Abstract
Abstract Objective This paper studies the measurement indicators of nursing workload in neurology department, discusses the development and development law of nursing workload, provides scientific basis for nursing staff deployment, and guarantees high-quality and safe nursing services. Methods By using time series algorithm model, the paper calculates the nursing workload of neurology department and establishes the measurement index of nursing workload of neurology department. Improve the nursing workload information system, automatically generate and extract daily nursing workload, and construct a time series model of daily nursing workload. Results Through literature search and on-site observation, preliminary measurement of nursing workload measurement indicators, consultation with expert meetings to develop an expert consultation form for nursing workload measurement indicators, and application of SPSS 19.0 for time series analysis to construct a time series model for daily nursing workload. Results The best fit models of the time series of the two wards in neurology department were both exponential smoothing models. The predictive value of the ward A smoothing model for the total nursing workload from January 1 to 3, 2014 was 317.39. 316.14, 295.94 points (upper limit: 366.39, 375.95, 364.88 points; lower limit: 268.40, 256.33, 227.00 points). The prediction value of the B Ward Index Smoothing Model for the total nursing workload from January 1 to 3, 2014 is 450.03, 449.38, 445.58 points (upper limit: 503.76, 512.04, 515.05 points; lower limit: 396.30, 386.71, 375.11 points). Conclusion Time series analysis can predict the nursing workload on the one hand, and adjust the number of nurses on the day of work according to the short-term predicted value of the nursing workload on the time series model; on the other hand, it can evaluate the rationality of the existing manpower allocation strategy.
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