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Construction and application of a nursing human resource allocation model based on the case mix index
Yanying Yang1, Mei He2, Yuwei Yang3
1Nursing Department, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, 621000, People's Republic of China. 2729433618@qq.com.
Background:
The case mix index (CMI) may reflect the severity of disease and the difficulty of care objectively, and is expected to be an ideal indicator for assessing the nursing workload. The purpose of this study was to explore the quantitative relationship between daily nursing worktime (DNW) and CMI to provide a method for the rational allocation of nursing human resources.
Methods:
Two hundred and seventy-one inpatients and 36 nurses of the department of hepatobiliary surgery were prospectively included consecutively from August to September 2022. The DNW of each patient were accurately measured, and the CMI data of each patient were extracted. Among 10 curve estimations, the optimal quantitative model was selected for constructing the nursing human resource allocation model. Finally, the applicability of the allocation model was preliminarily assessed by analyzing the relationship between the relative gap in nursing human resources and patient satisfaction, as well as the incidence of adverse events in 17 clinical departments.
Results:
The median (P25, P75) CMI of the 271 inpatients was 2.62 (0.92, 4.07), which varied by disease type (F = 3028.456, P < 0.001), but not by patient gender (F = 0.481, P = 0.488), age (F = 2.922, P = 0.089), or level of care (F = 0.096, P = 0.757). The median (P25, P75) direct and indirect DNW were 76.07 (57.98, 98.85) min and 43.42 (39.42, 46.72) min, respectively. Among the 10 bivariate models, the quadratic model established the optimal quantitative relationship between CMI and DNW; DNW = 92.3 + 4.8*CMI + 2.4*CMI2 (R2 = 0.627, F = 225.1, p < 0.001). The relative gap between theoretical and actual nurse staffing in the 17 clinical departments were linearly associated with both patient satisfaction (r = 0.653, P = 0.006) and incidence of adverse events (r = - 0.567, P = 0.021). However, after adjusting for other factors, it was partially correlated only with patient satisfaction (rpartial = 0.636, P = 0.026).
Conclusion:
The DNW derived from CMI can be used to allocate nursing human resources in a rational and convenient way, improving patient satisfaction while ensuring quality and safety.
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