AU2021103263A4 - Optimal allocation system of medical emergency rescue resources for catastrophic emergency events - Google Patents
Optimal allocation system of medical emergency rescue resources for catastrophic emergency events Download PDFInfo
- Publication number
- AU2021103263A4 AU2021103263A4 AU2021103263A AU2021103263A AU2021103263A4 AU 2021103263 A4 AU2021103263 A4 AU 2021103263A4 AU 2021103263 A AU2021103263 A AU 2021103263A AU 2021103263 A AU2021103263 A AU 2021103263A AU 2021103263 A4 AU2021103263 A4 AU 2021103263A4
- Authority
- AU
- Australia
- Prior art keywords
- emergency
- hospital
- events
- rescue
- decision
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Ceased
Links
- 238000011160 research Methods 0.000 claims abstract description 51
- 238000004458 analytical method Methods 0.000 claims abstract description 25
- 230000004044 response Effects 0.000 claims abstract description 23
- 238000012545 processing Methods 0.000 claims abstract description 10
- 238000013480 data collection Methods 0.000 claims abstract description 8
- 230000009897 systematic effect Effects 0.000 claims abstract description 8
- 230000010365 information processing Effects 0.000 claims abstract description 4
- 238000000034 method Methods 0.000 claims description 99
- 238000007726 management method Methods 0.000 claims description 51
- 230000008878 coupling Effects 0.000 claims description 19
- 238000010168 coupling process Methods 0.000 claims description 19
- 238000005859 coupling reaction Methods 0.000 claims description 19
- 238000011156 evaluation Methods 0.000 claims description 15
- 238000011835 investigation Methods 0.000 claims description 15
- 230000007246 mechanism Effects 0.000 claims description 14
- 230000008569 process Effects 0.000 claims description 13
- 238000012549 training Methods 0.000 claims description 12
- 230000000052 comparative effect Effects 0.000 claims description 9
- 238000010276 construction Methods 0.000 claims description 7
- 238000011161 development Methods 0.000 claims description 7
- 230000006399 behavior Effects 0.000 claims description 6
- 210000004556 brain Anatomy 0.000 claims description 6
- 238000006243 chemical reaction Methods 0.000 claims description 6
- 238000010219 correlation analysis Methods 0.000 claims description 6
- 238000013278 delphi method Methods 0.000 claims description 6
- 238000013461 design Methods 0.000 claims description 6
- 239000003814 drug Substances 0.000 claims description 6
- 238000012216 screening Methods 0.000 claims description 6
- 230000008520 organization Effects 0.000 claims description 5
- 230000000694 effects Effects 0.000 claims description 4
- 239000000047 product Substances 0.000 claims description 4
- 238000012937 correction Methods 0.000 claims description 3
- 238000009792 diffusion process Methods 0.000 claims description 3
- 229940124645 emergency medicine Drugs 0.000 claims description 3
- 230000036541 health Effects 0.000 claims description 3
- 238000013332 literature search Methods 0.000 claims description 3
- 239000011159 matrix material Substances 0.000 claims description 3
- 238000010197 meta-analysis Methods 0.000 claims description 3
- 238000002360 preparation method Methods 0.000 claims description 3
- 239000013589 supplement Substances 0.000 claims description 3
- 238000005303 weighing Methods 0.000 claims description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 229920000742 Cotton Polymers 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 239000002360 explosive Substances 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 239000000383 hazardous chemical Substances 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000002195 synergetic effect Effects 0.000 description 1
- 231100000331 toxic Toxicity 0.000 description 1
- 230000002588 toxic effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B25/00—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems
- G08B25/006—Alarm destination chosen according to type of event, e.g. in case of fire phone the fire service, in case of medical emergency phone the ambulance
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06311—Scheduling, planning or task assignment for a person or group
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B27/00—Alarm systems in which the alarm condition is signalled from a central station to a plurality of substations
- G08B27/001—Signalling to an emergency team, e.g. firemen
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/20—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Health & Medical Sciences (AREA)
- Physics & Mathematics (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Economics (AREA)
- Public Health (AREA)
- Emergency Management (AREA)
- General Health & Medical Sciences (AREA)
- Biomedical Technology (AREA)
- Development Economics (AREA)
- Medical Informatics (AREA)
- Educational Administration (AREA)
- Epidemiology (AREA)
- Game Theory and Decision Science (AREA)
- Primary Health Care (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Theoretical Computer Science (AREA)
- Medical Treatment And Welfare Office Work (AREA)
Abstract
The present invention provides an optimal allocation system of medical
emergency rescue resources for catastrophic emergency events, which relates to the
technical field of medical emergency rescue. The optimal allocation system of
medical emergency rescue resources for catastrophic emergency events includes a
data collection system, a smart decision platform for information processing and
evolution law of hospital unconventional emergencies (UE), a dynamic assessment
module for rescue emergency decision under an emergency situation of the hospital
UE, a theoretical framework and system module for research and decision, a
response platform for hospital emergency management commanders, a support
auxiliary platform of hospital emergency decision for unconventional emergencies
and a rescue emergency module. The optimal allocation system of medical
emergency rescue resources for catastrophic emergency events provided by the
present invention analyzes catastrophic emergency events and correlation among the
events by means of a systematic analysis method, thereby obtaining an intrinsic law
of evolution of the catastrophic emergency events, and further making different
rescue decisions to provide scientific and effective auxiliary support for the
emergency rescue decisions.
