Abstract
This paper aims to helps, facilitate, and improve the efficiency of care, and allows real-time monitoring of patients. In fact, it allows collecting and archiving of heterogeneous medical data in centralized, virtual and secure sources. The main aim of the paper is to improve the efficiency and the quality of care and improve patients’ lives through optimal information sharing between doctors and professionals. It also contributes to ensure the continuous monitoring of patients. This innovation in this field of e-health can solve, with a perfect cost control, the challenges related to the health care system. In the second hand this article aims to establish an interactive component at the application layer of the system as “Serious Game” for patients, physicians, professionals, and students in medicine. For physicians and students the device acts as an interactive guide that simulates a medical consultation and can implement all stages of diagnosis, including information gathering, simultaneous notes taking, and physical examination with instruments, so that a doctor would be able to perform a complete assessment of the health state of the patient. Moreover, our solution allows physicians and/or professionals to simulate a whole collaborative training in an educational online game, capable of improving the quality and safety of medical practices. As an example, the solution allows to train professionals in the operating room to avoid all risks before performing a complex surgery. For patients, this component offers schematic solutions that are well adapted to their conditions. Patients learn techniques of cognitive behavioral therapy to address symptoms of depression and become well assisted in their rehabilitation. For instance, patients would be able to deal with negative thinking, solve problems, better plan their activities, and learn how to relax. Our solutions will be applied to two basic application fields.
Keywords
1 Study and Strategic Coordination
Strategic Coordination
Over the past few years, there has been a rapid growth in the use of ICT in the sector of e-health. These technologies constitute a change in the provision of care as services to the population. E-Health is a relatively recent term, which dates back to at least 1999, and it designates “all technologies, networks and services of care based on the telecommunication and comprising education programs, collaborative research, consultation and other services offered in the aim of improving the health of the patients”. Focused on the large public, the e-Health covers currently the activities, services, systems, related to health, practices at a distance by means of ICT, for the needs of global health promotion, care, control of epidemics, management and research applied to health care.
1.1 The Basic Components of e-Health
The term e-Health encompasses a range of services or systems, which are on the edge of medicine, health and information technology. It includes:
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Electronic health records or Medical Record of the patient (DMP): allows the communication of patient data between different health care professionals (general practitioners, specialists, etc.).
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E-Prescribing: gives access to options for prescription, requirements of printing for the patients and the electronic transmission of orders, sometimes from doctors to pharmacists.
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Telemedicine: remote physical and psychological treatments, including remote monitoring of functions of patients.
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E-Health knowledge management: for example, the epidemiological monitoring or guides to good practice.
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Virtual teams of health: composed of health professionals who work together and share information on patients thanks to digital equipment.
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M-Health or e-Health: includes the use of mobile devices in the collection of data of patients, providing health information for practitioners, researchers and patients. Real-time monitoring of the vital signs of patients, and the direct provision of care via mobile telemedicine. Examples of m-health products are mobile applications that can help doctors to diagnose. The communicating devices can transmit information (weight, heart rate, etc.) to the physician.
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Health information systems: also, often, refer to software solutions for the management of the patient data, the management of working hours and other administrative tasks surrounding the health.
1.2 e-Health and the Private Life
The requirements for the respect of privacy are numerous in an information system, and especially when it comes to information concerning health. One of the factors that are blocking and are to worry about the use of e-health tools is the concern on privacy issues concerning the records of patients, more particularly the DMP (medical record of the patient). This main concern relates to the confidentiality of the data. Examples among others include:
Data Theft:
The theft of patient data becomes possible outside the cabinet. There is no way for the patient to realize it. It is an irreversible fact; storage and copying of information is extremely simple with informatics.
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Centralization: Centralization of data or access to the latter on a same platform increases the interest of hackers and the gravity of the facts in case of a problem.
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Sensitivity: In addition to being part of the individual, the data on the health of a person are worth money for banks, insurance, or a future employer.
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Security: If the principle of encryption is infallible in theory, its practical implementation on the other hand is not. All areas of acts of piracy are committed in secure infrastructures.
