目的:探讨精细化管理在儿童发热门诊输液流程中的应用效果。方法:选取2022年3月1日—6月30日在江西省儿童医院发热门诊进行静脉输液治疗的300例患儿作为对照组(实施常规管理),选取2022年7月1日—10月31日在江西省儿童医院发热门诊进行...目的:探讨精细化管理在儿童发热门诊输液流程中的应用效果。方法:选取2022年3月1日—6月30日在江西省儿童医院发热门诊进行静脉输液治疗的300例患儿作为对照组(实施常规管理),选取2022年7月1日—10月31日在江西省儿童医院发热门诊进行静脉输液治疗的300例患儿作为观察组(实施精细化管理)。比较两组患儿发热门诊诊疗时间、输液等待时间,家长满意度,护士输液工作职业倦怠感[职业倦怠感调查普适量表(Maslach burnout inventory general survey,MBI-GS)]。结果:观察组患儿发热门诊诊疗时间、输液等待时间短于对照组,家长总满意度高于对照组,护士MBI-GS的情绪疲惫感、工作冷漠感、成就感低落得分均低于对照组,差异有统计学意义(P<0.05)。结论:儿童发热门诊输液流程中应用精细化管理,能缩短患儿发热门诊诊疗时间和输液等待时间,提高家长满意度,降低护士职业倦怠感。展开更多
In this article, we develop and analyze a continuous-time Markov chain (CTMC) model to study the resurgence of dengue. We also explore the large population asymptotic behavior of probabilistic model of dengue using th...In this article, we develop and analyze a continuous-time Markov chain (CTMC) model to study the resurgence of dengue. We also explore the large population asymptotic behavior of probabilistic model of dengue using the law of large numbers (LLN). Initially, we calculate and estimate the probabilities of dengue extinction and major outbreak occurrence using multi-type Galton-Watson branching processes. Subsequently, we apply the LLN to examine the convergence of the stochastic model towards the deterministic model. Finally, theoretical numerical simulations are conducted exploration to validate our findings. Under identical conditions, our numerical results demonstrate that dengue could vanish in the stochastic model while persisting in the deterministic model. The highlighting of the law of large numbers through numerical simulations indicates from what population size a deterministic model should be considered preferable.展开更多
文摘目的:探讨精细化管理在儿童发热门诊输液流程中的应用效果。方法:选取2022年3月1日—6月30日在江西省儿童医院发热门诊进行静脉输液治疗的300例患儿作为对照组(实施常规管理),选取2022年7月1日—10月31日在江西省儿童医院发热门诊进行静脉输液治疗的300例患儿作为观察组(实施精细化管理)。比较两组患儿发热门诊诊疗时间、输液等待时间,家长满意度,护士输液工作职业倦怠感[职业倦怠感调查普适量表(Maslach burnout inventory general survey,MBI-GS)]。结果:观察组患儿发热门诊诊疗时间、输液等待时间短于对照组,家长总满意度高于对照组,护士MBI-GS的情绪疲惫感、工作冷漠感、成就感低落得分均低于对照组,差异有统计学意义(P<0.05)。结论:儿童发热门诊输液流程中应用精细化管理,能缩短患儿发热门诊诊疗时间和输液等待时间,提高家长满意度,降低护士职业倦怠感。
文摘In this article, we develop and analyze a continuous-time Markov chain (CTMC) model to study the resurgence of dengue. We also explore the large population asymptotic behavior of probabilistic model of dengue using the law of large numbers (LLN). Initially, we calculate and estimate the probabilities of dengue extinction and major outbreak occurrence using multi-type Galton-Watson branching processes. Subsequently, we apply the LLN to examine the convergence of the stochastic model towards the deterministic model. Finally, theoretical numerical simulations are conducted exploration to validate our findings. Under identical conditions, our numerical results demonstrate that dengue could vanish in the stochastic model while persisting in the deterministic model. The highlighting of the law of large numbers through numerical simulations indicates from what population size a deterministic model should be considered preferable.
