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The document describes the MEDICAS model for a health information system (HIS). MEDICAS is a medical information system that covers a wide range of patient, provider, and healthcare activities. It contains comprehensive electronic health records and can be implemented across all health facilities. The system also allows connection and data exchange with regional and central health information structures. MEDICAS has different subsystems that health institutions can use depending on their specifics, including subsystems for basic healthcare, hospitals, specialist clinics, medical laboratories, and dental clinics.
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Low adoption rates of EMRs in physician practices
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Vital signs monitoring for elderly in daily life environment is a promising concept that efficiently can provide medical services to people at home. However, make the system self-served and functioning as personalized provision makes the challenge even larger. This paper presents a case study on a Health-IoT system where an intelligent healthcare service is developed to monitor vital signs in daily life. Here, a generic Health-IoT framework with a Clinical Decision Support System (CDSS) is presented. The generic framework is mainly focused on the supporting sensors, communication media, secure and safe data communication, cloud-based storage, and remote accesses of the data. The CDSS is used to provide a personalized report on persons‟ health condition based on daily basis observation on vital signs. Six participants, from Spain (n=3) and Slovenia (n=3) have been using the proposed healthcare system for eight weeks (e.g. 300+ health measurements) in their home environments to monitor their health. The sensitivity, specificity and overall accuracy of the DSS‟s classification are achieved as 90%, 97% and 96% respectively while k=2 i.e., top 2 most similar retrieved cases are considered. The initial user evaluation resultdemonstrates the feasibility and performance of the implemented system through the proposed framework.
Understanding the Need of Data Integration in E Healthcare
This paper discusses the current scenario of e healthcare and different dimensions of Big data in healthcare and the importance of data integration in e health care and the challenges associated with data integration and associated uses of data integration with respect to different use cases which might be helpful to physician's decision making because the data driven decision making involves combination of heterogeneous data which includes Electronic Health Record containing different types of data and connected healthcare organization in order to provide value based connected healthcare which would be useful to primary healthcare center located at different location because patients suddenly expect their healthcare experiences to be as exceptional and as transparent as those of retail or banking, and physician's have to scramble to adjust to these new expectations due to lack of data integrity. Mrs. Shashi Rekha. H. | Dr. Chethana Prakash. M | Dr. K. Thippeswamy "Understanding the Need of Data Integration in E- Healthcare" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31007.pdf Paper Url :https://www.ijtsrd.com/engineering/computer-engineering/31007/understanding-the-need-of-data-integration-in-e-healthcare/mrs-shashi-rekha-h
IRJET- Predictive Analysis and Healthcare of Diabetes
This document discusses using machine learning and predictive analysis to help manage diabetes. It proposes a system that collects healthcare data, structures it using Hadoop for storage and analysis, and applies machine learning algorithms like SVM and decision trees to classify patients, predict diabetes types and complications, and determine the best treatment. The goal is to develop an automated diabetes interpretation system that can help provide better, more personalized healthcare by identifying key clinical insights from a patient's diabetes data.
IRJET- A Survey on Big Data Frameworks and Approaches in Health Care Sector
This document discusses how big data frameworks and approaches can benefit the healthcare sector. It first introduces common big data tools like Hadoop, MapReduce, and Apache Sqoop that can be used to analyze large amounts of healthcare data from sources like electronic health records. It then discusses how data warehouse platforms like OpenEHR and EHR4CR can be used to store this healthcare data. The document proposes a framework to retrieve and analyze electronic health records using big data systems. Potential applications of this approach mentioned include improved healthcare analysis, prognosis, report management, and follow-up systems. In conclusion, the integration of big data technologies with healthcare data platforms and sources can provide benefits like personalized care, disease prediction, and support for clinical decision
The concept of a medical information
The objective of our study is to focus on the basic concepts of the medical information systems used for the management of IT information taking place in a hospital center and to share the information in databases depending on its use [2]. Nowadays, many softwares exist for the management of information in a hospital. The professional applications are oriented towards invoicing and accounting, while our application focuses on the systems used in a hospital center such as system of medical services, accounting system, storage system, human resources system, and administrative system (Figure 1)... These systems are considered as subsystems which make up the global system [1]. Our hospital information system is based on different the subsystems for the management of: laboratory results, clinic, images, pharmalogical, and pathological results[8]... So, this rate of huge information must be handled by a database management system like SQL [4,5], and its concept must be detailed using a language like UML [6]. In addition, the graphical user interface (gui) [19] is essential to complete our work, by using the software Visual Basic [10, 11], in order to achieve our software the manipulation of data must have a calibration between the execution time and the amount of data storage[14,15,20]. Hence, the distribution of databases is done according to their rate of use is an encouraging solution
Final case study
mMR is a mobile medical records application developed by Kloud Data that allows healthcare professionals to access patient records from mobile devices. The application provides access to a patient's full medical history, test results, prescriptions, notes and can be used to discharge patients. It has a user-friendly interface compatible with Android and iOS devices. The application ensures security by not storing patient data locally and requiring authentication. Implementing mMR provides doctors access to patient information anytime, improves hospital operations and supports high-quality patient care both inside and outside of hospitals.
