دورية أكاديمية
أعرض في EDS

Closure simulation for reduction of emergency patient diversion: a discrete agent-based simulation approach to minimizing ambulance diversion.

التفاصيل البيبلوغرافية
العنوان: Closure simulation for reduction of emergency patient diversion: a discrete agent-based simulation approach to minimizing ambulance diversion.
المؤلفون: Pförringer D; Klinik und Poliklinik für Unfallchirurgie, Klinikum rechts der Isar, Technische Universität München, Ismaninger Str. 22, 81675, Munich, Germany. Dominik.Pfoerringer@mri.tum.de., Breu M; Klinik und Poliklinik für Unfallchirurgie, Klinikum rechts der Isar, Technische Universität München, Ismaninger Str. 22, 81675, Munich, Germany.; TUM School of Management, Technische Universität München, Arcisstr. 21, 80333, Munich, Germany., Crönlein M; Klinik und Poliklinik für Unfallchirurgie, Klinikum rechts der Isar, Technische Universität München, Ismaninger Str. 22, 81675, Munich, Germany., Kolisch R; TUM School of Management, Technische Universität München, Arcisstr. 21, 80333, Munich, Germany., Kanz KG; Klinik und Poliklinik für Unfallchirurgie, Klinikum rechts der Isar, Technische Universität München, Ismaninger Str. 22, 81675, Munich, Germany.
المصدر: European journal of medical research [Eur J Med Res] 2018 Jun 08; Vol. 23 (1), pp. 32. Date of Electronic Publication: 2018 Jun 08.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: BioMed Central Country of Publication: England NLM ID: 9517857 Publication Model: Electronic Cited Medium: Internet ISSN: 2047-783X (Electronic) Linking ISSN: 09492321 NLM ISO Abbreviation: Eur J Med Res Subsets: MEDLINE
أسماء مطبوعة: Publication: Jan. 2012- : London : BioMed Central
Original Publication: Munich, Germany : I. Holzapfel, c1995-
مواضيع طبية MeSH: Ambulance Diversion* , Computer Simulation* , Crowding*, Ambulances/*organization & administration , Bed Occupancy/*statistics & numerical data , Emergency Medical Services/*standards , Emergency Service, Hospital/*organization & administration, Ambulances/statistics & numerical data ; Humans ; Time Factors
مستخلص: Background: The city of Munich uses web-based information system IVENA to promote exchange of information regarding hospital offerings and closures between the integrated dispatch center and hospitals to support coordination of the emergency medical services. Hospital crowding resulting in closures and thus prolonged transportation time poses a major problem. An innovative discrete agent model simulates the effects of novel policies to reduce closure times and avoid crowding.
Methods: For this analysis, between 2013 and 2017, IVENA data consisting of injury/disease, condition, age, estimated arrival time and assigned hospital or hospital-closure statistics as well as underlying reasons were examined. Two simulation experiments with three policy variations are performed to gain insights on the influence of diversion policies onto the outcome variables.
Results: A total of 530,000+ patients were assigned via the IVENA system and 200,000+ closures were requested during this time period. Some hospital units request a closure on more than 50% of days. The majority of hospital closures are not triggered by the absolute number of patient arrivals, but by a sudden increase within a short time period. Four of the simulations yielded a specific potential for shortening of overall closure time in comparison to the current status quo.
Conclusion: Effective solutions against crowding require common policies to limit closure status periods based on quantitative thresholds. A new policy in combination with a quantitative arrival sensor system may reduce closing hours and optimize patient flow.
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فهرسة مساهمة: Keywords: Ambulance; Closure policy; Crowding; Dispatch; Diversion; Emergency medical services; Simulation
تواريخ الأحداث: Date Created: 20180610 Date Completed: 20190116 Latest Revision: 20190116
رمز التحديث: 20240628
مُعرف محوري في PubMed: PMC5994037
DOI: 10.1186/s40001-018-0330-0
PMID: 29884227
قاعدة البيانات: MEDLINE
الوصف
تدمد:2047-783X
DOI:10.1186/s40001-018-0330-0