ArticleHeliyon2024
Home health care nurse routing and scheduling problem considering ergonomic risk factors.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Home health care routing and scheduling is a complex problem that requires many aspects to be considered simultaneously. One of the important aspects is ergonomics. Home health care nurses are at higher risk of work-related health problems such as musculoskeletal disorders and burnout since they are frequently exposed to physical, mental, and environmental ergonomic risks in their jobs. Therefore, it is essential to integrate ergonomic considerations into the construction of daily schedules for home health care nurses to mitigate these health risks. The purpose of this study is to present a mathematical model that incorporate ergonomic risks. We introduce a set of constraints into our model to prevent nurses from encountering excessive workloads. To assess the workload, we propose a subjective assessment method and employ a fuzzy inference system to calculate nurses' perceived workload levels. We applied our model to a several numerical examples to investigate the impact of workload on the nurse daily schedules. We observed that, at a specified workload level, there may be alternative solutions where the number of patients visited is the same. Therefore, we defined an objective function to maximize patient visits while minimizing nurses' workload levels as much as possible. As a result, our model generates solutions that effectively reduce nurse workloads, leading to more balanced schedules. Thus, our study offers a comprehensive approach to home health care scheduling by incorporating ergonomic considerations, ultimately enhancing both patient care and nurse well-being.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.