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Trust: We must have faith in the doctor but it also becomes necessary to have confidence in all intermediate computers. This responsibility to protect the data is extended to persons that the patient knows less and has not chosen them.
1.3 The State of the Art of Health in Morocco
A. The actors of health
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The Legislature: The health sector is governed by legal texts and it follows that the legislator is a main speaker. It should be noted that all the legal texts are subject to publication in the Official Bulletin detained by the General Secretariat of the Government in compliance with the Moroccan constitution.
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The ministry of health: The Ministry of Health is responsible for the development and the implementation of the government policy in the area of health.
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Ministry of Education: In Morocco, all the faculties of medicine and pharmacy and dentistry, training institutions, are under the Ministry of Education, Higher Education, executive training and scientific research. Because of this it remains a major player in the health sector.
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Health care professionals: They are in direct contact with the patients for consultations, treatments, care, etc. And also, with the scientific research, training and monitoring of future health professionals.
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The NGOS: They reinforce the interventions of the Ministry of Health or draw its attention to the topics which are crucial.
All these actors are involved through an infrastructure that covers all the prefectures.
B. The health card of the Country
Morocco remains relatively endowed with offers of care at the level of health care institutions. We have: 4 university hospital centers (CHU): CHU Ibn Sina (Rabat), CHU Ibn Rochd (Casablanca), CHU Hassan II (FES) and CHU Mohamed VI (Marrakech). There are 130 hospitals, including 35 specialized and 65 general practitioners. As to the private clinics, we count about 302. And regarding specialized institutions, we have:
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The National Institute of hygiene,
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A poison control center
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A Pasteur Institute
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A National Laboratory for the control of medicines
The training institutions are many, we can cite among others.
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4 Faculties of Medicine and Pharmacy in Rabat, Casablanca, Fez and Marrakech.
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A faculty of dentistry in Casablanca.
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Training Institutes in Health care.
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A National Institute of Health administration.
1.4 Economic Benefits and Social Impact
The term e-health refers to all the opportunities that digital systems bring or are likely to bring to the health care field. This represents, as an example in France, a market estimated between 2.5 and 3 billion Euros. The development of new technologies in health is therefore a major challenge for the industry and the economy of the state. Platforms and software are all services which must facilitate the exchange and sharing between professionals in the community. They also aim to improve the conditions of the practice of the profession by an optimization of the coordination of care and an improvement in the involvement of patients in their medical history.
In the area of health, Morocco has embarked on a reform of its health care system which aims to enhance the quality of care and to guarantee access to the whole population. And to do so, Morocco needs to adopt e-health system which offers the citizens access to all of the information, communications and services, as well as a direct communication with the professionals and the health services; the main benefits of the e-health for health professionals are an improvement of the access to systems of clinical decision support to improve the quality of their decision and that of their delivery of services. Besides, it offers access to sources of information that are extremely rich for training continuous professionals. The impact of this project on the socio-economic sector can be summarized into:
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Improves the quality of care and avoid additional costs associated with duplication of treatments and interventions.
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Facilitates access to care particularly in areas of medical desertification.
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Offers home care and rapid home return for a better follow up in a familiar environment.
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Ensures better coordination between professionals.
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Facilitates the elaboration of statistics and the process of making decisions as well as the generalization of care on the totality of the Moroccan territory.
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Gives a global vision on the state of the health of citizens and the adverse effects of the environment on the citizens.
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Permits a quick Check of the progress and the distribution of diseases.
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Ensures an efficiency of health care system (control and reduction of health care costs).
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Allows training of professionals and students.
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Accelerates the capacities of all actors to produce and share data about health in a secure way with a better coordination of care.
1.5 Diseases Application Fields
a. Cancer Diseases
The project will put in place two attractive services for doctors and students of medicine. These two services are:
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1.
A tool for monitoring and consultation which centralizes all the data of the patients for their real-time monitoring. The doctor is close to the patients and intervenes remotely in case of need.
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2.
