International Journal of Engineering Research and Allied Sciences (IJERAS) ISSN : 2455-9660, Volume-01, Issue-05, July 2016, pp.1-6
The Enhancement of Emergency Medical Services Systems V. E. Gueorguiev, PhD, D. V. Georgieva, PhD, I. E. Ivanov, PhD Abstract - In recent years, in the global healthcare industry could clearly delineate the trend of a fundamental transformation – the global healthcare industry moves from a volume-based business to a value-based business. The development of a new generation of software tools and system for medicine requires a critical assessment of the advantages and disadvantages of existing systems. The paper explores some results of the collaboration project between Medical University Sofia and Technical University of Sofia, which has the main goal to develop a set of obligatory requirements and to design a new generation Emergency Medical Services Systems (EMSS) in Bulgaria with improved efficiency and enhanced quality indicator. Keywords —Emergency Medical Services Systems (EMSS), Medical Informatics, Advanced Analytics in Medical Systems
I. INTRODUCTION After 2000 year, many industrial areas were directly dependent on the use of computer equipment. In 2010 more than 80% of industries in Europe are based and/or supported by computers: many studies and analyzes of the European Commission show that now quality indicators of individual industries directly dependent on the quality of used computer systems, devices and equipment. The same can be said about our life: more and more it is oriented to computer support: we have the so-called “ubiquitous computing”. Now, more and more people do not associate the term "computing" with classical desktop computers; they talk about mobile and embedded computers in cars, washing machines, phones, TV, different types of smart or intelligent devices. They talk about some new kinds of computer-based systems and devise: Internet-of-thing, cyber-physical devices and apparatus, about safety-critical applications and systems. The medicine is not an isolated island and for the last 30-40 years many computer-based devices, apparatus, tools, and applications became a part of medical infrastructure, hospitals’ equipment and clinicians’ practice. At the beginning, the computers were only parts of information systems and special devices. After these first years, some hospitals started to use computer apparatus to increase sensing of clinicians and this created a new science direction - the “computer-assisted diagnosis”. Today computersupported methods and computer-assisted methods for
Manuscript received March 01, 2016 mag. eng. Vesselin Evgueniev Gueorguiev, PhD, Faculty of Computer Systems and Control, Technical University of Sofia, Sofia, Bulgaria (e-mail:
[email protected],
[email protected]). mag. Desislava Valentinova Velcheva, PhD, Department of Informatics, New Bulgarian University, Sofia, Bulgaria (e-mail:
[email protected]). mag. eng. Ivan Evgeniev Ivanov, PhD, Faculty of Automatics, Technical University of Sofia, Sofia, Bulgaria (e-mail:
[email protected]).
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medical purposes have a big advantage because they only increase clinicians’ sensing and enable to do high precision tasks. In many cases of a diagnosis process the physicians start to use computer systems as a second opinion (this is named as “computer-aided diagnosis”). This is a normal point of view for clinicians - everybody using stethoscope needs from time to time newer and better one. It determines the small resistance of the medical staff to the adoption and better use of computer-based apparatus and systems. We think that in the future the speed of this process is dependent on the need to keep solutions safe because they are related to human’s health. Since 2005, there is an explosion of e-Health scientific publications and funded by governments’ new surveys and new strategies, as well as expand the themes within the framework of the European Union at the national and above-national level. At the same time, the number of the healthcare topics funded by European Union at national and supranational level rapidly grew. According to the analysis of the European Commission [6] over 10% of jobs in Europe are in the healthcare sector and from this sector received over 9% of the EU gross revenue. In 2010, the gross income of the companies of e-Health sector amounted to 2.5 billion Euros and until the end of 2015, is expected to rise to 2.7 billion Euros [13]. The paper presents some results of a second stage of collaborative project between Advanced Control Systems Labs (Technical University of Sofia) and Medical University Sofia, oriented to research and development of new generation eHealth tools and hospitals systems. The aim of the project is to conduct an extensive research in the field of e-Health: the quality evaluation of current Emergency Medical Services Systems (EMSS) and developing a list with obligatory recommendations to improve. Current trends in eHealth Software Industry In the period 2007-2013 year the researches in Medical Informatics and eHealth systems were focused on a wide range of topics: from new generation medical sensors via new HIS architectures to the legal aspects of the protection of the information and the safety of the technologies. The reason for this was the imbalance between the available IT infrastructure and its application: hospitals are relatively well IT equipped for administrative purposes; the infrastructure for the maintenance of the information for patients is less-developed; and the maintenance of a permanent (or regular) contact with the patients is still rudimentary condition. At 2005 V. Lessens present that only 2.3% of the hospitals have advise the decision-making systems and only 18.7% for sustaining banks with clinical results and prescriptions [12]. At the end of 2010 the studies on the healthcare services development showed the expected increase in costs to reach
