Developing an Automatic Diagnostic System Driven by Consumer-Generated Health Care Data

10.5580/ceb ◽  
2010 ◽  
Vol 5 (2) ◽  
Keyword(s):  
Health Care ◽  
Diagnostic System ◽  
Health Care Data

Secure Health Care Data Transmission and Prevention Based on Hybrid Robin Public Key Signature Algorithm

2020 ◽  
Author(s):  
Dr. Karthikeyan Kaliyaperumal ◽  
Dr. C. Suresh Gnana Dhas ◽  
Mrs. F. Sammy
Keyword(s):  
Health Care ◽  
Data Transmission ◽  
Public Key ◽  
Health Care Data

Health-care Data and Databases

2020 ◽  
pp. 47-65
Author(s):  
Anthony C. Chang
Keyword(s):  
Health Care ◽  
Health Care Data

scholarly journals How to Use Blockchain for Diabetes Health Care Data and Access Management: An Operational Concept

2018 ◽  
Vol 13 (2) ◽  
pp. 248-253 ◽  
Author(s):  
Simon Lebech Cichosz ◽  
Mads Nibe Stausholm ◽  
Thomas Kronborg ◽  
Peter Vestergaard ◽  
Ole Hejlesen
Keyword(s):  
Health Care ◽  
Access Management ◽  
Health Care Data ◽  
Operational Concept

42: Understanding End-of-Life Cancer Care in Canada: an Updated 12-Year Retrospective Analysis of Three Provinces’ Administrative Health Care Data

2021 ◽  
Vol 163 ◽  
pp. S20-S21
Author(s):  
Amanda Khan ◽  
Hsien Seow ◽  
Rinku Sutradhar ◽  
Stuart Peacock ◽  
Kelvin Chan ◽  
...  
Keyword(s):  
Health Care ◽  
End Of Life ◽  
Retrospective Analysis ◽  
Cancer Care ◽  
Health Care Data

scholarly journals Confidential Health Care Data Exchange Between Multiple Entities in Cloud using Block Chain

2019 ◽  
Vol 9 (2) ◽  
pp. 2566-2573
Keyword(s):  
Health Care ◽  
Data Exchange ◽  
Health Care Organizations ◽  
Main Concept ◽  
Sensitive Data ◽  
Privacy And Security ◽  
Health Care Data ◽  
Private Data ◽  
Peer Network ◽  
Block Chain

Data in the cloud is leading to the more interest for cyber attackers. These days’ attackers are concentrating more on Health care data. Through data mining performed on health care data Industries are making Business out of it. These changes are affecting the treatment process for many people so careful data processing is required. Breaking these data security leads to many consequences for health care organizations. After braking security computation of private data can be performed. By data storing and running of computation on a sensitive data can be possible by decentralization through peer to peer network. Instead of using the centralized architecture by decentralization the attacks can be reduced. Different security algorithms have been considered. For decentralization we are using block chain technology. Privacy, security and integrity can be achieved by this block chain technology. Many solutions have been discussed to assure the privacy and security for Health care organizations somehow failed to address this problem. Many cryptographic functions can be used for attaining privacy of data. Pseudonymity is the main concept we can use to preserve the health care means preserving data by disclosing true identity legally.

scholarly journals Novel Method for Identifying Care Home Residents in England: A Validation Study

2021 ◽  
Vol 5 (4) ◽  
Author(s):  
Stefano Conti ◽  
Filipe Oliveira dos Santos ◽  
Arne Wolters
Keyword(s):  
Health Care ◽  
Predictive Value ◽  
Care Home ◽  
Care Homes ◽  
Health Care Data ◽  
Patient Level ◽  
Home Address ◽  
Negative Rate ◽  
Routine Identification ◽  
Address Matching

IntroductionThe ability to identify residents of care homes in routinely collected health care data is key to informing healthcare planning decisions and delivery initiatives targeting the older and frail population. Health-care planning and delivery implications at national level concerning this population subgroup have considerably and suddenly grown in urgency following the onset of the COVID-19 pandemic, which has especially hit care homes. The range of applicability of this information has widened with the increased availability in England of retrospectively collected administrative databases, holding rich patient-level details on health and prognostic status who have made or are in contact with the National Health Service. In practice lack of a national registry of care homes residents in England complicates assessing an individual's care home residency status, which has been typically identified via manual address matching from pseudonymised patient-level healthcare databases linked with publicly availably care home address information. ObjectivesTo examine a novel methodology based on linking unique care home address identifiers with primary care patient registration data, enabling routine identification of care home residents in health-care data. MethodsThis study benchmarks the proposed strategy against the manual address matching standard approach through a diagnostic assessment of a stratified random sample of care home post codes in England. ResultsDerived estimates of diagnostic performance, albeit showing a non-insignificant false negative rate (21.98%), highlight a remarkable true negative rate (99.69%) and positive predictive value (99.35%) as well as a satisfactory negative predictive value (88.25%). ConclusionsThe validation exercise lends confidence to the reliability of the novel address matching method as a viable and general alternative to manual address matching.

AUTOGRP: An Interactive Computer System for the Analysis of Health Care Data

Medical Care ◽  
1976 ◽  
Vol 14 (7) ◽  
pp. 603-615 ◽  
Author(s):  
Ronald Mills ◽  
Robert B. Fetter ◽  
Donald C. Riedel ◽  
Richard Averull
Keyword(s):  
Health Care ◽  
Computer System ◽  
Health Care Data
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