A simulation tool for the realization of complex surgical operations via a serious game. Examples include the “colposcopy” operation made for the uterus and the “endoscopic” operation made on the stomach. This type of operation requires a high precision because it allows determining the status or the severity of the cancer for these two sensitive organs. The proposed tool allows physicians to simulate the operation several times and discover with more details the steps of the operation prior to making it.
b. Autistic Children (in the context of the project)
Autism or more generally: Autistic Spectrum Troubles (TSA) are human development troubles characterized by an abnormal social and communication interaction, characterized by a restricted and repetitive behavior. In order to communicate with people with autism, a confident, funny and effective communication link must be created. To meet this need, the project proposes serious games, training and methods of integration to make the person with autism closer to normal life and facilitates his/her integration. All proposed options (games, tests, training, films, music etc.) represent effective learning tools that can be customized to match the condition of Autistic patients.
2 Work Packages
Generally, the paper goal addresses the reason, principles and functionalities of e-health and health care systems and presents a novel framework for revealing, understanding and implementing appropriate management interventions leading to qualitative improvement and transfer of health resources and health care by electronic means. It encompasses four main work packages:
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WP 1: Heterogeneous Data collection and classification based on context and optimization of the interrogation: Big data integration, Cloud computing.
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WP 2: The delivery of health information and the access to medical knowledge, for health professionals and health consumers through the Internet and telecommunications: Software architecture of a Digital Smart Health Application, System Architecture, functionalities and validation.
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WP 3: Using the power of IT to improve public health services, e.g. through the education and training of health workers and reviews standards and guidelines for practicing medicine: “Serious Game”.
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WP 4: The use of remote monitoring and real time surveillance practices in e-health systems management and data communication with the environment: Design and development of the wireless sensor network and the energy efficient communication protocol.
In this context the ARCHIMED project aims to help to facilitate and improve the efficiency of care, and allows real-time monitoring of patients. In fact, it allows collecting and archiving of heterogeneous medical data (pharmaceutical, medical imaging, teleradiology & reports, etc….) in a centralized, virtual and secure manner. The main aim is to improve the efficiency and the quality of care and improve patients’ lives through optimal information sharing between doctors. It also contributes to ensure the continuous monitoring of patients (those of chronic diseases for instance). This innovation in this field of e-health can solve, with a perfect cost control, the challenges related to the health care system, while ensuring the quality and safety of care for patients. ARCHIMED allows improving the quality of care (well-suited to the profile of the users) and decision-making based on these needs at all stages of patient care, from initial diagnosis to monitoring by doctors, health professionals located in geographically distributed institutions and private doctors. Concrete applications include screening, diagnosis, treatment guidance, surgeries controlling and therapeutic monitoring. The specificity of ARCHIMED is empowered by developing and implementing further innovative components to ensure all phases of medical information processing, mainly the acquisition, storage, classification, retrieval, querying, adaptation, testing, outsourcing, security, safety, data transfer, availability etc.
In the second hand, the ARCHIMED project aims to establish an interactive component at the application layer of the system in the form of a “Serious Game” for patients and physicians, professionals and students in medicine (Players). For physicians and students (future doctors), the device acts as an interactive guide that simulates a medical consultation and can implement all stages of diagnosis, including information gathering, simultaneous notes taking, and physical examination with instruments, so that a doctor would be able to perform a complete assessment of the health state of the patient. Moreover, our solution allows physicians and/or professionals to simulate a whole collaborative training in an educational online game, capable of improving the quality and safety of medical practices. As an example, the solution allows to train professionals in the operating room to avoid all risks before performing a complex surgery. The sessions can be replayed and analyzed as many times as needed to enable physicians (and/or students in training) to master the process of interventions, avoid all possible contingencies, manage risks and prevent serious adverse events. One innovation in the solution we propose is that when one (or many) player(s) is (are) not physically present to complete various components of the game, the system automatically offers adaptive and smart replacing agents with all necessary functionalities to automatically interact with the system and the other users. For patients, this component offers schematic solutions that are well-adapted to their conditions. Patients learn techniques of cognitive behavioral therapy to address symptoms of depression and become well-assisted in their rehabilitation. For instance, patients would be able to deal with negative thinking, solve problems, better plan their activities, and learn how to relax. In doing so, patients would be monitored both at the hospital and at home and are more independent and active in their rehabilitation. Our solution is a multiplayer platform: it allows patients to see their progress in the game and use the results from other patients’ requests (accomplished quests, past levels …). In addition, the patient does not re-educate himself alone as he deals with other patients or family members. This allows the patient to get out of his isolation thanks to a real innovative and customized working tool. In this feature, the proposed system is connected with different devices: Kinect, touch pad (iPad or Android), mouse and graphic tablets, to ensure extreme and precise adaptability to different motor abilities of the patient during his rehabilitation program.