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Please Enter Title Name of Your Paper up to 15% of the gross domestic product: the main reason is the growth of prices and the expansion of demand without substantially to increase the quality and accessibility of healthcare. Therefore, in addition to the classical tasks, the governments and the business set new tasks for research and development of next generation Advanced Analytics in medical systems: to assist both the processes of the administrative management of medical activities and the existing clinical practices and the activities [11]. Now the usefulness of the research and the necessity of new generation of advances analytics tools are one of the most frequently discussed themes. Analyses show extremely high relevance of research in all e-Health aspects [7,8,9]: from the medical, the financial, and the engineering aspects to the legal, the legislative and the organizational aspects. Today the progress in medical diagnostics and new thinking in the healthcare development services are achieved by the intensive introduction of ICT and providing of effective guidelines for pre-analytical procedures, medical diagnostic services, and healthcare management services. But in the last 3-5 year many times was discussed business aspect of future trends of computer-assisted and computer-aided methods and technologies. The Frost & Sullivan investigation [5] of computer-aided diagnosis market was mention: “From the inception of the market in 1998 up to 2008, revenues from the North American Computer Aided Diagnosis market continued to grow rapidly year after year. It surpassed the $100 million mark for the first time in 2007. However, this upward trend was reversed in 2009 due to several factors affecting global healthcare.” In combination with some other studies can be extracted some interesting trends [1,3,4]: Standalone types of diagnosis applications and tools are not more interesting because the business interest is oriented to tools and applications that can be integrated with current generation HIS. This trend is well known for other computer-based business and the result is plug-in technology. Analysis showed that computer-assisted methods are more suitable and more adoptable for use in relation to computer-aided methods. The computer-automated methods are less adoptable and they have a much larger additional maintenance costs. Decreasing of changing an eHealth tools market is based on reimbursement the research activities cost: patients do not want to pay for research (the hospitals increases patient’s cost because they add research cost as a part of the patient’s cost). This trend has led to stable rates of money reduction for the companies’ research. It sets a new company development strategy: creating and integrating new tools and modules to existing corporate systems. Unfortunately, the chosen strategy put as the main question a very old problem facing medical systems and devices: different manufacturers have their standards for interfaces between systems, apparatus, and devices; there is no common standard for medical data and information interfaces. There is no standard for Digital Medical Patient Record.
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The Health sector has been applying information and communication technologies for quite long time but although large achievements have been attained, many challenges remain either partially explored or simply unexplored. Current generation of eHealth hospital systems changes a lot from their previous basic functions: many new functions and expectations are addressed to them. The future of eHealth systems does not oriented only to the hospital data and information: they will have to cover patients out of the hospital and it will have to collect data for scientific research, and to provide data for pharmaceutical analyses, and so on. The technology trends are closely connected to the future of the computer as a device: the research and development are still oriented to desktop types of computers. But the future will be too different: we will have central service-based servers and many consoles/ terminals (mobile and desktop) connected to them. The speed of communication and the local power of console/terminal will be dominant for the new era of medical applications. This will change the point of view to current Data Mining and AI applications in medicine because will change boundaries between thin and fat clients from computer point of view. As example this will change in many aspects the computer-aided diagnosis application oriented to chronic diseases. Our examinations on current generation eHealth hospitaloriented systems concluded to the fact that hospital network overloads immediately if massive image or real-video exchange starts. This is unacceptable for this type of systems. In this context new generation medical systems have to address modes of failures, attacks to the network, overload of information and data, and basic robustness. The performance characteristics should include among others: Quality of service Accuracy of response Data and resource occupancy Security and access control Speed of response Massive research effort targets improving clinical outcomes and increasing the access to healthcare services and information, all while creating efficiencies that can save money and generate revenue. The analyses show expectations of the society for higher service quality, better results and lower costs. This poses a number of serious challenges to the Healthcare sector, as increasing expectations contrast with the clearly expressed critical shortage of resources, considering the ongoing ageing of population, each year requiring the increasing use of these resources on a daily basis. At the same time there is an increase of the share of chronically ill people, thus additionally limiting the available resources for healthcare. Those challenges have led to the development of various approaches and solutions during recent years, the most widely spread being the e-Health and Telemedicine. These advantages have reduced significantly with the new generation medical devices and the emergence of new approaches for working with the patients (e.g., pHealth and mHealth approaches). This brings the issue of new paradigms of the medical information workflow. One of the most promising research directions is the exploration of the possibilities for development of advanced analytic tools in
