Literature DB >> 26310949

StratBAM: A Discrete-Event Simulation Model to Support Strategic Hospital Bed Capacity Decisions.

Priyantha Devapriya1, Christopher T B Strömblad, Matthew D Bailey, Seth Frazier, John Bulger, Sharon T Kemberling, Kenneth E Wood.   

Abstract

The ability to accurately measure and assess current and potential health care system capacities is an issue of local and national significance. Recent joint statements by the Institute of Medicine and the Agency for Healthcare Research and Quality have emphasized the need to apply industrial and systems engineering principles to improving health care quality and patient safety outcomes. To address this need, a decision support tool was developed for planning and budgeting of current and future bed capacity, and evaluating potential process improvement efforts. The Strategic Bed Analysis Model (StratBAM) is a discrete-event simulation model created after a thorough analysis of patient flow and data from Geisinger Health System's (GHS) electronic health records. Key inputs include: timing, quantity and category of patient arrivals and discharges; unit-level length of care; patient paths; and projected patient volume and length of stay. Key outputs include: admission wait time by arrival source and receiving unit, and occupancy rates. Electronic health records were used to estimate parameters for probability distributions and to build empirical distributions for unit-level length of care and for patient paths. Validation of the simulation model against GHS operational data confirmed its ability to model real-world data consistently and accurately. StratBAM was successfully used to evaluate the system impact of forecasted patient volumes and length of stay in terms of patient wait times, occupancy rates, and cost. The model is generalizable and can be appropriately scaled for larger and smaller health care settings.

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Year:  2015        PMID: 26310949     DOI: 10.1007/s10916-015-0325-0

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  13 in total

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3.  Myths of ideal hospital occupancy.

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Journal:  Health Care Manag Sci       Date:  2005-08

5.  Dynamics of bed use in accommodating emergency admissions: stochastic simulation model.

Authors:  A Bagust; M Place; J W Posnett
Journal:  BMJ       Date:  1999-07-17

6.  The impact of inpatient boarding on ED efficiency: a discrete-event simulation study.

Authors:  Aaron E Bair; Wheyming T Song; Yi-Chun Chen; Beth A Morris
Journal:  J Med Syst       Date:  2009-05-15       Impact factor: 4.460

Review 7.  Systematic review of the use of computer simulation modeling of patient flow in surgical care.

Authors:  Boris G Sobolev; Victor Sanchez; Christos Vasilakis
Journal:  J Med Syst       Date:  2009-07-07       Impact factor: 4.460

8.  Improving patient flow in an obstetric unit.

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Journal:  J Med Syst       Date:  2009-02       Impact factor: 4.460

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Journal:  J Med Syst       Date:  2008-10       Impact factor: 4.460

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  11 in total

1.  A Discrete Event Simulation Model of Patient Flow in a General Hospital Incorporating Infection Control Policy for Methicillin-Resistant Staphylococcus Aureus (MRSA) and Vancomycin-Resistant Enterococcus (VRE).

Authors:  Erica S Shenoy; Hang Lee; Erin E Ryan; Taige Hou; Rochelle P Walensky; Winston Ware; David C Hooper
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2.  Simulation-Based Design of ED Operations with Care Streams to Optimize Care Delivery and Reduce Length of Stay in the Emergency Department.

Authors:  Duane Steward; Todd F Glass; Yann B Ferrand
Journal:  J Med Syst       Date:  2017-09-06       Impact factor: 4.460

3.  Optimizing nurse capacity in a teaching hospital neonatal intensive care unit.

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Journal:  Health Care Manag Sci       Date:  2016-01-04

4.  A systematic literature review of simulation models for non-technical skill training in healthcare logistics.

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5.  A Data-Driven Hybrid Three-Stage Framework for Hospital Bed Allocation: A Case Study in a Large Tertiary Hospital in China.

Authors:  Li Luo; Jialing Li; Xueru Xu; Wenwu Shen; Lin Xiao
Journal:  Comput Math Methods Med       Date:  2019-05-02       Impact factor: 2.238

6.  Rapid cancer diagnosis for patients with vague symptoms: a cost-effectiveness study.

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7.  Resource management framework using simulation modeling and multi-objective optimization: a case study of a front-end department of a public hospital in Thailand.

Authors:  Tanatorn Tanantong; Warut Pannakkong; Nittaya Chemkomnerd
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Review 8.  Discrete-Event Simulation Modeling in Healthcare: A Comprehensive Review.

Authors:  Jesús Isaac Vázquez-Serrano; Rodrigo E Peimbert-García; Leopoldo Eduardo Cárdenas-Barrón
Journal:  Int J Environ Res Public Health       Date:  2021-11-22       Impact factor: 3.390

9.  Machine learning based forecast for the prediction of inpatient bed demand.

Authors:  Manuel Tello; Eric S Reich; Jason Puckey; Rebecca Maff; Andres Garcia-Arce; Biplab Sudhin Bhattacharya; Felipe Feijoo
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10.  Using Simulation Optimization to Solve Patient Appointment Scheduling and Examination Room Assignment Problems for Patients Undergoing Ultrasound Examination.

Authors:  Ping-Shun Chen; Gary Yu-Hsin Chen; Li-Wen Liu; Ching-Ping Zheng; Wen-Tso Huang
Journal:  Healthcare (Basel)       Date:  2022-01-15
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