3 Basic Functionalities of ARCHIMED System and Key Words
Shared services for medical data analysis/Data Center for patients’ medical information (DMP)/Reuse of medical results/service-oriented Awareness/Body virtualization and Medical Imaging/Data Analysis and extraction for automatic prediction/Security and safety of online health data/Connecting health care and social information systems/Remote control and monitoring of patients/Telemedicine and mobile collaboration technology.
1. WP1 Heterogeneous Data collection and classification based on context and Optimization of the interrogation
With a multitude of actors in the health field, the studies have demonstrated that the capital information on the medical knowledge doubles every seven years. This explosion of information is not without problems of organization of medical knowledge, which is more accessible to a human mind in its entirety. Therefore, this WP proposes a solution that every citizen can have an electronic medical record which can be used separately both by the patient and doctors to improve the quality of the medical care with the possibility of interactivity with all sources in relation to a high efficiency and in better working conditions. Besides, the introduction of an interoperability frame work systems for e-health with technical conditions, legal financial and organizational functionalities of the health sector will allow relevant statistical and policy analyses. Particularly in the context of epidemiological studies and in the transformation of medical knowledge on a broader spectrum of integrated systems for country decisions and prevention. Thus, the analyses of risk factors determine the steps of diagnostic research and therapeutic strategies. This type of tools is also widespread in all western countries, but it faces now competition from private products which do not offer the same guarantees neither for the functionality nor for the instruments developed by public authorities. This situation calls for vigilance and determination in the conduct of public projects (Fig. 1).
This WP requires a methodical and pragmatic approach which will allow a development of a system for integration and federation of e-Health sources in order to ensure:
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Communication and interaction with each data source as needed.
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Specification of a query, expressed in terms of a user-specified vocabulary (ontology), across multiple heterogeneous and autonomous data sources.
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Specification of mappings between user ontology and the data-source specific ontologies.
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Transformation of a query into a plan for extracting the needed information by interacting with the relevant data sources.
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Integration and presentation of the results in terms of a vocabulary known to the user.
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Deployment on national scale of the generic services for sharing e-Health documents between health professionals following rule clearances controlled by the patient, and provision of the first on line and secure platform for medical data (history, prescriptions drug, biological test results, radiology reports of hospitalization and consultations etc….).
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Implementation of new services to patients which offer available information about them (automatic receive results analysis avoiding travel, for example) or the help in their taken load (callbacks, capacity computerized exchanges with their doctor, therapy support programs … etc.).
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Exchange of information and provision of medical products and flexible and reliable services.
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Provision of high availability and mobility 24 H/24 and 7D/7 by making online patient records, securely and reliably.
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Management of the patient’s health in order to improve his health and facilitate support by monitoring permanently the state of a patient.
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Make a profound decision on diseases and make a statistical prediction.
Research Issues
The main issues are: (1) How to detect and resolve problems related to heterogeneity? (2) How to effectively find the relevant data sources and generate an optimal execution plan? (3) How to automate the generation of queries? (4) How to reduce the search space for a query? (5) How to classify data sources for integration? (6) How to take into account the semantics of sources? (7) How to make a global optimization for query processing? (8) How to give the possibility to users to express their preferences? (9) How to take into account user preferences and needs in the design of integration system?
