The Application of Model-Based Systems Engineering to Rural Healthcare System Disaster Planning: A Scoping Review

被引:3
作者
Berg, Thomas A. [1 ]
Marino, Kelsi N. [1 ]
Kintziger, Kristina W. [2 ]
机构
[1] Univ Tennessee Knoxville, Coll Nursing, Knoxville, TN 37966 USA
[2] Univ Nebraska Med Ctr, Coll Publ Hlth, Omaha, NE 68198 USA
关键词
Computer simulation; Disaster preparedness; Model-based systems engineering; Rural healthcare; Systems thinking; PUBLIC-HEALTH; SIMULATION; PREPAREDNESS; RESILIENCE; TOOL;
D O I
10.1007/s13753-023-00492-z
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Disasters and other emergency events have complex effects on human systems, particularly if the events are severe or prolonged. When these types of events happen in rural communities, the resources of the local public health, healthcare, and emergency response organizations can be quickly depleted or overwhelmed. Planning for emergencies can help to mitigate their impact. Model-based systems engineering (MBSE) methods, including computer simulations, can provide insight on how best to prepare for these events and to explore the effects of varying approaches and resource utilization. To best apply these methods for improving disaster management in rural settings, a synthesis of the current body of evidence in this field is needed. The objective of this scoping review was to provide a descriptive overview of the application of computer simulation based on MBSE approaches to disaster preparedness and response for rural healthcare systems. Six studies met inclusion criteria, and varied in terms of MBSE method used, healthcare setting, and disaster type and context considered. We identified a gap in the research regarding the application of MBSE approaches to support rural healthcare disaster preparedness planning efforts. Model-based systems engineering and systems thinking, therefore, represent novel methods for developing tools and computational simulations that could assist rural communities better prepare for disasters.
引用
收藏
页码:357 / 368
页数:12
相关论文
共 53 条
[1]   A simulation modelling toolkit for organising outpatient dialysis services during the COVID-19 pandemic [J].
Allen, Michael ;
Bhanji, Amir ;
Willemsen, Jonas ;
Dudfield, Steven ;
Logan, Stuart ;
Monks, Thomas .
PLOS ONE, 2020, 15 (08)
[2]  
American Hospital Association, 2022, Rural hospital closures threaten access: Solutions to preserve care in local communities
[3]   Simulation as a tool to assess the vulnerability of the operation of a health care facility [J].
Arboleda, Carlos A. ;
Abraham, Dulcy M. ;
Lubitz, Robert .
JOURNAL OF PERFORMANCE OF CONSTRUCTED FACILITIES, 2007, 21 (04) :302-312
[4]  
Arksey H., 2005, INT J SOC RES METHOD, V8, P19, DOI [10.1080/1364557032000119616, DOI 10.1080/1364557032000119616]
[5]  
Benkacem A., 2022, 2022 14 INT C LOG SU
[6]  
Carmichael T., 2019, Complex Adaptive Systems, P1, DOI [DOI 10.1007/978-3-030-20309-2_1, DOI 10.1007/978-3-030-20309-21]
[7]   Effective plans for hospital system response to earthquake emergencies [J].
Ceferino, Luis ;
Mitrani-Reiser, Judith ;
Kiremidjian, Anne ;
Deierlein, Gregory ;
Bambaren, Celso .
NATURE COMMUNICATIONS, 2020, 11 (01)
[8]   A model of nursing as a complex adaptive system [J].
Chaffee, Mary W. ;
McNeill, Margaret M. .
NURSING OUTLOOK, 2007, 55 (05) :232-241
[9]   Changes in economic outcomes before and after rural hospital closures in the United States: A difference-in-differences study [J].
Chatterjee, Paula ;
Lin, Yuqing ;
Venkataramani, Atheendar S. .
HEALTH SERVICES RESEARCH, 2022, 57 (05) :1020-1028
[10]  
Chovatiya M., 2019, 2019 3 INT C TRENDS