Evidence map›Paper›PMID 38057787›Full record

ArticleBMC nursing2023

Construction and application of a nursing human resource allocation model based on the case mix index.

Yanying Yang, Mei He, Yuwei Yang, Qiong Liu, Hongmei Liu, Xi Chen, Wanchen Wu, Jing Yang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC nursing, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Yanying Yang *Nursing 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.
Mei HeNursing Department, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, 621000, People's Republic of China. hemei2022520@163.com.
Yuwei YangDepartment of Laboratory Medicine, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, 621000, People's Republic of China. yyw318@sc-mch.cn.
Qiong Liu *Nursing Department, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, 621000, People's Republic of China.
Hongmei LiuNursing Department, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, 621000, People's Republic of China.
Xi ChenDepartment of Hepatobiliary Surgery, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, 621000, People's Republic of China.
Wanchen WuDepartment of Hepatobiliary Surgery, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, 621000, People's Republic of China.
Jing YangDepartment of Hepatobiliary Surgery, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, 621000, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 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.

methodsTwo 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.

resultsThe 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*CMI

conclusionThe 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.

Indexed as

Allocation of nursing resourcesCase mix indexDaily nursing worktime

Identifiers

PMID38057787
PMCPMC10698983

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.