The general research context of this section is based on the integration of heterogeneous data sources and especially on the global optimization of interrogation of the integration systems. The proposed system is similar to a hybrid integration system, insofar as it combines virtual integration and materialized integration data. The materialized integration consists in consolidating distributed data, after being pretreated in a single consolidated synthesis base and integrated by topic. Extracting, by queries, parts of the database, it becomes possible to analyze the data and make the best decisions quickly; while in a virtual integration, the data remains in the local sources and will be retrieved at the query. Our choice for hybrid architecture is essentially done to achieve a compromise between freshness of data mediation approach and rapid response time to requests for data warehouse approach.
The use of ontologies in the integration process is an approach that has been successful and is still promising with a large number of researches done in this area. Known by their undeniable contributions to the semantic level, they are addressing the semantic problems to reduce the heterogeneity of the data. Their formal aspect allows, in addition, to automate the integration process, which is a very interesting contribution when dealing with a large number of data sources. That is why we also want that the user of our integration system can be able to query the internal and external data simultaneously using the global ontology of the data integration system. Indeed, to automatically exploit the resources distributed across different data warehouses and mediators, the definition of ontologies and a shared ontology field is required. Given the objectives mentioned previously, the main objective of this WP can be summarized in the following sub-tasks:
Task 1.1: Define hybrid integration Architecture of heterogeneous information sources
In this task we will develop a flexible data integration framework by implementing hybrid integration architecture to overcome the major limitations of virtual and materialized methods when they are used separately. Our first objective is to develop a hybrid multi-mediators functional architecture for our integration system. It is an architecture that responds perfectly to a data integration approach that focuses on the performance and the overall optimization of query processing, which aims to make more relevant and accurate interrogation in the sense where the user can access the parts of the resources that meet his request.
Task 1.2: Global Shared Ontology for hybrid integration system modeling the medical field
One Solution to provide a global optimization query processing is the restriction of the search space using semantic knowledge (ontology) level of integration system. Our objective in this level is to build the global shared ontology for the system that models knowledge about the domain of interest “the medical field” that we have defined for the application integration scenario. We also provide a structuration for the ontologies in our hybrid integration system that meets its functional architecture. The approach we have adopted enables automatic integration of the e-health sources and it also aims to create first the shared ontology of the system and then to extract local ontologies associated with the sources of real data from the different concepts of the global ontology. Each source contains concepts in the pre-existing domain ontology by referring to his local ontology. This is an “a priori” approach that simplifies the design process and reduces the time for the construction of local ontologies.
Task 1.3: Automatic generation of execution order plan for querying the ARCHIMED system
We present our solution to reduce the search space of a query by imposing a partial optimal order for the access to sources by querying the sources most relevant to a given query and by avoiding access to less relevant sources. It is a new method for automatic generation of an optimized execution order plane of sub queries regarding the degree of importance of sources capable of satisfying the user query based on a weight measure associated with each source or concept and the semantic links that connect the concepts of sources. These two criteria are used when querying for assessing the relevance of a response to a query. To ensure the computability of this plan, we will offer a comprehensive mathematical model and an algorithm for the construction of the canonical graph of order execution for the development of an optimal ordered sequence of relevant data sources for a query.
Task 1.4: Optimization of the interrogation process by the combinatorial data warehousing of sources
Another objective concerns the proposal of an efficient method for automatic classification of data sources by combinatorial data warehousing of sources. This is a query optimization approach based on the classification of data sources to integrate into homogeneous groups of sources (local data warehouses), which respond similarly to changes in user requests. The principle of this classification is based on the knowledge of the distance, similarity and coupling function between all pairs of sources to classify and integrate, and a combination of the principles of two classic methods of classification: the hierarchical top-down method and mobile centers method. Unlike optimizers which consider a restricted search space, the optimizer that we will propose, runs sources groups hierarchically and in depth according to the priority of sources. A performance evaluation of the approach through a comparative study on the distribution network overloaded with the proposed solutions will be designed to validate our approach.