1/1
-5
-T -t 0
Collection moue Processing and sumnnarizing module
Data collection system
Smart decision plafobrn for iformiation processing
and evolution law of hospital UE
Dynamic assessment modUe for -rescue emergency decision Theoretical framework and s m mUe for research
under an emergency scenario of the hospital UE and decision
Response platfor for hospital emergency upot auxLay platform of hospital emergency
management connnander s ecisin for unconventional emergency events
Rescue emergency module
Peaation system Decision system Execution system Operatin decision support cas library
FIG. 1
Description
1/1
-5
-T -t 0
Collection moue Processing and sumnnarizing module
Data collection system
Smart decision plafobrn for iformiation processing and evolution law of hospital UE
Dynamic assessment modUe for -rescueemergency decision Theoretical framework and s mmUe for research under an emergency scenario of the hospital UE and decision
Response platfor for hospital emergency upot auxLay platform of hospital emergency management connnander s ecisin for unconventional emergency events
Rescue emergency module
Peaation system Decision system Execution system Operatin decision support cas library
FIG. 1
[0001] The present invention relates to the technical field of medical emergency rescue, and particularly relates to an optimal allocation system of medical emergency rescue resources for catastrophic emergency events.
[0002] Catastrophic emergency events refer to particularly serious disasters or catastrophic events caused by natural or human factors, which occur suddenly and lead to heavy casualties, property losses, environmental damage and social disorder, and require the government, military and social forces to take emergency rescue actions to effectively deal with so as to minimize losses and harms caused by the disasters. Medical emergency rescue for the catastrophic emergency events is a key support point to effectively deal with the emergency events. Scientific understanding of the medical emergency rescue risks of catastrophic emergency events and further study on the mechanism are of great significance to enhance the predictability, pertinence, scientificity and initiative of the governmental emergency medical rescue work and to "early predict the crucial point" of the emergency rescue for the emergency events. The analysis on the medical emergency rescue risk of the catastrophic emergencies is a management activity that comprehensively considers the existing medical rescue response force and the risk of catastrophic emergency events, and aims to improve the ability to foresee the hazards of the catastrophic emergency events and the ability to treat casualties after occurrence, and to identify, estimate and evaluate the risks of elements requiring the medical emergency rescue caused by the coupling, occurrence and development of catastrophic emergency events at different stages to take effective countermeasures for alleviating, avoiding or transferring the risks.
[0003] Because of particularity, large hospitals are faced with greater threat of the catastrophic emergency events than conventional institutions. To enhance the study on the emergency response capacity of the large hospitals is of great significance to prevent the catastrophic emergency events in China. Compared with general public places, the hospitals have greater particularities that are reflected on unfavorable social factors, complex personnel composition, special functions, numerous equipment and facilities, and so on. The unfavorable social factors include tense doctor-patient relationship and overwork of medical staff, which can easily lead to catastrophic emergency events. In the aspect of the equipment and facilities, there are numerous expensive electric appliances, and inflammable, explosive, combustion-supporting and toxic hazardous chemicals and cotton products. These particularities bring difficulty for the emergency management of the catastrophic emergency events in the hospitals.
[0004] (I) Technical problems to be solved
[0005] In view of the disadvantages of the prior art, the present invention provides an optimal allocation system of medical emergency rescue resources for catastrophic emergency events, which solves the problem that large hospitals are faced with greater threat of catastrophic emergency events than conventional institutions because of particularity and the enhancement of the emergency response capacity of the large hospitals is of great significance to prevent the catastrophic emergency events.
[0006] (II) Technical solutions
[0007] To realize the above purpose, the present invention is implemented through the following technical solution: an optimal allocation system of medical emergency rescue resources for catastrophic emergency events includes a data collection system, a smart decision platform for information processing and evolution law of hospital
unconventional emergencies (UE), a dynamic assessment module for rescue
emergency decision under an emergency scenario of the hospital UE, a theoretical
framework and system module for research and decision, a response platform for hospital emergency management commanders, a support auxiliary platform of
hospital emergency decision for unconventional emergency events and a rescue
emergency module. The data collection system includes a collection module and a processing and summarizing module. The support auxiliary platform of the hospital emergency decision for unconventional emergency events is configured to perform emergency auxiliary decision on the response platform for the hospital emergency management commanders.
