Abstract

Hospitals traditionally segregate resources into centralized functional departments such as diagnostic departments, ambulatory care centers, and nursing wards. In recent years this organizational model has been challenged by the idea that higher quality of care and efficiency in service delivery can be achieved when services are organized around patient groups. Examples include specialized clinics for breast cancer patients and clinical pathways for diabetes patients. Hospitals are struggling with the question of whether to become more centralized to achieve economies of scale or more decentralized to achieve economies of focus. In this paper we examine service and patient group characteristics to study the conditions where a centralized model is more efficient, and conversely, where a decentralized model is more efficient. This relationship is examined analytically with a queuing model to determine themost influential factors and then with simulation to fine-tune the results. The tradeoffs between economies of scale and economies of focus measured by these models are used to derive general management guidelines.
Original languageUndefined
Pages (from-to)371-390
Number of pages20
JournalOR Spectrum = OR Spektrum
Volume34
Issue number2
DOIs
Publication statusPublished - 2012

Keywords

  • Slotted Queueing Model
  • Simulation
  • Resource pooling
  • Health care modelling
  • METIS-269656
  • IR-79968
  • Focused factories
  • EWI-18600

Cite this

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title = "Efficiency evaluation for pooling resources in health care",
abstract = "Hospitals traditionally segregate resources into centralized functional departments such as diagnostic departments, ambulatory care centers, and nursing wards. In recent years this organizational model has been challenged by the idea that higher quality of care and efficiency in service delivery can be achieved when services are organized around patient groups. Examples include specialized clinics for breast cancer patients and clinical pathways for diabetes patients. Hospitals are struggling with the question of whether to become more centralized to achieve economies of scale or more decentralized to achieve economies of focus. In this paper we examine service and patient group characteristics to study the conditions where a centralized model is more efficient, and conversely, where a decentralized model is more efficient. This relationship is examined analytically with a queuing model to determine themost influential factors and then with simulation to fine-tune the results. The tradeoffs between economies of scale and economies of focus measured by these models are used to derive general management guidelines.",
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author = "P.T. Vanberkel and Boucherie, {Richardus J.} and Hans, {Elias W.} and Hurink, {Johann L.} and Nelli Litvak",
note = "Open Access",
year = "2012",
doi = "10.1007/s00291-010-0228-x",
language = "Undefined",
volume = "34",
pages = "371--390",
journal = "OR Spectrum = OR Spektrum",
issn = "0171-6468",
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}

Efficiency evaluation for pooling resources in health care. / Vanberkel, P.T.; Boucherie, Richardus J.; Hans, Elias W.; Hurink, Johann L.; Litvak, Nelli.

In: OR Spectrum = OR Spektrum, Vol. 34, No. 2, 2012, p. 371-390.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Efficiency evaluation for pooling resources in health care

AU - Vanberkel, P.T.

AU - Boucherie, Richardus J.

AU - Hans, Elias W.

AU - Hurink, Johann L.

AU - Litvak, Nelli

N1 - Open Access

PY - 2012

Y1 - 2012

N2 - Hospitals traditionally segregate resources into centralized functional departments such as diagnostic departments, ambulatory care centers, and nursing wards. In recent years this organizational model has been challenged by the idea that higher quality of care and efficiency in service delivery can be achieved when services are organized around patient groups. Examples include specialized clinics for breast cancer patients and clinical pathways for diabetes patients. Hospitals are struggling with the question of whether to become more centralized to achieve economies of scale or more decentralized to achieve economies of focus. In this paper we examine service and patient group characteristics to study the conditions where a centralized model is more efficient, and conversely, where a decentralized model is more efficient. This relationship is examined analytically with a queuing model to determine themost influential factors and then with simulation to fine-tune the results. The tradeoffs between economies of scale and economies of focus measured by these models are used to derive general management guidelines.

AB - Hospitals traditionally segregate resources into centralized functional departments such as diagnostic departments, ambulatory care centers, and nursing wards. In recent years this organizational model has been challenged by the idea that higher quality of care and efficiency in service delivery can be achieved when services are organized around patient groups. Examples include specialized clinics for breast cancer patients and clinical pathways for diabetes patients. Hospitals are struggling with the question of whether to become more centralized to achieve economies of scale or more decentralized to achieve economies of focus. In this paper we examine service and patient group characteristics to study the conditions where a centralized model is more efficient, and conversely, where a decentralized model is more efficient. This relationship is examined analytically with a queuing model to determine themost influential factors and then with simulation to fine-tune the results. The tradeoffs between economies of scale and economies of focus measured by these models are used to derive general management guidelines.

KW - Slotted Queueing Model

KW - Simulation

KW - Resource pooling

KW - Health care modelling

KW - METIS-269656

KW - IR-79968

KW - Focused factories

KW - EWI-18600

U2 - 10.1007/s00291-010-0228-x

DO - 10.1007/s00291-010-0228-x

M3 - Article

VL - 34

SP - 371

EP - 390

JO - OR Spectrum = OR Spektrum

JF - OR Spectrum = OR Spektrum

SN - 0171-6468

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