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International Journal of Engineering Research and Allied Sciences (IJERAS) ISSN : 2455-9660, Volume-01, Issue-05, July 2016, pp.1-6 medical field: they would allow the healthcare to function successfully, while balancing between the demands and expectations of patients and society, and the resources and changes in medical systems and practices. In order to achieve this, it is required that the tools for advanced analytics are able to use the increasingly broadening range of information of the patient, thus allowing a much earlier action for medical and administrative intervention. Directions are mixed medical, technical and financial: eHealth, Telemedicine, scalable business models, emerging reimbursement and payment structures, preventive health efforts, disease surveillance methods, chronic disease management, and behavior change interventions. As a final result, this would help improving the quality of patient care, better results of the work of the health system and reduction of costs. II. OUR PROJECT In recent years, in the global healthcare industry could clearly delineate the trend of a fundamental transformation – the global healthcare industry moves from a volume-based business to a value-based business [14,15]. Healthcare payers are under pressure to deliver better outcomes, driven by consumers’ expectations are for a higher quality of care, better outcomes and lower costs. The dynamics of healthcare costs is changing and new approaches to healthcare delivery are increasing complexity and competition. The increase of the amount of changes and the speed of changes is driven by defensive medicine practices, the increased length of human life, the pervasiveness of chronic illnesses, and the infectious diseases. The situation is expected to become even more complex in the next few years [16]. It is already clear that the growing complexity of the healthcare industry will require smarter, more informed decisions. This is the only possible solution for improving medical and economic results imposed by market dynamics and increasingly demanding consumers. The Emergency Department (ED) is one of the principal elements of modern healthcare systems. The aim of emergency care medicine is to provide patients with the healthcare that they need, ensuring the quality and safety of care [2]. There is an increasing demand for this resource, which involves high resources (staff, costs, equipment, etc.). Quality healthcare guarantees safe, appropriate, effective, efficient, accessible, and fair patient-centered care [10]. In last two decades, the care quality has the central healthcare focus, and patient safety has come to represent one of the key quality aspects. In the case of emergency care, this interest in quality is even more evident, not only because of its social and economic impact. Today, two factors are cited as key ones to the continuing push for improving quality of emergency care: for many humans the Emergency Department is the only public portal to access medical services; another key factor is the ‘life-and-death’ nature of emergency care. Measuring quality in EMSS is challenging because emergency medicine is all about juggling tasks. The complexity of the task is increased by the fact that the EMSS is only one of components of the larger health care delivery system. As such, it is subject to many forces far beyond its
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direct control. The analyses of the EMSS development show expectations of the society for higher service quality, better results and lower costs (as in many other healthcare industry sectors). This poses a number of serious challenges as: increasing expectations contrast with the clearly expressed critical shortage of resources, considering the ongoing ageing of population, and each year requiring the increasing use of these resources on a daily basis. At the same time there is an increase of the share of chronically ill people, thus additionally limiting the available resources for healthcare. Those challenges have led to the development of various approaches and solutions during recent years. Although emergency medicine is relatively new discipline of medicine (it is separated as an independent discipline towards the middle of the 20th century), but nevertheless, throughout this period the quality enhancement of emergency care has been a major concern and task for healthcare. The existing academic studies focus only on individual aspects of the problem and most often they only cover a narrowly defined field of application. Corporate developments are oriented towards the possibility of renewal and development of the old company systems, through integrating new approaches to collection, unification, search and processing of data, information retrieval and generation of knowledge. The most frequently reported result is the identified impossibility to introduce substantially new generation tools due to outdated design of systems of older generations. By the end of 2014, our group (Advanced Control Systems Lab, Technical University of Sofia), together with colleagues from Medical University Sofia, started collaborative project aimed at defining the requirements, constraints and key features of the new generation EMSS. The project objectives include: to make an analysis of the existing quality of emergency care (activities, devices, environment, staff, etc.) ; to fix the existing sources of medical, biological, and hospital data; to research of the possibility to use information and/or knowledges about illnesses and their treatment in patients with similar symptoms; to define more flexible and scalable structure of medical data: it will enhanced ability to use new Advanced Analytics in EMSS; to determine the requirements for a new framework to the Emergency Departments in Bulgaria. To achieve the objectives we plan following activities: defining and evaluating a new set of quality indicators for EMSS; researching and evaluation of new methods for processing, storage and modification over time of medical, biological, and hospital data / information / knowledge will be created; changes in the ways of gathering and integration of information in real time will be effected; applicability of mobile agents for semantic search across heterogeneous and distributed sources will be studied and developed;