[0008] Preferably, the collection module comprehensively utilizes multidisciplinary research methods of systematic theories, management science, emergency medicine, fire protection theories, education science, disaster medicine, emergency management science and computers, and conducts systematic research on the hospital unconventional emergency events.
[0009] Preferably, the collection module includes a literature research method, a theoretical demonstration method, an index construction method, a comparative research method, a scale investigation method, an expert consultation method, a field investigation method and an empirical demonstration method;
[0010] The literature research method searches related articles by querying journals, works, INTERNET and the like, starts with the scientificity and rationality of system design and arrangement, utilizes relevant research methods and analysis tools of organization behaviors and management economics, refers to operation mechanisms of foreign hospitals for dealing with the unconventional events, and focuses on the analysis of literature and research results of emergency management in view of serious losses after the occurrence of domestic and foreign hospital events according to the situation in China to provide research reference by analysis and processing.
[0011] The theoretical demonstration method utilizes related theories of hospital management science, disaster medicine, emergency management, fire protection science, education and the like to demonstrate whether the emergency management of the unconventional emergency events in the hospitals in China is complete.
[0012] The index construction method performs fuzzy information conversion on an information index set according to a utility value index conversion formula and an order relation value index to establish an evaluation information index set, and synthesizes various information matrices of the evaluation information index set according to an OWA operator "more-than-a-half rule", i.e. a method of determining a weighting parameter by a determined parameter (0, 0.5) to obtain a fuzzy comprehensive evaluation matrix. According to an OWA operator "optimal" rule, that is, determining the weighing parameter from a parameter range (0.3, 0.8), a comprehensive evaluation value of 3 decision groups is calculated, wherein a maximal comprehensive evaluation value is an assessment solution of the optimal group solution.
[0013] The comparative research method performs transverse and longitudinal comparative research on the emergency management of unconventional emergency events in domestic and foreign hospitals, and researches the management experience and methods for hospital unconventional emergency events in the USA, Australia, Canada and Taiwan.
[0014] The scale investigation method designs a series of scales which are mainly based on closed questions, and then performs coding to facilitate the mathematical statistics and objective comparison.
[0015] The expert consultation method depends on the knowledge and experiences of hospital emergency management experts, fire protection experts, management science experts and education experts. The experts judge and evaluate the index system of the series of scales and the specific content thereof; and weights need to be provided for the indexes to reflect different influences of different indexes on the vulnerability of the hospital in an establishment process of an HVA method.
[0016] The field investigation method performs field investigation on the hospitals that have experienced fires or earthquake; and interviewing objects include the director of the local health bureau, the president and vice president of the hospital, head of medical departments, head of security guard departments, and relevant personnel of local safety supervision, fire protection, emergency management and the like at the time of the events;
[0017] The empirical demonstration method takes hospitals such as Affiliated Hospital of Armed Police Logistics College as research cases of the emergency management system for the unconventional emergency events in the hospitals. The method mainly performs empirical analysis before and after the training based on a scenario-coping mode and after different standardized training in China and abroad, and then performs the feedback and correction.
[0018] Preferably, the rescue emergency module includes a preparation system, a decision system, an execution system and an operation decision support case library.
[0019] Preferably, the optimal allocation system includes the following steps:
[0020] SI, collecting and decomposing data
[0021] collecting typical cases of various emergency events that have already occurred in large hospitals in China, describing and explaining reasons, processes, consequences, adopted countermeasures and experiences and lessons of events of these cases, collecting relevant information of similar hospital catastrophic emergency events in foreign countries or other places, and predicting risks of most-threatening possible unconventional catastrophic emergency events according to the international, national and regional economic and social development trend and new situations and new trends in environment, geography, geology, society and culture, including sources and types;
[0022] S2, classifying the cases
[0023] classifying the collected cases according to a time sequence and event type, describing the occurrence and a development process of the event, and establishing a system dynamics model of large hospital UE emergency rescue according to an entropy theory, system dynamics, mechanism methodology and other theories to analyze main dynamics behaviors of the event evolution and to mainly analyze the emergence, handling and effect of focus events;
[0024] S3, extracting case features
[0025] condensing and summarizing elements with a plurality of features from complex and changeable event groups, forming an event chain, distinguishing same and different characteristics of different events, defining and analyzing the features of hospital UE through literature consultation and case research, analyzing system features of the hospital UE emergency rescue, and exploring a tense framework and mechanism of the emergency rescue decision for the unconventional emergency events;
[0026] S4, establishing an event logic structure and analyzing main risks and threats
[0027] decomposing the hospital UE into a plurality of orderly sequences according to indexes of character classes, intensity grade and scenario characteristics, calculating a total score of a product of typical indexes by combining grade correlation analysis and index clustering analysis and by using a Delphi method and a brain storming method, and analyzing and determining representative typical indexes to analyze the main risks and threats;
[0028] S5, screening the cases
[0029] on the basis of the work of the first several phases, establishing a sorting order of scenario importance and priority of all events according to the disruptive strength of the hospital UE, an influencing range, complexity and probability of future special risk to integrate and supplement the hospital UE scenarios, and screening a plurality of emergency event scenarios with the least number and the highest commonness;
[0030] S6, planning a case response scenario
[0031] analyzing a coupling mechanism in the evolution of hospital UE scenarios from the aspects of geography, environment, meteorology, diffusion and secondary disasters, proposing a co-force coupling mode, a mutual-force coupling mode and a driving-force coupling mode of the hospital UE coupling, studying the estimation of coupling parameters, then establishing a standardized HUICS training course and scenario exercise schemes according to an ISD theory, and completing the HUICS and training content according to the continuous feedback of the trainee hospitals.
