productivity management takes into account monitoring and realistic benchmarks; not mandates of 5 minutes per patient. Managers must be accountable so that waste does not occur, but by the same token, coming in onto budget while continuing to provide excellent care is a more balanced approach that should be rewarded. In addition, consider the dimensions of quality (cycle time through tests, x-rays, etc.)…