Healthcare system design and parttime working doctors

Molema, J. J. W.; Groothuis, Siebren; Baars, I.J.; Kleinschiphorst, M.; Leers, E. G. E.; Hasman, Arie; Merode, G.G. van

doi:10.1007/s10729-007-9032-9

Cited by 18 publications

(11 citation statements)

References 27 publications

(56 reference statements)

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“…Molema et al (2007) analysed part‐time work options for doctors. They illustrated through a simulation of two case studies that introduction of part‐time work can indeed improve service offerings and system design.…”

Section: Healthcare Management and Logisticsmentioning

confidence: 99%

“…In Sherali et al (2002), the resident on-call scheduling problem is modelled as a Mixed Integer Program and solved by heuristic procedures that exploit the network structure embedded in the model. Molema et al (2007) analysed part-time work options for doctors. They illustrated through a simulation of two case studies that introduction of part-time work can indeed improve service offerings and system design.…”

Section: Operating Room and Physician Schedulingmentioning

confidence: 99%

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Operations Research in Healthcare: a survey

Rais

Viana

2010

International Transactions in Operational Research

293

130

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Optimisation problems in Healthcare have received considerable attention for more than three decades. More recently, however, with decreasing birth rates in nearly all of the developed countries and increasing average longevity globally, optimisation issues in Healthcare have become noticeably important and attract keen interest from the Operations Research community. Over the years, attention has gradually expanded from resource allocation and strategic planning to include operational issues such as resource scheduling and treatment planning. This paper surveys several applications of Operations Research in the domain of Healthcare. In particular, the paper reviews key contributions addressing contemporary optimisation issues in this area. It highlights current research activities, focusing on a variety of optimisation problems as well as solution techniques used for solving the optimisation problems.

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Section: Healthcare Management and Logisticsmentioning

confidence: 99%

Section: Operating Room and Physician Schedulingmentioning

confidence: 99%

Operations Research in Healthcare: a survey

Rais

Viana

2010

International Transactions in Operational Research

293

130

View full text Add to dashboard Cite

show abstract

“…This involves simulation modelling of care delivery for performance improvement. Research has been conducted to simulate hospital operations for optimum resource utilization, to reduce waiting times and length of stay (LOS), to increase throughput of the care delivery processes [28] [37][38][39].…”

Section: Introductionmentioning

confidence: 99%

Pathway variation analysis (PVA): Modelling and simulations

Shukla

Lahiri

Ceglarek

2015

Operations Research for Health Care

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Maintaining a care pathway within a hospital to provide complex care to patients is associated with challenges related to variations from the pathway. This occurs due to ineffective decision-making processes, unclear process steps, the interactions, conflicting performance measures for speciality units, and the availability of resources. These variations from the care pathway or standard care delivery processes lead to longer patient waiting times and lower patient throughput. Traditional approaches to improve the pathway focus primarily on reducing variations within the care pathway such as bottlenecks or throughput within the pathway rather than examining variations from the care pathway. In this study, we propose a novel methodology, called pathway variation analysis (PVA), to identify, simulate and analyse variations from the patient care pathways. PVA method includes patient ward level journey dataset and qualitative staff interviews to simulate patient variations. The proposed methodology had been applied to the stroke care services of a hospital, which increased their key performance from 73% to 84.97%. A PVA methodology is proposed which simulated patient diversions from the care pathway by modelling hospital operational parameters, assessing the accuracy of clinical decisions and performance measures of speciality units involved. The proposed methodology can be applied to other care pathways settings to reduce patient diversion from the care pathway.

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“…On the other hand, unbalanced or understaffed nursing teams can influence the quality of care (Hurst 2003), even determining burnouts and job dissatisfaction for nurses and a higher risk of mortality for patients (Aiken et al 2002). Predicting workload over time and allocating nurses accordingly are essential for guaranteeing quality of care in a cost-effective manner (Kortbeek et al 2015;Molema et al 2007). This can be realized by means of a flexible workforce, which is considered a powerful tool to respond to variability in patient demand by many authors (Kortbeek et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Daily nurse requirements planning based on simulation of patient flows

Sarno

Nenni

2015

Flex Serv Manuf J

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Nurses account for approximately 50 % of total hospital budgets and their allocation to medical units and shifts can significantly affect the quality of care provided to patients. The adoption of flexible shift schedules and the assessment of actual nursing time can enable sensible resource planning, balancing the quality of care with efficiency in resource use. Starting from the concept that nurse requirements are triggered by patient needs, which are stochastic in nature both for clinical activities and their duration, this paper proposes an innovative Nurse Requirement Planning model grounded on the concept of the clinical pathway (the “standard” sequence of diagnostic, therapeutic and care activities a patient with certain pathology should undertake over time) with its inner routing probability and patient dependence on nurses, which can be correlated to the time needed to perform nursing tasks. In merging and modelling these two aspects, the method summarizes the best features of acuity-quality and timed-task/activity techniques, well known although not usually applied for reasons of demands on clinicians’ time. Instead, in this paper, for each shift of the day, hospital management is enabled to choose the optimal number of nurses to meet actual requirements according to a desired service level and personnel saturation by means of a tool that simulates the patient flow in a medical unit based on automatic data retrieval from hospital databases. The validation and verification of the proposal were undertaken in a stroke unit. © 2015, Springer Science+Business Media New York

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Healthcare system design and parttime working doctors

Cited by 18 publications

References 27 publications

Operations Research in Healthcare: a survey

Operations Research in Healthcare: a survey

Pathway variation analysis (PVA): Modelling and simulations

Daily nurse requirements planning based on simulation of patient flows

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