Looking through the ‘Magnifying Glass’: Term Maps of Intelligent Medical System

2018 ◽  
Author(s):  
Peter Kokol ◽  
M. Zorman ◽  
V. Podgorelec
Keyword(s):  
Medical System

Medical Data Handling Using Cloud Computing And A Proposal for Countrywide Medical System

2012 ◽  
Vol 7 (1) ◽  
pp. 19-24
Author(s):  
Samayita Bhattacharya ◽  
◽  
Kalyani Mali ◽  
Keyword(s):  
Cloud Computing ◽  
Medical Data ◽  
Medical System ◽  
Data Handling

E-Health as a Service Software of Medical System in Prototype Modeling

2017 ◽  
Vol 4 (2) ◽  
pp. 99-104
Author(s):  
Agus Nursikuwagus
Keyword(s):  
Health Care ◽  
Information System ◽  
Health Service ◽  
Community Health ◽  
Health Center ◽  
Community Health Center ◽  
Community Health Service ◽  
Medical System ◽  
Medical Prescription ◽  
Uml Diagrams

Information system at community health center is an information system that has several activities, such as registration, medical record, health care, and reporting.  Day to day operation, community health service, is using process manually. It is cause the stack of service. Sometime, the patient has to wait within several times. For Further, the patient did not know that the queuing is full. In order to help the problem, this paper wants to show about E-Health as service software. The research is completed by conveying the model like UML diagram. The UML diagrams are consisting such as usecase, class, activity, and component. The sequence of system construct is using Prototype Paradigm. The result is the software which has ability to service patient start from registration, medical check, medical prescription, until reporting. As an impact for Community health service is the service more efficiency. The system is able to control the medicine and reporting on day to day operation.   REFERENCES[1] Susanto, Gunawan,” Sistem Informasi Rekam Medis PadaRumah Sakit Umum Daerah (RSUD) Pacitan Berbasis WebBase”. Pacitan. 2012.[2] B, Nugroho, S.H. Fitriasih, B. Widada, “Sistem InformasiRekam Medis Di Puskesmas Masaran I Sragen”. JournalTIKomSiN, vol.5, no.1, p.49-56, 2017.[3] G.G.S. Bagja,” Membangun Sistem Informasi KesehatanPuskesmas Cibaregbeg”, Univ. Komp. Indonesia, 2010.[4] A.M. Herdy, Aulia, M. Amran, D. Novita, “PerancanganSistem Informasi Pelayanan Medis Di Puskesmas SungaiDua”, STMIK MDP. 2014.[5] J. Sundari, “Sistem Informasi Pelayanan Puskesmas BerbasisWeb”, Int.Journal.on Soft.Eng, vol.2, no.1, p.57-62, 2016.[6] R.S. Pressman, Software Engineering A PractitionersApproach. Nineth Edition, Addsion Wesley, 2011.[7] G. Booch, J. Rumbaugh, I. Jacobson, Unified ModelingLanguage User Guide, Addison-Wesley, 1999.[8] I, Daqiqil. (2011, August 2). Framework CodeIgnite. [Online].Available: http://koder.web.id/buku-codeigniter-gratis/

Design based exploration of medical system adoption: Case of wheelchair ramps

2021 ◽  
Vol 66 ◽  
pp. 101620
Author(s):  
Elvan Dogan Kumtepe ◽  
Eda Çorbacıoğlu ◽  
Ahmet Nuri Başoğlu ◽  
Tugrul Unsal Daim ◽  
Amir Shaygan
Keyword(s):  
Medical System

scholarly journals Factors affecting health care users’ first contact with primary health care facilities in north eastern China, 2008–2018

2021 ◽  
Vol 6 (2) ◽  
pp. e003907
Author(s):  
Ran Liao ◽  
Yaqian Liu ◽  
Shunzhuang Peng ◽  
Xing Lin Feng
Keyword(s):  
Health Care ◽  
Primary Health Care ◽  
Eastern China ◽  
Medical System ◽  
Health Care Facilities ◽  
Factors Affecting ◽  
Primary Health ◽  
North Eastern ◽  
First Contact ◽  
Hierarchical Medical System

BackgroundChina set out the vision to establishing a hierarchical medical system, with primary health care (PHC) facilities serving health care users’ first contact. Common ailments were listed, supported by a series of auxiliary policy measures. We aim to assess whether these policies were effective to prompt users’ preference to PHCs within these contexts.MethodsUsing data from three waves of National Health Service Survey, we examined trends in care users’ first contact with PHC facilities in Jilin, a north eastern province, during 2008–2018. We analysed trends and factors affecting care users’ choices, stratified by type of diseases and urban–rural settings.ResultsFrom 38 823 respondents, the survey identified 3302 health care users who sought outpatient care. 54.92% and 82.49% with diseases recommended to PHC, in urban and rural Jilin, respectively, contacted PHC facilities first. While 33.51% and 61.19% with diseases not recommended to PHC did so. Care users’ first contact with PHC facilities followed an inverse U shape during 2008–2018. Such trends were more profound among care users with hypertension and/or diabetes. Neither social health insurance coverage nor contracting with family doctors was associated with care users’ first contacts. Only 1.25% care users had referral experiences. Low perceived quality was the main barrier to choose PHC facilities.ConclusionHealth care users sought PHC in a chaotic manner in Jilin. None of the recent efforts seemed effective in prompting their preference to PHC facilities. Without levering quality of PHC, an effective hierarchical medical system could be hardly forged in China.

Calculating estimated glomerular filtration rate without the race correction factor: observations at a large academic medical system

2021 ◽  
Author(s):  
Junyan Shi ◽  
Edwin G. Lindo ◽  
Geoffrey S. Baird ◽  
Bessie Young ◽  
Michael Ryan ◽  
...  
Keyword(s):  
Glomerular Filtration Rate ◽  
Glomerular Filtration ◽  
Correction Factor ◽  
Filtration Rate ◽  
Estimated Glomerular Filtration Rate ◽  
Medical System ◽  
Academic Medical

scholarly journals Design and Evaluation of Large-Scale IoT-Enabled Healthcare Architecture

2021 ◽  
Vol 11 (8) ◽  
pp. 3623
Author(s):  
Omar Said ◽  
Amr Tolba
Keyword(s):  
Packet Loss ◽  
Large Scale ◽  
Performance Metrics ◽  
Medical System ◽  
Healthcare Data ◽  
High Altitude Platforms ◽  
Wide Range ◽  
Simulation Results ◽  
Healthcare Architecture ◽  
The Internet Of Things

Employment of the Internet of Things (IoT) technology in the healthcare field can contribute to recruiting heterogeneous medical devices and creating smart cooperation between them. This cooperation leads to an increase in the efficiency of the entire medical system, thus accelerating the diagnosis and curing of patients, in general, and rescuing critical cases in particular. In this paper, a large-scale IoT-enabled healthcare architecture is proposed. To achieve a wide range of communication between healthcare devices, not only are Internet coverage tools utilized but also satellites and high-altitude platforms (HAPs). In addition, the clustering idea is applied in the proposed architecture to facilitate its management. Moreover, healthcare data are prioritized into several levels of importance. Finally, NS3 is used to measure the performance of the proposed IoT-enabled healthcare architecture. The performance metrics are delay, energy consumption, packet loss, coverage tool usage, throughput, percentage of served users, and percentage of each exchanged data type. The simulation results demonstrate that the proposed IoT-enabled healthcare architecture outperforms the traditional healthcare architecture.

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