Geostatistical Analysis of Health Data: State-of-the-Art and Perspectives

2008 ◽  
pp. 3-22 ◽  
Author(s):  
P. Goovaerts
Keyword(s):  
State Of The Art ◽  
Health Data ◽  
Geostatistical Analysis

scholarly journals Doctors Routinely Share Health Data Electronically Under HIPAA, and Sharing With Patients and Patients’ Third-Party Health Apps is Consistent: Interoperability and Privacy Analysis

10.2196/19818 ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. e19818
Author(s):  
Mark Savage ◽  
Lucia Clara Savage
Keyword(s):  
Information Exchange ◽  
State Of The Art ◽  
Digital Health ◽  
Health Data ◽  
Third Party ◽  
Health It ◽  
Basic Principles ◽  
Health Records ◽  
Health Apps ◽  
Shared Information

Since 2000, federal regulations have affirmed that patients have a right to a complete copy of their health records from their physicians and hospitals. Today, providers across the nation use electronic health records and electronic information exchange for health care, and patients are choosing digital health apps to help them manage their own health and health information. Some doctors and health systems have voiced concern about whether they may transmit a patient’s data upon the patient’s request to the patient or the patient’s health app. This hesitation impedes shared information and care coordination with patients. It impairs patients’ ability to use the state-of-the-art digital health tools they choose to track and manage their health. It undermines the ability of patients’ family caregivers to monitor health and to work remotely to provide care by using the nearly unique capabilities of health apps on people’s smartphones. This paper explains that sharing data electronically with patients and patients’ third-party apps is legally consistent under the Health Insurance Portability and Accountability Act (HIPAA) with routine electronic data sharing with other doctors for treatment or with insurers for reimbursement. The paper explains and illustrates basic principles and scenarios around sharing with patients, including patients’ third-party apps. Doctors routinely and legally share health data electronically under HIPAA whether or not their organizations retain HIPAA responsibility. Sharing with patients and patients’ third-party apps is no different and should be just as routine.

scholarly journals Doctors Routinely Share Health Data Electronically Under HIPAA, and Sharing With Patients and Patients’ Third-Party Health Apps is Consistent: Interoperability and Privacy Analysis (Preprint)

2020 ◽  
Author(s):  
Mark Savage ◽  
Lucia Clara Savage
Keyword(s):  
Information Exchange ◽  
State Of The Art ◽  
Digital Health ◽  
Health Data ◽  
Third Party ◽  
Health It ◽  
Basic Principles ◽  
Health Records ◽  
Health Apps ◽  
Shared Information

UNSTRUCTURED Since 2000, federal regulations have affirmed that patients have a right to a complete copy of their health records from their physicians and hospitals. Today, providers across the nation use electronic health records and electronic information exchange for health care, and patients are choosing digital health apps to help them manage their own health and health information. Some doctors and health systems have voiced concern about whether they may transmit a patient’s data upon the patient’s request to the patient or the patient’s health app. This hesitation impedes shared information and care coordination with patients. It impairs patients’ ability to use the state-of-the-art digital health tools they choose to track and manage their health. It undermines the ability of patients’ family caregivers to monitor health and to work remotely to provide care by using the nearly unique capabilities of health apps on people’s smartphones. This paper explains that sharing data electronically with patients and patients’ third-party apps is legally consistent under the Health Insurance Portability and Accountability Act (HIPAA) with routine electronic data sharing with other doctors for treatment or with insurers for reimbursement. The paper explains and illustrates basic principles and scenarios around sharing with patients, including patients’ third-party apps. Doctors routinely and legally share health data electronically under HIPAA whether or not their organizations retain HIPAA responsibility. Sharing with patients and patients’ third-party apps is no different and should be just as routine.

scholarly journals Ensuring Confidentiality of Geocoded Health Data: Assessing Geographic Masking Strategies for Individual-Level Data

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Paul A. Zandbergen
Keyword(s):  
Public Health ◽  
Recent Progress ◽  
State Of The Art ◽  
Random Perturbation ◽  
Health Data ◽  
The Other ◽  
Individual Level ◽  
Current State ◽  
Level Data ◽  
Geocoded Data

Public health datasets increasingly use geographic identifiers such as an individual’s address. Geocoding these addresses often provides new insights since it becomes possible to examine spatial patterns and associations. Address information is typically considered confidential and is therefore not released or shared with others. Publishing maps with the locations of individuals, however, may also breach confidentiality since addresses and associated identities can be discovered through reverse geocoding. One commonly used technique to protect confidentiality when releasing individual-level geocoded data is geographic masking. This typically consists of applying a certain amount of random perturbation in a systematic manner to reduce the risk of reidentification. A number of geographic masking techniques have been developed as well as methods to quantity the risk of reidentification associated with a particular masking method. This paper presents a review of the current state-of-the-art in geographic masking, summarizing the various methods and their strengths and weaknesses. Despite recent progress, no universally accepted or endorsed geographic masking technique has emerged. Researchers on the other hand are publishing maps using geographic masking of confidential locations. Any researcher publishing such maps is advised to become familiar with the different masking techniques available and their associated reidentification risks.