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Please Enter Title Name of Your Paper automatic and semi-automatic methods for imaging data structuring will be introduced; to define and to validate the critical functionality, characteristics, and constraints of new generation EMSS with Advanced Analytics modules. III. PROJECT RESULT A. The first stage results The main stage goal is a comprehensive study of the concepts and methods for a new generation of advanced analyses in healthcare sector. Research on the opportunities to creating of tools for new generation advanced analysis is considered most promising direction of investigations, which will enable successful functioning of health, for better management of patients at lower costs. So today they are in the priority objectives group. The accompanying project objectives are to conduct: a research of the sources of medical and biological data; a research of the possibility for using information/knowledge for illness and its treatment of patients with similar symptoms; structuring the medical data/information/knowledge about the needs of the methods for advanced analysis. The study of the medical and hospital information systems and their networking determines the following data/information/knowledge sources: medical staff computers, clinical workstations, hospital medical labs (e.g., microbiology) radiology, clinical laboratories, pharmacy, clinical databases (electronic medical records), patient computers, financial systems (billing, cost accounting), material management, administrative systems, research databases, library system, and educational resources. The study of the input/output data streams has determined the following sources and consumers of data/ information/knowledge: patients (home workstations), other hospital systems, other physicians, government healthcare systems (e.g., electronic medical records), pharmaceuticals regulators, insurance agencies, medical research groups/institutions, the Internet, other information resources/libraries/databases, vendors and providers of various types, and medical education centers (e.g., medical schools). After fixing data sources and data streams, our research is directed towards research on some characteristics of the data that have a direct impact on the ability to investigate and to evaluate data variability and data interoperability. The main
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characteristics of data are: heterogeneity, distribution, and modality. The studies of the heterogeneity and the distribution of data at this stage have shown that the main problems of multiple data sources are the following: Heterogeneity of names: different databases store the same values, but the names of the attributes given are different. Heterogeneity of relational structure: the composition of attributes in a complex structure is varies, but the stored values are identical. Heterogeneity of values: different data sources have different methods of values presentation. Semantic heterogeneity: different assumptions can be made about the data relevance, reliability and usefulness. Heterogeneity of the models of data storage: this raises the issue of transformation between models. Heterogeneity by time: different data are obtained at different times. B. The second stage results The quality of care can be defined as the degree to which the services provided to an individual and to a population increase the probability of obtaining a desirable outcome that is coherent with the current knowledge of the profession [17]. We started stage’s activities based on well-known key axiom of engineering: “The evaluation of quality is a process of measuring of the difference between the results that should be achieved and those that are achieved.” The first step is to select the approach. In order to accelerate the initial project activities stage we used a hybrid approach between the two classical basic approaches to the evaluation and improvement of the quality of care [17]: 1. The so-called “Room for Improvement” model: It begins with the identification of problems, followed by their analysis and proposals for improvement. The main question: What could we or should we improve? 2. The so-called “Monitoring systems” model: This model is used to detect problems and periodically evaluate performance, the fundamental element of which is the indicators. The main question: Of everything that we do, what is most important and how can we assure that we are doing it well enough? At the second step we prepare two preliminary lists of activities aimed at quality improvement: a list of mandatory ED activities needed to be improved (the “Room for Improvement” model point-of-view), and a list of activities that necessarily need to be part of the emergency care (the “Monitoring systems” model point-of-view). After that we validate our lists for completeness and consistency: we examine the full connectivity and traceability between the activities in two lists, i.e. each element from one list has to have at least one directly connected element of the second list (an activity giving raises this action or an activity that is a direct consequence of this action). This led to rapid extensions of the both lists with many new activities.
