Construction and application of a nursing human resource allocation model based on the case mix index
Abstract 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...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-12-01
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| Series: | BMC Nursing |
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| Online Access: | https://doi.org/10.1186/s12912-023-01632-y |
| _version_ | 1827590604003999744 |
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| author | Yanying Yang Mei He Yuwei Yang Qiong Liu Hongmei Liu Xi Chen Wanchen Wu Jing Yang |
| author_facet | Yanying Yang Mei He Yuwei Yang Qiong Liu Hongmei Liu Xi Chen Wanchen Wu Jing Yang |
| author_sort | Yanying Yang |
| collection | DOAJ |
| description | Abstract 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 (R 2 = 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. |
| first_indexed | 2024-03-09T01:19:10Z |
| format | Article |
| id | doaj.art-085e54b99e65457f9a303bb93e9e23c4 |
| institution | Directory Open Access Journal |
| issn | 1472-6955 |
| language | English |
| last_indexed | 2024-03-09T01:19:10Z |
| publishDate | 2023-12-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Nursing |
| spelling | doaj.art-085e54b99e65457f9a303bb93e9e23c42023-12-10T12:13:00ZengBMCBMC Nursing1472-69552023-12-0122111010.1186/s12912-023-01632-yConstruction and application of a nursing human resource allocation model based on the case mix indexYanying Yang0Mei He1Yuwei Yang2Qiong Liu3Hongmei Liu4Xi Chen5Wanchen Wu6Jing Yang7Nursing Department, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of ChinaNursing Department, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of ChinaDepartment of Laboratory Medicine, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of ChinaNursing Department, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of ChinaNursing Department, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of ChinaDepartment of Hepatobiliary Surgery, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of ChinaDepartment of Hepatobiliary Surgery, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of ChinaDepartment of Hepatobiliary Surgery, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of ChinaAbstract 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 (R 2 = 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.https://doi.org/10.1186/s12912-023-01632-yCase mix indexAllocation of nursing resourcesDaily nursing worktime |
| spellingShingle | Yanying Yang Mei He Yuwei Yang Qiong Liu Hongmei Liu Xi Chen Wanchen Wu Jing Yang Construction and application of a nursing human resource allocation model based on the case mix index BMC Nursing Case mix index Allocation of nursing resources Daily nursing worktime |
| title | Construction and application of a nursing human resource allocation model based on the case mix index |
| title_full | Construction and application of a nursing human resource allocation model based on the case mix index |
| title_fullStr | Construction and application of a nursing human resource allocation model based on the case mix index |
| title_full_unstemmed | Construction and application of a nursing human resource allocation model based on the case mix index |
| title_short | Construction and application of a nursing human resource allocation model based on the case mix index |
| title_sort | construction and application of a nursing human resource allocation model based on the case mix index |
| topic | Case mix index Allocation of nursing resources Daily nursing worktime |
| url | https://doi.org/10.1186/s12912-023-01632-y |
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