Daily scheduling of caregivers with stochastic times

Yuan, Biao; Liu, Ran; Jiang, Zhibin

doi:10.1080/00207543.2018.1445879

Cited by 23 publications

(14 citation statements)

References 31 publications

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“…We found that the OR literature concerning HHC remains dominated by papers proposing models and solution methods for combinations of operational decisions concerning the rostering of staff, the allocation of staff to patient visits, the scheduling of visits and the routing of staff. Previous reviews (Ciss e et al, 2017 andHirsch, 2017) have suggested a need for more stochastic formulations in such models and our review found that recent work has indeed incorporated stochastic patient demand, staff travel times and service times (for instance Shi et al, 2017aShi et al, , 2017bShi et al, , 2018Yuan et al, 2018;Cappanera et al, 2018). Other advances since previous reviews include moves to explore alternative approaches to the multiple aspects of system performance acknowledged to be important in HHC, with for instance Liu et al (2018) and Carello et al (2018) using multi-objective optimisation, as suggested by Ciss e et al 2017.…”

Section: Discussionmentioning

confidence: 71%

“…Analytical derivation of optimal solution Genetic algorithm (Shi et al, 2017b) Simulated annealing (Shi et al, 2018) Branch and price (Yuan et al, 2015;Yuan et al, 2018) Not specified -commercially available software Errarhout et al, 2016) Cardinality-constrained approach (n ¼ 2)…”

Section: Or Approaches In Hhcmentioning

confidence: 99%

“…Genetic algorithm (Shi et al, 2017b) Simulated annealing (Shi et al, 2018) Branch and price (Yuan et al, 2015;Yuan et al, 2018) Coordination with other home care services (n ¼ 4) (Mixed-)integer programming (n ¼ 4)…”

Section: Approaches From the Non-hhc Literaturementioning

confidence: 99%

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Operational research applied to decisions in home health care: A systematic literature review

Grieco

Utley²,

Crowe

2020

Journal of the Operational Research Society

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The efficient deployment of resources in home-based care is considered crucial for the sustainability of health and social care systems worldwide. The aim of this study was to identify and review operational research approaches to support decision-making in home health care. We identified a set of linked decisions at different planning levels (strategic, tactical, operational) and conducted a systematic review of operational research approaches used to address these decisions. We also sampled OR literature applied to analogous decisions in other settings. The 77 papers selected focused predominantly on solutions for staff-to-patient allocation, visit scheduling and staff routing, few of which were adopted by organisations. Few studies dealt with tactical decisions of team size and composition or strategic decisions of districting, and we found no studies on contract design for commissioning home health care, on staff role definitions or on reassessment of patient need. Integrative work is scarce and the aspects of system performance considered are variable and diverse. For these reasons the literature does not provide guidance for home health care services aspiring to effective and coherent decisions across planning levels. OR approaches from other areas of application provide some insights for future research aimed at addressing this shortfall.

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Section: Discussionmentioning

confidence: 71%

Section: Or Approaches In Hhcmentioning

confidence: 99%

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Operational research applied to decisions in home health care: A systematic literature review

Grieco

Utley²,

Crowe

2020

Journal of the Operational Research Society

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“…Each task is necessarily performed for a certain duration, which can be requested using either a fixed constant ( Cappanera et al, 2018 , Gomes and Ramos, 2019 , Liu et al, 2017 , Maya Duque et al, 2015 ) or a flexible range ( Mosquera et al, 2019 ). Yuan et al, 2018 , Shi et al, 2018 assume that the service duration is a random variable with known probability distributions, while Shi et al (2019) describe an uncertainty set for the service duration. Mosquera et al (2019) define the lower and upper bound of the duration (

) for each visit t , such that a visit always has a minimum and maximum duration of

and

time units, respectively.…”

Section: Literature Reviewmentioning

confidence: 99%

Matching daily home health-care demands with supply in service-sharing platforms

Lin

Ying

2021

Transportation Research Part E: Logistics and Transportation Re

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Highlights Match daily home health-care demand with supply on service-sharing platforms. Develop an effective branch-and-price approach for the daily matching problem. Consider factors such as flexible service duration, break, and temporal dependency. Analyze four matching strategies in different stages for service-sharing platforms.

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“…In their solution approach, a label-correcting algorithm is applied to the lunch break constraints and in the column generation process, some acceleration strategies are used, as well. Yuan et al (2018) proposed a daily HHCRSP with considering non-deterministic travel and service times. These assumptions are derived from possible changes in the patient health status and road traffic conditions that are valid in the practical world of HHC.…”

Section: Introductionmentioning

confidence: 99%

A Bi-Objective Home Health Care Routing and Scheduling Model with Considering Nurse Downgrading Costs

Khodabandeh

Kayvanfar

Rafiee

et al. 2020

Preprint

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In recent years, the management of health systems is a main concern of governments and decision makers. Home health care is one of the newest methods of providing services to patients in developed societies that can respond to the individual lifestyle of modern age and the increase of life expectancy. The home health care routing and scheduling problem is a generalized version of the vehicle routing problem, which is extended to a complex problem by adding special features and constraints of health care problems. In this problem, there are multiple stakeholders such as nurses for which an increase of their satisfaction level is very important. In this study, a mathematical model is developed to expand traditional home health care routing and scheduling models to downgrading cost aspects by adding the objective of minimizing the difference between the actual and potential skills of the nurses. Downgrading can lead to a dissatisfaction of the nurses. In addition, skillful nurses have higher salaries and high-level services increase equipment costs and need more expensive trainings and nursing certificates. Therefore, downgrading can enforce hidden huge costs to the managers of a company. To solve the bi-objective model, an -constraint based approach is suggested and the model applicability and its ability to solve the problem in various sizes are discussed. A sensitivity analysis on the Epsilon parameter is conducted to analyze the effect of this parameter on the problem. Finally, some managerial insights are presented to help the managers in this field, and some directions for future studies are mentioned as well.

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Daily scheduling of caregivers with stochastic times

Cited by 23 publications

References 31 publications

Operational research applied to decisions in home health care: A systematic literature review

Operational research applied to decisions in home health care: A systematic literature review

Matching daily home health-care demands with supply in service-sharing platforms

A Bi-Objective Home Health Care Routing and Scheduling Model with Considering Nurse Downgrading Costs

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