A Blockchain Framework for Healthcare Data Management Using Consensus Based Selective Mirror Test Approach

2021 ◽  
pp. 77-95
Author(s):  
P. S. G. Aruna Sri ◽  
D. Lalitha Bhaskari
Keyword(s):  
Data Management ◽  
Healthcare Data

Exploring Factors Influencing Big Data and Analytics Adoption in Healthcare Management

2020 ◽  
pp. 413-428
Author(s):  
Sampson Abeeku Edu ◽  
Divine Q. Agozie
Keyword(s):  
Big Data ◽  
Data Management ◽  
Patient Management ◽  
Technological Development ◽  
Healthcare Management ◽  
Quality Cost ◽  
Healthcare Data ◽  
Management Quality ◽  
Factors Influencing ◽  
Quality Decision

Demand for improvement in healthcare management in the areas of quality, cost, and patient care has been on the upsurge because of technology. Incessant application and new technological development to manage healthcare data significantly led to leveraging on the use of big data and analytics (BDA). The application of the capabilities from BDA has provided healthcare institutions with the ability to make critical and timely decisions for patients and data management. Adopting BDA by healthcare institutions hinges on some factors necessitating its application. This study aims to identify and review what influences healthcare institutions towards the use of business intelligence and analytics. With the use of a systematic review of 25 articles, the study identified nine dominant factors driving healthcare institutions to BDA adoption. Factors such as patient management, quality decision making, disease management, data management, and promoting healthcare efficiencies were among the highly ranked factors influencing BDA adoption.

scholarly journals Healthcare data management issues and the eCert solution

2011 ◽  
Author(s):  
Lisha Chen-Wilson ◽  
Xin Wang ◽  
Gary B Wills ◽  
David Argles ◽  
Charles Shoniregun
Keyword(s):  
Data Management ◽  
Healthcare Data ◽  
Management Issues

scholarly journals Blockchain Applications for Healthcare Data Management

2019 ◽  
Vol 25 (1) ◽  
pp. 51 ◽  
Author(s):  
Dimiter V. Dimitrov
Keyword(s):  
Data Management ◽  
Healthcare Data

Authentic Cloud-biometric Signature Verification System for Healthcare Data Management

2020 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Gunasekar Thangarasu ◽  
KAYALVIZHI SUBRAMANIAN ◽  
P. D. D. Dominic
Keyword(s):  
Data Management ◽  
Signature Verification ◽  
Healthcare Data ◽  
Verification System

scholarly journals Healthcare data management, regarding the growing popularity of precision medicine

2019 ◽  
Vol 14 (3) ◽  
pp. 99-111
Author(s):  
Katarzyna Maciejewska
Keyword(s):  
Data Management ◽  
Precision Medicine ◽  
Human Genome ◽  
Human Genome Project ◽  
Genome Project ◽  
Healthcare Data

Medycyna precyzyjna, która zajmuje się badaniem genezy chorób na podstawie DNA, zyskuje coraz większą popularność na świecie za sprawą dynamicznego rozwoju technologii sekwencjonowania materiału genetycznego. W roku 2003 został ukończony projekt poznania ludzkiego genomu (ang. Human Genome Project, HGP), który trwał 15 lat i który kosztował 2,7 miliarda dolarów. Obecnie koszt przeprowadzenia badania genomu wynosi około 1000 dolarów i trwa zaledwie od kilku godzin do kilku dni w zależności od wybranej technologii. W niniejszej pracy zostały opisane wybrane pojęcia związane z medycyną precyzyjną i zarządzaniem danymi w systemach ochrony zdrowia. Ze względu na znaczne obniżenie kosztów związanych z przeprowadzaniem testów genetycznych stały się one bardziej dostępne i mogą być brane pod uwagę w procesie diagnozowania i leczenia pacjentów. Omawiane techniki i metody generują dużą ilość danych medycznych, które powinny być zarządzane i wykorzystywane również w profilaktycznej opiece zdrowotnej.

scholarly journals Applications of Blockchain Technology in Medicine and Healthcare: Challenges and Future Perspectives

Cryptography ◽  
2019 ◽  
Vol 3 (1) ◽  
pp. 3 ◽  
Author(s):  
Asad Ali Siyal ◽  
Aisha Zahid Junejo ◽  
Muhammad Zawish ◽  
Kainat Ahmed ◽  
Aiman Khalil ◽  
...  
Keyword(s):  
Data Management ◽  
Cyber Security ◽  
Financial Services ◽  
Brain Research ◽  
Food Science ◽  
Healthcare Industry ◽  
Future Perspectives ◽  
Healthcare Data ◽  
Blockchain Technology ◽  
Effective Diagnosis

Blockchain technology has gained considerable attention, with an escalating interest in a plethora of numerous applications, ranging from data management, financial services, cyber security, IoT, and food science to healthcare industry and brain research. There has been a remarkable interest witnessed in utilizing applications of blockchain for the delivery of safe and secure healthcare data management. Also, blockchain is reforming the traditional healthcare practices to a more reliable means, in terms of effective diagnosis and treatment through safe and secure data sharing. In the future, blockchain could be a technology that may potentially help in personalized, authentic, and secure healthcare by merging the entire real-time clinical data of a patient’s health and presenting it in an up-to-date secure healthcare setup. In this paper, we review both the existing and latest developments in the field of healthcare by implementing blockchain as a model. We also discuss the applications of blockchain, along with the challenges faced and future perspectives.

Exploring Factors Influencing Big Data and Analytics Adoption in Healthcare Management

2022 ◽  
pp. 1433-1449
Author(s):  
Sampson Abeeku Edu ◽  
Divine Q. Agozie
Keyword(s):  
Big Data ◽  
Data Management ◽  
Patient Management ◽  
Technological Development ◽  
Healthcare Management ◽  
Quality Cost ◽  
Healthcare Data ◽  
Management Quality ◽  
Factors Influencing ◽  
Quality Decision

Demand for improvement in healthcare management in the areas of quality, cost, and patient care has been on the upsurge because of technology. Incessant application and new technological development to manage healthcare data significantly led to leveraging on the use of big data and analytics (BDA). The application of the capabilities from BDA has provided healthcare institutions with the ability to make critical and timely decisions for patients and data management. Adopting BDA by healthcare institutions hinges on some factors necessitating its application. This study aims to identify and review what influences healthcare institutions towards the use of business intelligence and analytics. With the use of a systematic review of 25 articles, the study identified nine dominant factors driving healthcare institutions to BDA adoption. Factors such as patient management, quality decision making, disease management, data management, and promoting healthcare efficiencies were among the highly ranked factors influencing BDA adoption.

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