[0032] Preferably, the collection method for the data in the step Si includes case recall, literature research, Meta analysis on literature and works, and brain storming method combined with the Delphi method.
[0033] Preferably, the system dynamics model of emergency rescue for unconventional emergency events based on the entropy principle and consumption structure theory is established in the step S2 and is used to analyze the system structure and tense framework of the emergency rescue decision for the unconventional emergency events, and to establish the emergency response process of the unconventional emergency events in response to the great rescue practice on the basis of the analysis on the scenario features of large hospital UE, evolution and case reasoning emergency decision method.
[0034] Preferably, in the step S4, the typical unconventional emergency events that have already occurred in domestic and foreign countries are selected as the research object; by collecting, sorting and analyzing the historical data, the framework method is used as a basic case expression method to describe the cases according to the time attributes; and the correlation analysis method and main component analysis method are used to study the features of the emergency rescue cases, and to analyze the features of the emergency rescue of the unconventional emergency events.
[0035] (1I) Beneficial effects
[0036] The present invention provides the optimal allocation system of medical emergency rescue for catastrophic emergency events. The present invention has the following beneficial effects:
[0037] 1. The present invention provides the optimal allocation system of medical emergency rescue resources for catastrophic emergency events. The system classifies the rescue scenario elements according to an organization element, a facility element, an information knowledge element and the like and performs qualitative and quantitative description on basic features of various scenario situations, including the description for occurrence probability of various situations. According to the knowledge and experience of experts, the catastrophic emergency events and correlation among the events are analyzed by the systematic analysis method to obtain the intrinsic law such as the evolution of the catastrophic emergency events, thereby making different rescue decisions, and providing scientific and effective auxiliary support for the emergency rescue decisions.
[0038] 2. The present invention provides the optimal allocation system of medical emergency rescue resources for catastrophic emergency events. A synergistic system theory method is used, and different types of catastrophes that occur in China in recent years are selected; in view of the evolution law and evolution path of the catastrophic emergency events in China, the interaction between a medical emergency rescue main body and the evolution of the catastrophic emergency events is used as a complex large system; and a series of models are used to dynamically simulate the interaction between the evolution path of the catastrophic emergency events and the medical emergency rescue main body. On this basis, the medical emergency rescue demand and the formation and operation mechanism of the emergency rescue system are studied, and the countermeasures of the medical emergency rescue under different risk conditions are proposed, thereby providing theoretical evidence and analysis platform for the catastrophic emergency rescue, providing scientific evidence for the optimal allocation of the emergency resources, and providing novel methods and means for studying relevant theoretical problems of the emergency management.
[0039] 3. The present invention provides the optimal allocation system of medical emergency rescue resources for catastrophic emergency events. The system not only can provide the organization structure for the emergency event management, but also can guide the planning and construction of the process and adjust the structure, and can also be conducive to practicing and accumulating skills for handling the large-scale emergency events in the future. The system is flexible, has extensibility and high adaptability, is applicable to all hospitals, and is wider in applicability for any scale, geographic location, patient type, patient number or danger.
[0040] 4. The present invention provides the optimal allocation system of medical emergency rescue resources for catastrophic emergency events. By using the system, efficient and coordinative response can be made to the emergency events. After the catastrophic emergency events occur, when different institutions are required for cooperation in the system, the systems can be integrated seamlessly with various response institutions. The system provides a framework which supports the priority handling of the hospital emergency events, allocation of key resources, integration of communication systems and coordination of information, thereby finally improving the emergency management capacity of the hospitals.
[0041] Fig. 1 is a structural block diagram of the present invention.
[0042] Technical solutions in the embodiments of the present invention are described clearly and fully below in combination with the drawings in the embodiments of the present invention. Apparently, the described embodiments are merely part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by those ordinary skilled in the art without contributing creative labor will belong to the protection scope of the present invention.
