Patient acuity profiles can keep you on budget
December 1, 1999 5 minutes read
Patient acuity profiles can keep you on budget
Nurse staffing forecast scans past patient data
Administrators are beating on your door, demanding that you justify your nursing budget. But patient assessments don’t seem to follow any set pattern. Lengths of stay (LOS) are dropping. Yet, your new admissions seem to be more acutely ill than ever and require closer nursing care.
In that environment, "ICU managers really have to know what their staffs are doing and be able to translate that activity into hard numbers," says Donna Diers, RN, MSN, a professor at Yale University School of Nursing in New Haven, CT, and an expert on nurse resource utilization.
A nursing assignment forecasting system based on retrospective patient data can help make the job a lot easier for you and your charge nurses, Diers recommends.
For those who believe that patient acuity-based nursing assignments are more art than science, nurses at some hospitals are proving that you can make justifiable predictions of nursing needs for a specific time period.
Either because there isn’t time or no one has taken the initiative, many ICUs tend to "fly by the seat of their pants" when determining actual nursing utilization, she concludes. "They can’t seem to justify their nursing assignments at the end of each month."
Trend reporting assesses nursing needs
Of course, deciding on how many nurses to assign to individual patients is still partly a function of department policy and how busy things get in the ICU. The number of patients needing one-on-one care and the overall supply of available nurses are also factors.
However, nurses at Yale-New Haven Hospital’s 18-bed cardiothoracic ICU (CTICU) have been using a simple patient trend-reporting system that has helped in predicting appropriate short-term nursing utilization.
By using a shift management report, managers can determine the number of needed nursing hours by patient census based on actual nursing requirements on each shift, says Carol Just, RN, CCRN, patient services manager for the CTICU stepdown.
The monthly report gives an accurate snapshot of times when the unit was overstaffed or understaffed based on patient census figures, and clinical acuity profiles derived from the patient records, Just says.
It helps charge nurses on each shift to adjust nursing coverage by patient acuity for each month and aids managers in setting nursing budgets realistically based on actual short-term need, she adds.
"You can see by looking at the report how far off-budget yours were compared with actual [nursing] hours. It also helps to pinpoint areas of nonproductive hours, and helps managers plan training and education periods," Just explains.
Graphs help in analysis
Based on the report, managers are expected to submit an explanation to administration whenever actual hours depart from budgeted hours by 5% or more. The report is often converted into a graph for easy analysis. (See charts, p. 137.) However, Just emphasizes that the monthly shift management report is simply one of many tools for improving resource utilization.
The key, according to Diers, is to track nursing performance by documenting the amount of nursing resources needed for a particular set of patient acuities. "By looking at your performance retrospectively, you can set targets intelligently and justify your resource needs into the future," she explains.
However, using those tools requires ample background data. Making reasonable nursing assignment decisions is always hampered by patient mix. Therefore, Diers recommends collecting a year’s worth of patient ICU-related DRG (diagnosis-related group) data to help determine long-term patterns in patient acuity. The DRGs can provide clues regarding patient mix in a specific month or a three-month period. They can reveal the types of patients you are admitting, their complications, and the number of nursing hours they are likely to require on each shift, Diers says.
Once you’ve analyzed the DRGs, you can begin to calculate your nursing requirements within specific blocks of time, even down to a particular shift, she adds. In addition, your unit’s ADT (admission, discharge, and transfer) data will provide the other half of the needed information, including the average length of stay per DRG, and the level of nursing intensity required of each DRG per LOS, Just says.
The hospital’s OR schedule can reinforce information regarding the number of expected admissions and help in planning timely transfers in a day. The information can then help in setting budgets and sticking to them, Diers says.
This use for patient profiling helps, particularly in open-heart surgery units where patients are admitted directly from the operating room and typically require one-on-one nursing coverage for at least six hours, says Just.
Large ICUs with several private rooms and a highly variable patient mix will also find profiling effective. At Yale-New Haven, managers also use the patient profiling in training recent nursing graduates on setting patient-care priorities and gauging their own bedside techniques according to acuity, adds Just.
In fact, 800-bed Yale-New Haven was the site of a novel research project in the adult ICU that compared levels of nursing intensity with case mix-related clinical and financial information to explain trends and variances in nursing utilization.1 What came out of the study was a case mix-related nursing classification system that focused on six levels of nursing care requirements.
Information can identify staffing trend
The levels were a breakdown of relative time weightings defined as hours of nursing care required per patient day in both the adult non-ICU and adult ICU patient population with the same DRGs (pediatric and neonatal ICUs were not studied). For example, the study found that 34 ICU-related DRGs achieved a weighting of 10, which means those cases required an average of 10 hours of nursing care per patient day. In comparison, 93 DRGs achieved a 10 weighting in the non-ICU departments.
The actual DRGs in the comparisons were not specified and not construed by investigators as being either similar or the same. The weightings were then multiplied by the number of patients in that DRG category on that unit on that day. Payroll and nursing schedule data for that time period were selected, excluding the managers’ and assistant managers’ time and pay. The resulting information painted a "clinical picture" of patients by DRGs that permits managers to budget according to acuity, the report stated.
In their summary, the authors concluded that the "solution to the problem of the work being harder is not necessarily increasing the number of staff members," which would mean spending more money. Rather, the solution, the study suggests, lies in using information to better understand trends and changes and target for the future, Diers says.
"Those closest to the work must understand and manage it before those farthest away [payers] try to manage the work for us," the authors concluded.
Reference
1. Diers D, Bozzo J, Blatt L. Understanding nursing resources in intensive care: A case study. Am J Crit Care 1998; 7:143-148.
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