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Simulation based process improvement...

Gao, Zhanting.

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Simulation based process improvement and staffing optimization for care management system.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Simulation based process improvement and staffing optimization for care management system./
作者:	Gao, Zhanting.
面頁冊數:	102 p.
附註:	Source: Masters Abstracts International, Volume: 54-06.
Contained By:	Masters Abstracts International54-06(E).
標題:	Industrial engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1593824
ISBN:	9781321901375

Simulation based process improvement and staffing optimization for care management system.
Gao, Zhanting.

Simulation based process improvement and staffing optimization for care management system. - 102 p.

Source: Masters Abstracts International, Volume: 54-06.

Thesis (M.S.)--State University of New York at Binghamton, 2015.

Currently, unstandardized processes and waste of resources are common in care management. It is critical to systematically investigate care management processes and remove wastes in order to build capacity and prepare for population expansion. This research develops a transformation model to standardize processes, optimize staffing level and minimize cost.

ISBN: 9781321901375Subjects--Topical Terms:

526216
Industrial engineering.

Simulation based process improvement and staffing optimization for care management system.
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245 1 0 $a Simulation based process improvement and staffing optimization for care management system.
300 $a 102 p.
500 $a Source: Masters Abstracts International, Volume: 54-06.
500 $a Adviser: Mohammad T. Khasawneh.
502 $a Thesis (M.S.)--State University of New York at Binghamton, 2015.
520 $a Currently, unstandardized processes and waste of resources are common in care management. It is critical to systematically investigate care management processes and remove wastes in order to build capacity and prepare for population expansion. This research develops a transformation model to standardize processes, optimize staffing level and minimize cost.
520 $a In this research, four models are designed and simulated in ARENA. Compare with current model, current optimization model achieves greater cost reduction and higher staff utilization. For future model, it accomplishes significant capacity gain, but the achievements on cost reduction and utilization are less significant. As the result, future optimization model obtains largest capacity gain (2.31%), greatest cost reduction (44.43%) and highest utilization (93.43%). Additionally, the scale of contribution from staffing optimization is more significant than that from process improvement. In the end, population expansion model is built to provide a capacity-planning tool for incoming care demand.
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650 4 $a Health care management. $3 2122906
650 4 $a Systems science. $3 3168411
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710 2 $a State University of New York at Binghamton. $b Systems Science Industrial Engineering. $3 2104041
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793 $a English
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