[0043] Embodiments:
[0044] As shown in Fig. 1, embodiments of the present invention provide an optimal allocation system of medical emergency rescue resources for catastrophic emergency events, including a data collection system, a smart decision platform for information processing and evolution law of hospital unconventional emergencies
(UE), a dynamic assessment module for rescue emergency decision under an
emergency scenario of the hospital UE, a theoretical framework and system module for research and decision, a response platform for hospital emergency management commanders, a support auxiliary platform of hospital emergency decision for
unconventional emergency events and a rescue emergency module. The data
collection system includes a collection module and a processing and summarizing module. The support auxiliary platform of the hospital emergency decision for unconventional emergency events is configured to perform emergency auxiliary decision on the response platform for the hospital emergency management commanders.
[0045] Preferably, the collection module comprehensively utilizes multidisciplinary research methods of systematic theories, management science, emergency medicine, fire protection theories, education science, disaster medicine, emergency management science and computers, and conducts systematic research on the hospital unconventional emergency events.
[0046] Preferably, the collection module includes a literature research method, a theoretical demonstration method, an index construction method, a comparative research method, a scale investigation method, an expert consultation method, a field investigation method and an empirical demonstration method.
[0047] The literature research method searches related articles by querying journals, works, INTERNET and the like, starts with the scientificity and rationality of system design and arrangement, utilizes relevant research methods and analysis tools of organization behaviors and management economics, refers to operation mechanisms of foreign hospitals for dealing with the unconventional events, and focuses on the analysis of literature and research results of emergency management in view of serious losses after the occurrence of domestic and foreign hospital events according to the situation in China to provide research reference by analysis and processing.
[0048] The theoretical demonstration method utilizes related theories of hospital management science, disaster medicine, emergency management, fire protection science, education and the like to demonstrate whether the emergency management of the unconventional emergency events in the hospitals in China is complete.
[0049] The index construction method performs fuzzy information conversion on an information index set according to a utility value index conversion formula and an order relation value index to establish an evaluation information index set, and synthesizes various information matrices of the evaluation information index set according to an OWA operator "more-than-a-half rule", i.e. a method of determining a weighting parameter by a determined parameter (0, 0.5) to obtain a fuzzy comprehensive evaluation matrix. According to an OWA operator "optimal" rule, that is, determining the weighing parameter from a parameter range (0.3, 0.8), a comprehensive evaluation value of 3 decision groups is calculated, wherein a maximal comprehensive evaluation value is an assessment solution of the optimal group solution.
[0050] The comparative research method performs transverse and longitudinal comparative research on the emergency management of unconventional emergency events in domestic and foreign hospitals, and researches the management experience and methods for hospital unconventional emergency events in the USA, Australia, Canada and Taiwan.
[0051] The scale investigation method designs a series of scales which are mainly based on closed questions, and then performs coding to facilitate the mathematical statistics and objective comparison.
[0052] The expert consultation method depends on the knowledge and experiences of hospital emergency management experts, fire protection experts, management science experts and education experts. The experts judge and evaluate the index system of the series of scales and the specific content thereof; and weights need to be provided for the indexes to reflect different influences of different indexes on the vulnerability of the hospital in an establishment process of an HVA method.
[0053] The field investigation method performs field investigation on the hospitals that have experienced fires or earthquake; and interviewing objects include the director of the local health bureau, the president and vice president of the hospital, head of medical departments, head of security guard departments, and relevant personnel of local safety supervision, fire protection, emergency management and the like at the time of the events;
[0054] The empirical demonstration method takes hospitals such as Affiliated Hospital of Armed Police Logistics College as research cases of the emergency management system for the unconventional emergency events in the hospitals. The method mainly performs empirical analysis before and after the training based on a scenario-coping mode and after different standardized training in China and abroad, and then performs the feedback and correction.
[0055] The rescue emergency module includes a preparation system, a decision system, an execution system and an operation decision support case library.
