Analysis of factors related to expense budgeting for nursing services

Abstract

Scope and Method of Study: Hospital budgeting has traditional been based on the statistical variable of patient days. Hillcrest Medical Center uses this variable to project monthly expenditures. Variances of up to 34 percent for the 1972 data used in the study have resulted from using patient days. The purpose of this study was to determine whether a more appropriate variable or combination of variables existed for accurately projecting budget expenditure for nursing services. The nursing units selected for stud were a general medical unit with student nurses (2W), a general medical unit with private physicians (4S), the intensive coronary care unit (ICCU), and the psychiatric unit (ZN). A combination of several techniques was used in the study. Six variables were initially considered: patient days, patient capacity, turnover and the demographic characteristics of age, sex and race. Graphical analysis indicated that a better combination of predictor variables possibly could be obtained using multivariate techniques. Both factor analysis and multiple regression analysis were employed to screen the variables and to develop predictor equations. The use of factor analysis developed combinations of the independent or predictor variables, called factors, which combine the effects of variables which are highly intercorrelated and at the same time independent of other factors. Regression techniques were then used to obtain prediction equations, using the factors as the independent variables.

Findings and Conclusions: The results of this analysis were different for each of the four nursing units. For 2W the three factors required in the prediction equation developed were respectively "patient days-capacity," "age-sex," and "race-turnover"; for 4S the only factor required was "patient days-capacity"; for ICCU the two factors required were "patient days-capacity" and "race"; and for 2N the two factors required were "turnover-race" and "sex-patient day capacity."