Task 1.5: Develop and use cooperatives ontologies for customizing the interrogation process of a hybrid mediator
The last distinctive point of our approach is the use of cooperative ontologies for the improvement of the integration process of the ARCHIMED system. In order to customize the hybrid mediator, we are interested in taking into account profiles and interests of users in the interrogation process to refine and improve in terms of relevance the search results. To achieve this goal, we performed a classification of ontologies into profile ontology and query ontology. These ontologies cooperate with each other in order to take into account changes in the semantics of the data according to user profiles and the operating mode of the integration system. The proposed technique is based on the interaction between dimensions of the profile represented by the search history in the sources integrated by the hybrid mediator and interests of user groups.
Task 1.6: Define a security and privacy model for patient data
ARCHIMED platform must have a national norm of accommodation of document associated with integrated services: confidence, protection, identification, authentication, management clearances and collection of consent. Therefore, this task focuses on the aspect of security and confidentiality of patient data which is an important issue for the development of uses of ICT in the health sector. The services offered must make the regulatory measures of health data treatment, such:
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Each personal health record will be inviolable, that is to say protected against all risks of intrusion during its storage and transfer.
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All the rules and terms of access as well as the governed use of expression consent, the empowerment of the health professionals, identification, authentication, and traceability access ensure to patients the respect of their right to the confidentiality of their personal data and to exercise health professional secrecy.
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Patients and healthcare professionals are confident that the collection and use of health information will only be used legitimately and be uniformed everywhere and every time for everyone. Moreover, this information can be applied everywhere to protect individuals against inappropriate discrimination or harm from intentional misuse.
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Confidentiality and security protections are uniform and they set a high standard throughout the country for fair, reasonable, and uniform health information practices that respect the rights of the individual and the public (storage, transfer or access).
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Confidentiality, privacy, and security laws and regulations are conscientiously enforced, and those who break these laws or ignore these regulations face vigorous prosecution and serious penalties for their offenses.
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Individuals will have the right to access their health information in any setting and with minimal limits, have an understanding of their privacy rights and options for that setting, be notified about all information practices concerning their information and have the right to appropriately challenge the accuracy of their health information.
4 Conclusion
As like as Health fields, in the distributed environment where a query involves across several heterogeneous sources (Clinical, chirurgical, DMP), communication cost must be taken into consideration. In this perspective we describe tow query optimization approach using dynamic programming technique for a given set of integrated heterogeneous sources. The primary objective of the optimization is to minimize the total processing time including load processing, request rewriting and communication costs, to facilitate communication inter-sites and to optimize the time of data transfer from different sites. Moreover, the ability to store the data on centre site, gives more flexibility in terms of Security/Safety and overload the network. In contrast to optimizers which consider a restricted search space, the proposed optimizer searches the subsets of sources and independency relationship which may be deep laniary or bushy trees. Especially the execution de query can be start traversal anywhere over any subset and not only from a specific one.
The main problem is to maintain a distributed data warehouse, consisting of multiple local data warehouses (sites) adjacent to the collection points, together with a coordinator. In order for such a solution to make sense, we need a technology for the data classification process. We must develop an algorithm for this task. This algorithm translates a set of sources into distributed distinct subsets and generates distributed warehouses, with the following concept: (i) each generated data warehouse performing some computation and communicating the query result to the coordinator, and (ii) the coordinator synchronizing the results and (possibly) communicating with the warehouses. The semantics of the subqueries generated by system ensure that the amount of data that has to be shipped between warehouses is independent of the size of the underlying data at the sites.
The solution allows for a wide variety of optimizations that are easily expressed in the interrogation and thus readily integrated into the query optimizer. The optimization algorithm included in our prototype contribute both to the minimization of synchronization traffic and the optimization of the data processing at the local sites. Significant features of this approach are the ability to perform both distribution-dependent and distribution in dependent optimizations that reduce the data transferred and the number of evaluation rounds.
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Loubna, C., Sarah, K., Mostafa, E. (2019). Analytical Approach for Virtual Classification of e-Health Interventions and Medical Data Sources Integration. In: Ezziyyani, M. (eds) Advanced Intelligent Systems for Sustainable Development (AI2SD’2018). AI2SD 2018. Advances in Intelligent Systems and Computing, vol 914. Springer, Cham. https://doi.org/10.1007/978-3-030-11884-6_26
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