[0056] The optimal allocation system of medical emergency rescue resources for catastrophic emergency events includes the following steps:
[0057] SI, collecting and decomposing data
[0058] collecting typical cases of various emergency events that have already occurred in large hospitals in China, describing and explaining reasons, processes, consequences, adopted countermeasures and experiences and lessons of events of these cases, collecting relevant information of similar hospital catastrophic emergency events in foreign countries or other places, and predicting risks of most-threatening possible unconventional catastrophic emergency events according to the international, national and regional economic and social development trend and new situations and new trends in environment, geography, geology, society and culture, including sources and types;
[0059] S2, classifying the cases
[0060] classifying the collected cases according to a time sequence and event type, describing the occurrence and a development process of the event, and establishing a system dynamics model of large hospital UE emergency rescue according to an entropy theory, system dynamics, mechanism methodology and other theories to analyze main dynamics behaviors of the event evolution and to mainly analyze the emergence, handling and effect of focus events;
[0061] S3, extracting case features
[0062] condensing and summarizing elements with a plurality of features from complex and changeable event groups, forming an event chain, distinguishing same and different characteristics of different events, defining and analyzing the features of hospital UE through literature consultation and case research, analyzing system features of the hospital UE emergency rescue, and exploring a tense framework and mechanism of the emergency rescue decision for the unconventional emergency events;
[0063] S4, establishing an event logic structure and analyzing main risks and threats
[0064] decomposing the hospital UE into a plurality of orderly sequences according to indexes of character classes, intensity grade and scenario characteristics, calculating a total score of a product of typical indexes by combining grade correlation analysis and index clustering analysis and by using a Delphi method and a brain storming method, and analyzing and determining representative typical indexes to analyze the main risks and threats;
[0065] S5, screening the cases
[0066] on the basis of the work of the first several phases, establishing a sorting order of scenario importance and priority of all events according to the disruptive strength of the hospital UE, an influencing range, complexity and probability of future special risk to integrate and supplement the hospital UE scenarios, and screening a plurality of emergency event scenarios with the least number and the highest commonness;
[0067] S6, planning a case response scenario
[0068] analyzing a coupling mechanism in the evolution of hospital UE scenarios from the aspects of geography, environment, meteorology, diffusion and secondary disasters, proposing a co-force coupling mode, a mutual-force coupling mode and a driving-force coupling mode of the hospital UE coupling, studying the estimation of coupling parameters, then establishing a standardized HUICS training course and scenario exercise schemes according to an ISD theory, and completing the HUICS and training content according to the continuous feedback of the trainee hospitals.
[0069] The collection method for the data in the step S includes case recall, literature research, Meta analysis on literature and works, and brain storming method combined with the Delphi method.
[0070] The system dynamics model of emergency rescue for unconventional emergency events based on the entropy principle and consumption structure theory is established in the step S2 and is used to analyze the system structure and tense framework of the emergency rescue decision for the unconventional emergency events, and to establish the emergency response process of the unconventional emergency events in response to the great rescue practice on the basis of the analysis on the scenario features of large hospital UE, evolution and case reasoning emergency decision method.
[0071] In the step S4, the typical unconventional emergency events that have already occurred in domestic and foreign countries are selected as the research object; by collecting, sorting and analyzing the historical data, the framework method is used as a basic case expression method to describe the cases according to the time attributes; and the correlation analysis method and main component analysis method are used to study the features of the emergency rescue cases, and to analyze the features of the emergency rescue of the unconventional emergency events.
[0072] Although the embodiments of the present invention have been shown and described, those ordinary skilled in the art can understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principle and spirit of the present invention. The scope of the present invention is defined by the appended claims and the equivalents.
Claims (8)
- CLAIMS: 1. An optimal allocation system of medical emergency rescue resources for catastrophic emergency events, comprising a data collection system, a smart decision platform for information processing and evolution law of hospital unconventionalemergencies (UE), a dynamic assessment module for rescue emergency decisionunder an emergency scenario of the hospital UE, a theoretical framework and system module for research and decision, a response platform for hospital emergency management commanders, a support auxiliary platform of hospital emergency decision for unconventional emergency events and a rescue emergency module, wherein the data collection system comprises a collection module and a processing and summarizing module; and the support auxiliary platform of the hospital emergency decision for unconventional emergency events is configured to perform emergency auxiliary decision on the response platform for the hospital emergency management commanders.
- 2. The optimal allocation system of medical emergency rescue resources for catastrophic emergency events according to claim 1, wherein the collection module comprehensively utilizes multidisciplinary research methods of systematic theories, management science, emergency medicine, fire protection theories, education science, disaster medicine, emergency management science and computers, and conducts systematic research on the hospital unconventional emergency events.
