A SENSITIVITY MODEL FOR TESTING THE EFFECTS OF SELECTED VARIABLES ON PRODUCTIVITY USING ABSENTEEISM AS THE CRITERION VARIABLE: A POLICY MODEL (NURSING, HEALTH SYSTEM). - Info and Reading Options

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The purpose of the study was to develop a sensitivity model for testing the effects of selected variables on productivity, utilizing absenteeism as the criterion variable. As there were insufficient variables with significant relationships resulting from the Pearson product moment analysis, the direction of correlation for the seven variables was derived from the literature. The arbitrarily selected variables were those most germane to the nursing environment. The model demonstrates a systematic way to observe, evaluate, predict, and monitor productivity. It allows an administrator to alter the mix of staff by day, shift, unit, position, tenure, education, and marital status so as to change the productivity rate in hours, and thus, theoretically to maximize the utilization of human resources. Through sensitivity analysis (altering the values of the variables and observing the change in productivity recorded in hours), policy analysis in health care agencies can be facilitated. This could assist the administrator in recruitment, retention, and promotion of employees, and in planning schedules for nursing service. The methodology was reported in four parts. First, the systems model approach utilized for planning, implementing and evaluating the study was discussed. Second, an 11-step sensitivity model for evaluating productivity was developed. Third, the simulation technique was used to represent a replica of a system to assist decision makers in productivity evaluation prior to implementing a plan or change. Fourth, sensitivity analyses were done to determine the impact on productivity of changing selected variables. The study subjects were 228 full-time nursing service employees from a rural community hospital. Absence and personal characteristics data of the subjects were taken from records covering one year. The computer model consists of (a) a predictor formula based on a real data set, and (b) calculation to predict future productivity measured in hours. The sensitivity model consists of a computer program with which an administrator may manipulate the variables of day, unit, shift, education, position, tenure, and marital status to see the change in productivity (hours worked/hours scheduled).

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