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International Journal of Engineering Research and Allied Sciences (IJERAS) ISSN : 2455-9660, Volume-01, Issue-05, July 2016, pp.1-6 The next step is the restructuring and merging two lists because we need more general categories of activities (i.e., a smaller number of specific quality indicators). Here are some of these aggregated categories: The emergency care is a patient-centered care and this includes good communication, an emphasis on relieving suffering, and the overall experience of patients. Patients with emergency care needs should have as early as possible access to specialist to assure appropriate on-going treatment. Additionally, after timely and appropriate care patients need additional care which continues to support them after they have left the ED. The ED staff should as early as possible recognize those patients requiring immediate attention and prompt time critical interventions. This improves assessment, investigation and management of patients with emergency conditions. The hallways or non-equipped overflow spaces are no place for routinely caring injured or acutely-ill patients. The duration of patients’ stay in the ED is a compromise between requirement to maximize care and comfort of patients and requirement to optimize hospital outcomes. The ED should have adequate space to provide the necessary patient care: the environment should be promoted patient dignity and privacy. The ED staff should be specially qualified and trained to deliver emergency care. In cases of injury, life-threatening illness, mental or physical changing illness as early as possible to involve senior physician/-s with specific expertise (It is recommended that these professionals have experience in emergency care). Example: in many cases diagnoses and treatments need collaboration with physician from intensive care and/or anesthesia departments. The ED environment should be provided for appropriate access to diagnostic support services (labs, radiology, ultrasound, etc.) when needed for the immediate diagnosis of life threatening conditions The ED environment should not be a source of new hospital infection. This requires appropriate set of rules, tools, and compliance with infection and • hygiene control. The ED management should establish mechanisms to monitor compliance and standards, with action taken if a staff short. Designated categories allow easier to define quality indicators because the indicator’s influence is localized only within a specific group. This allows binding the created indicators with the basic three structural units of Emergency Medical Systems [6]: 1st emergency medical care: provide treatment for emergency patients with relatively mild illness or injury 2nd emergency medical care: provide treatment for emergency patients with more severe conditions,
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requiring surgery and/or hospital admissions, in general referred from initial emergency medical facility 3rd emergency medical care: provide 24 hour treatment for emergency patient with serious conditions requiring high level medical care (e.g., head injuries, stroke, myocardial infraction) This allowed to start research on possible areas of application of Advanced Analytical in EMSS and to start the investigation of the critical functionality, characteristics, and constraints of the new generation EMSS. C. The preliminary results of third project stage We start out stage activities with evaluation of the question “Why ED is classified as complex and chaotic environment from management point-of-view?” Now we can say that there are two main reasons: limited patient information: The Emergency Department (ED) staff frequently need to make critical decisions without having the minimum necessary information for the patient (patient records/medical history/...) stressing available resources: many times crucial decisions are made under pressure with limited resources and continual readiness for new arrivals. This allowed us to change some of our preliminary views on existing patient data and information flows. The result is a clear definition of role of ED systems in healthcare IT architecture: to enhance the quality of ED computer systems we need to think about this system both as a consumer of available past patient data and as new patient information source. This has allowed creating a prototype of the meta-model of data and information flow in a new generation ED services system. The following main groups of physicians’ activities have to be covered by new generation EMSS infrastructure: examining a patient, searching and taking a past patient history, ordering tests, interpreting test results and considering diagnoses, creating a patient treatment plan, and defining the communication and/or data and information exchange with other hospital departments. We define the following set of obligatory computer and communications technologies to achieve new medical and hospital management requirements: Wireless registration, monitoring, and communication. Digital audio/video communication: at least host-to-host, but better teleconference. Handheld devices and mobile computing Telemedicine devices support Electronic dashboard: centralized with remote connections New generation decision support systems Digital image creating and archiving: supporting different standards and devices of digital radiography Hi-speed secure and safety pre-hospital data and information transfer RFID tracking: at least passive, but better active.
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Please Enter Title Name of Your Paper Now our project activities are aimed at the definition and evaluation of requirements and identifying base EMSS functions groups. At this moment we define and evaluate following obligatory functions groups for new generation EMSS: 1. Monitoring and management patient flow and following-up hospital patient care activities: this includes variety of systems characteristics and functions oriented to patient tracking, data/information exchange, and seamless communications between hospital departments and laboratories. 2. Documentation and archiving of medical/clinical data, information, and knowledge: all emergencies require documentation of the specific details of the visit but this task is a time-consuming and nobody like it. 3. Medical decision support: all types of adverse events and activities that prevents physicians in time-critical decision activities. 4. Interoperability between ED and other healthcare providers: in this group we select all medical information functions that are used to “ED-patient” and “ED-other health provider” communications and data/information exchange. 5. Real-time patient health status monitoring. IV. CONCLUSION
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The Emergency Department is a very spatial and unique location at which patients are guaranteed 24 hours/7 days access to health care. Social changes produce a number of challenges to the provision of high efficient and quality emergency care. The quality of medical care can be defined as “… the degree to which the services provided to an individual and to a population increase the probability of obtaining a desirable outcome that is coherent with the current knowledge of the profession.” [17]. An important element of good emergency care is the constant development of enhanced and innovative services to support the delivery of safety and quality. The current results of our project allowed us to determine the main groups of quality indicator: staff, approach, processes, decision making, results, environment, support, inpatient vs. outpatient services, creation of new services, the starting time and the duration of staying in ED, etc.
[17]
[18]
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