- 3. The optimal allocation system of medical emergency rescue resources for catastrophic emergency events according to claim 1, wherein the collection module comprises a literature research method, a theoretical demonstration method, an index construction method, a comparative research method, a scale investigation method, an expert consultation method, a field investigation method and an empirical demonstration method; the literature research method searches related articles by querying journals, works, INTERNET and the like, starts with the scientificity and rationality of system design and arrangement, utilizes relevant research methods and analysis tools of organization behaviors and management economics, refers to operation mechanisms of foreign hospitals for dealing with the unconventional events, and focuses on the analysis of literature and research results of emergency management in view of serious losses after the occurrence of domestic and foreign hospital events according to the situation in China to provide research reference by analysis and processing; the theoretical demonstration method utilizes related theories of hospital management science, disaster medicine, emergency management, fire protection science, education and the like to demonstrate whether the emergency management of the unconventional emergency events in the hospitals in China is complete; the index construction method performs fuzzy information conversion on an information index set according to a utility value index conversion formula and an order relation value index to establish an evaluation information index set, and synthesizes various information matrices of the evaluation information index set according to an OWA operator "more-than-a-half rule", i.e. a method of determining a weighting parameter by a determined parameter (0, 0.5) to obtain a fuzzy comprehensive evaluation matrix; according to an OWA operator "optimal" rule, that is, determining the weighing parameter from a parameter range (0.3, 0.8), a comprehensive evaluation value of 3 decision groups is calculated, wherein a maximal comprehensive evaluation value is an assessment solution of the optimal group solution; the comparative research method performs transverse and longitudinal comparative research on the emergency management of unconventional emergency events in domestic and foreign hospitals, and researches the management experience and methods for hospital unconventional emergency events in the USA, Australia, Canada and Taiwan; the scale investigation method designs a series of scales which are mainly based on closed questions, and then performs coding to facilitate the mathematical statistics and objective comparison; the expert consultation method depends on the knowledge and experiences of hospital emergency management experts, fire protection experts, management science experts and education experts; the experts judge and evaluate the index system of the series of scales and the specific content thereof; and weights need to be provided for the indexes to reflect different influences of different indexes on the vulnerability of the hospital in an establishment process of an HVA method; the field investigation method performs field investigation on the hospitals that have experienced fires or earthquake; and interviewing objects comprise a director of the local health bureau, president and vice president of the hospital, head of medical departments, head of security guard departments, and relevant personnel of local safety supervision, fire protection, emergency management and the like at the time of the events; the empirical demonstration method takes hospitals such as Affiliated Hospital of Armed Police Logistics College as research cases of the emergency management system for the unconventional emergency events in the hospitals; and the method mainly performs empirical analysis before and after the training based on a scenario-coping mode and after different standardized training in China and abroad, and then performs the feedback and correction.
- 4. The optimal allocation system of medical emergency rescue resources for catastrophic emergency events according to claim 1, wherein the rescue emergency module comprises a preparation system, a decision system, an execution system and an operation decision support case library.
- 5. The optimal allocation system of medical emergency rescue resources for catastrophic emergency events according to claim 1, comprising the following steps: Si, collecting and decomposing data collecting typical cases of various emergency events that have already occurred in large hospitals in China, describing and explaining reasons, processes, consequences, adopted countermeasures and experiences and lessons of events of the cases, collecting relevant information of similar hospital catastrophic emergency events in foreign countries or other places, and predicting risks of most-threatening possible unconventional catastrophic emergency events according to the international, national and regional economic and social development trend and new situations and new trends in environment, geography, geology, society and culture, including sources and types; S2, classifying the cases classifying the collected cases according to a time sequence and event type, describing the occurrence and a development process of the event, and establishing a system dynamics model of large hospital UE emergency rescue according to an entropy theory, system dynamics, mechanism methodology and other theories to analyze main dynamics behaviors of the event evolution and to mainly analyze the emergence, handling and effect of focus events; S3, extracting case features condensing and summarizing elements with a plurality of features from complex and changeable event groups, forming an event chain, distinguishing same and different characteristics of different events, defining and analyzing the features of hospital UE through literature consultation and case research, analyzing system features of the hospital UE emergency rescue, and exploring a tense framework and mechanism of the emergency rescue decision for the unconventional emergency events; S4, establishing an event logic structure and analyzing main risks and threats decomposing the hospital UE into a plurality of orderly sequences according to indexes of character classes, intensity grade and scenario characteristics, calculating a total score of a product of typical indexes by combining grade correlation analysis and index clustering analysis and by using a Delphi method and a brain storming method, and analyzing and determining representative typical indexes to analyze the main risks and threats; S5, screening the cases on the basis of the work of the first several phases, establishing a sorting order of scenario importance and priority of all events according to the disruptive strength of the hospital UE, an influencing range, complexity and probability of future special risk to integrate and supplement the hospital UE scenarios, and screening a plurality of emergency event scenarios with the least number and the highest commonness; S6, planning a case response scenario analyzing a coupling mechanism in the evolution of hospital UE scenarios from the aspects of geography, environment, meteorology, diffusion and secondary disasters, proposing a co-force coupling mode, a mutual-force coupling mode and a driving-force coupling mode of the hospital UE coupling, studying the estimation of coupling parameters, then establishing a standardized HUICS training course and scenario exercise schemes according to an ISD theory, and completing the HUICS and training content according to the continuous feedback of the trainee hospitals.
- 6. The optimal allocation system of medical emergency rescue resources for catastrophic emergency events according to claim 5, wherein the collection method for the data in the step S comprises case recall, literature research, Meta analysis on literature and works, and brain storming method combined with the Delphi method.
- 7. The optimal allocation system of medical emergency rescue resources for catastrophic emergency events according to claim 5, wherein the system dynamics model of emergency rescue for unconventional emergency events based on the entropy principle and consumption structure theory is established in the step S2 and is used to analyze the system structure and tense framework of the emergency rescue decision for the unconventional emergency events, and to establish the emergency response process of the unconventional emergency events in response to the great rescue practice on the basis of the analysis on the scenario features of large hospital UE, evolution and case reasoning emergency decision method.