CLOUD-BASED DEVELOPMENT OF SMART AND CONNECTED DATA IN HEALTHCARE APPLICATION
There is a need of data integration in cloud – based system, we propose an Information Integration and Informatics framework for cloud – based healthcare application. The data collected by the Electronic Health Record System need to be smart and connected, so we use informatica for the connection of data
from different database. Traditional Electronic Health Record Systems are based on different technologies, languages and Electronic Health Record Standards. Electronic Health Record System stores data based on interaction between patient and provider. There are scalable cloud infrastructures, distributed and heterogeneous healthcare systems and there is a need to develop advanced healthcare application. This advance healthcare application will improve the integration of required data and helps in fast interaction between the patient and the service providers. Thus there is the development of smart
and connected data in healthcare application of cloud. The proposed system is developed by using cloud platform Aneka.
E hdas e- healthcare diagnosis & advisory system
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IEEE DEST CEE 2013 - Paper 4 (1) (1)
The document describes a future model for delivering home and community health care services using new technologies and interoperability standards. It involves:
1. Using e-devices and mobile apps in patients' homes to monitor health and enable remote diagnosis, with data flowing securely between patients and healthcare providers.
2. Developing a system where all the various e-devices and healthcare records can interoperate through common standards, giving providers a full view of patients' care needs.
3. Implementing this new model will require national infrastructures that separate physical networks from shared data and service models, and using standards like OASIS to ensure interoperability.
IEEE DEST 2013 tGov paper eHealth - The Future Service Model for Home & Co...
IEEE DEST 2013 tGov paper eHealth - The Future Service Model for Home & Co...Hans A. Kielland Aanesen
Abstract — This document describes how future home and community health care services can be delivered using a range of new technologies and using standards developed by the EPR-forum and OASIS, and provides an overview of current efforts to build a new demonstrator showing how these services can be provided by the interoperability of the various edevices and systems.An Adaptive Technique in Electronic Health Record for Clinical Decision Makin...
Cloud computing is a collection of several computer resources that consists of both software and hardware. It is a type of service that is delivered over the internet and can be accessible from anywhere. 1 The data and services can be accessed through the internet. 4 These services are managed by the third party over the internet. They eventually provide access to the servers and resources. Health records consist of patient’s data regarding health. This data is usable by both the hospitals and patients. 6 8 This can be eventually used to track the medical history of patients. Data Visualization is a graphical depiction of the data. It implicates producing images that advertise the link among the data that the users view. Hence, they are used for clinical decision making. In this paper we will be discussing how cloud can be used to maintain health records electronically. Meghana Prakash | Vignesh S "An Adaptive Technique in Electronic Health Record for Clinical Decision Making Based on Data Visualization" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30699.pdf Paper Url :https://www.ijtsrd.com/computer-science/other/30699/an-adaptive-technique-in-electronic-health-record-for-clinical-decision-making-based-on-data-visualization/meghana-prakash
MyHealthRecords
Digital health is about electronically connecting up the points of healthcare so that health information can be shared securely.
This is the first step to understanding how digital health can help deliver safer, better and quality healthcare.
“My Health Record” is the new name of the digital health record system.
IRJET- An Android Application for Electronic Health Record System
This document proposes an Android application for an electronic health record (EHR) system. It summarizes that EHR systems use digital records rather than paper to store patient health information like medical history, appointments, lab results, and more. The proposed application would allow patients to book appointments with doctors and view their health records on their phones. It would also give patients the ability to manually enter blood pressure and sugar levels. Doctors could use the app to view patient appointment schedules and send prescriptions. The application aims to improve healthcare services and efficiency by making records easily accessible to both patients and doctors.
IRJET- An Android Application for Electronic Health Record System
This document proposes an Android application for an electronic health record (EHR) system. It summarizes:
1) The application would allow patients to manage appointments with doctors, view medical histories, and manually enter health metrics like blood pressure. Doctors could view patient appointment lists.
2) An admin user could view patient and doctor data. The EHR system would store healthcare information more comprehensively and accessibly than paper records.
3) The system is intended to improve services for patients and doctors by making health records more easily accessible and minimizing data entry errors.
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- 1. MODEL OF HEALTH INFORMATION SYSTEM To explain the work of HIS we can use the same model that has been very extensive applied in practice, or to say that this model is used by many hospitals in our country and abroad. The aforementioned model is called MEDICAS and it is a medical information system for healthcare facilities that cover a very wide range of activities in conjunction with patients, providers and health care system. It contains a comprehensive electronic health record of the patient and is intended to be implemented in all health facilities. In addition, possible is a connection and exchange of data with regional and central structures for the collection and processing of information in health care. On Figure Figure2.2. is presented MEDICAS software package (Source: www.irvas.rs, accessed on Dec. 22, 2011). Depending on the specifics the health institutions consumers can use different subsystems (8, 9). The main subsystems that can be implemented are: MEDICAS GP–Subsystem for basic health care facilities. MEDICAS Hosp–Subsystem for hospitals and medical facilities of the stationary type. MEDICAS Poly–Subsystem for specialist clinics or clinics, MEDICAS Lab–Subsystem for medical laboratories MEDICAS Dent–Subsystem for dental clinic Identification modules are integral parts of the system, a modular system allows any combination of these levels, depending on the specific structure of the health facilities.