- 8. The optimal allocation system of medical emergency rescue resources for catastrophic emergency events according to claim 1, wherein in the step S4, the typical unconventional emergency events that have already occurred in domestic and foreign countries are selected as the research object; by collecting, sorting and analyzing the historical data, the framework method is used as a basic case expression method to describe the cases according to the time attributes; and the correlation analysis method and main component analysis method are used to study the features of the emergency rescue cases, and to analyze the features of the emergency rescue of the unconventional emergency events.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| AU2021103263A AU2021103263A4 (en) | 2021-06-10 | 2021-06-10 | Optimal allocation system of medical emergency rescue resources for catastrophic emergency events |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| AU2021103263A AU2021103263A4 (en) | 2021-06-10 | 2021-06-10 | Optimal allocation system of medical emergency rescue resources for catastrophic emergency events |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| AU2021103263A4 true AU2021103263A4 (en) | 2021-07-29 |
Family
ID=76972110
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| AU2021103263A Ceased AU2021103263A4 (en) | 2021-06-10 | 2021-06-10 | Optimal allocation system of medical emergency rescue resources for catastrophic emergency events |
Country Status (1)
| Country | Link |
|---|---|
| AU (1) | AU2021103263A4 (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114067970A (en) * | 2021-11-15 | 2022-02-18 | 福州大学 | Power supply vehicle emergency rescue scheduling method based on genetic algorithm |
| CN114067970B (en) * | 2021-11-15 | 2024-06-28 | 福州大学 | Power supply vehicle emergency rescue scheduling method based on genetic algorithm |
-
2021
- 2021-06-10 AU AU2021103263A patent/AU2021103263A4/en not_active Ceased
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114067970A (en) * | 2021-11-15 | 2022-02-18 | 福州大学 | Power supply vehicle emergency rescue scheduling method based on genetic algorithm |
| CN114067970B (en) * | 2021-11-15 | 2024-06-28 | 福州大学 | Power supply vehicle emergency rescue scheduling method based on genetic algorithm |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Brennan et al. | Correctional offender management profiles for alternative sanctions (COMPAS) | |
| Wells et al. | Modeling critical infrastructure resilience under compounding threats: A systematic literature review | |
| Syed-Yahya et al. | The relationship between safety climate and safety performance: A review | |
| Nilsson et al. | Performance indicators for initial regional medical response to major incidents: a possible quality control tool | |
| Ma et al. | A hybrid approach based on the HFACS-FBN for identifying and analysing human factors for fire and explosion accidents in the laboratory | |
| Van Vuuren | Organisational failure: lessons from industry applied in the medical domain | |
| Liu et al. | Assessing urban resilience to public health disaster using the rough analytic hierarchy process method: A regional study in China | |
| Kaplan et al. | The Medical Event Reporting System for Transfusion Medicine: will it help get the right blood to the right patient? | |
| Fu et al. | Investigation into the role of human and organizational factors in security work against terrorism at large-scale events | |
| CN111639864A (en) | Quantitative assessment method for post security competence of port operating personnel | |
| Shirali et al. | Evaluation of resilience engineering using super decisions software | |
| AU2021103263A4 (en) | Optimal allocation system of medical emergency rescue resources for catastrophic emergency events | |
| Chen et al. | Data-driven decision-making model for determining the number of volunteers required in typhoon disasters | |
| Liu et al. | Study on construction safety management in megaprojects from the perspective of resilient governance | |
| Gholamizadeh et al. | A hybrid framework to analyze crisis management system maturity in sociotechnical systems | |
| Diehl et al. | The Department of Defense at the forefront of a global health emergency response: lessons learned from the Ebola outbreak | |
| Zhou et al. | Use of an expert system in a personnel evaluation process | |
| Wang | Grey Multiattribute Emergency Decision‐Making Method for Public Health Emergencies Based on Cumulative Prospect Theory | |
| Givens et al. | Females Engaged in Elite Training Previously Only Open to Males: Exploring the Variables of Successful Outcomes | |
| Ru et al. | A Pre-Generation of Emergency Reference Plan Model of Public Health Emergencies with Case-Based Reasoning | |
| Li et al. | Dynamic simulation and control strategy exploration of the unsafe behavior of coal mine employees | |
| O'Leary | Measuring disaster preparedness: A practical guide to indicator development and application | |
| Paulikienė | Hospital disaster resilience: a conceptual framework | |
| Hanson et al. | The validity of risk assessments for intimate partner violence: A meta-analysis 2007-07 | |
| Pletcher et al. | Practical and Ethical Perspectives on AI-Based Employee Performance Evaluation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| FGI | Letters patent sealed or granted (innovation patent) | ||
| MK22 | Patent ceased section 143a(d), or expired - non payment of renewal fee or expiry |