scholarly journals A Comprehensive Survey on Security and Privacy for Electronic Health Data

2021 ◽  
Vol 18 (18) ◽  
pp. 9668
Author(s):  
Se-Ra Oh ◽  
Young-Duk Seo ◽  
Euijong Lee ◽  
Young-Gab Kim
Keyword(s):  
Health Systems ◽  
State Of The Art ◽  
Fog Computing ◽  
Health Data ◽  
Security And Privacy ◽  
Health Security ◽  
Comprehensive Survey ◽  
Security Concerns ◽  
Edge And Fog Computing ◽  
Privacy Issues

Recently, the integration of state-of-the-art technologies, such as modern sensors, networks, and cloud computing, has revolutionized the conventional healthcare system. However, security concerns have increasingly been emerging due to the integration of technologies. Therefore, the security and privacy issues associated with e-health data must be properly explored. In this paper, to investigate the security and privacy of e-health systems, we identified major components of the modern e-health systems (i.e., e-health data, medical devices, medical networks and edge/fog/cloud). Then, we reviewed recent security and privacy studies that focus on each component of the e-health systems. Based on the review, we obtained research taxonomy, security concerns, requirements, solutions, research trends, and open challenges for the components with strengths and weaknesses of the analyzed studies. In particular, edge and fog computing studies for e-health security and privacy were reviewed since the studies had mostly not been analyzed in other survey papers.

scholarly journals Fundamental privacy rights in a pandemic state

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252169
Author(s):  
Tânia Carvalho ◽  
Pedro Faria ◽  
Luís Antunes ◽  
Nuno Moniz
Keyword(s):  
Risk Analysis ◽  
Data Protection ◽  
State Of The Art ◽  
Health Data ◽  
Privacy Rights ◽  
Data Set ◽  
Health Authorities ◽  
Identity Disclosure ◽  
Decision Making Processes ◽  
Regional Health Authorities

Faced with the emergence of the Covid-19 pandemic, and to better understand and contain the disease’s spread, health organisations increased the collaboration with other organisations sharing health data with data scientists and researchers. Data analysis assists such organisations in providing information that could help in decision-making processes. For this purpose, both national and regional health authorities provided health data for further processing and analysis. Shared data must comply with existing data protection and privacy regulations. Therefore, a robust de-identification procedure must be used, and a re-identification risk analysis should also be performed. De-identified data embodies state-of-the-art approaches in Data Protection by Design and Default because it requires the protection of direct and indirect identifiers (not just direct). This article highlights the importance of assessing re-identification risk before data disclosure by analysing a data set of individuals infected by Covid-19 that was made available for research purposes. We stress that it is highly important to make this data available for research purposes and that this process should be based on the state of the art methods in Data Protection by Design and by Default. Our main goal is to consider different re-identification risk analysis scenarios since the information on the intruder side is unknown. Our conclusions show that there is a risk of identity disclosure for all of the studied scenarios. For one, in particular, we proceed to an example of a re-identification attack. The outcome of such an attack reveals that it is possible to identify individuals with no much effort.

scholarly journals Degradation assessment of bearing based on machine learning classification matrix

2021 ◽  
Vol 23 (2) ◽  
pp. 395-404
Author(s):  
Satish Kumar ◽  
Paras Kumar ◽  
Girish Kumar
Keyword(s):  
Machine Learning ◽  
State Of The Art ◽  
Research Work ◽  
Health Data ◽  
Classification Model ◽  
Data Driven ◽  
Prognostic Models ◽  
Machine Learning Classification ◽  
Bearing Condition Monitoring ◽  
Model Review

In the broad framework of degradation assessment of bearing, the final objectives of bearing condition monitoring is to evaluate different degradation states and to estimate the quantitative analysis of degree of performance degradation. Machine learning classification matrices have been used to train models based on health data and real time feedback. Diagnostic and prognostic models based on data driven perspective have been used in the prior research work to improve the bearing degradation assessment. Industry 4.0 has required the research in advanced diagnostic and prognostic algorithm to enhance the accuracy of models. A classification model which is based on machine learning classification matrix to assess the degradation of bearing is proposed to improve the accuracy of classification model. Review work demonstrates the comparisons among the available state-of-the-art methods. In the end, unexplored research technical challenges and niches of opportunity for future researchers are discussed.

scholarly journals A Comparative Study of Bluetooth SPP, PAN and GOEP for Efficient Exchange of Healthcare Data

2021 ◽  
Vol 5 (3) ◽  
pp. 279-293
Author(s):  
Athanasios Kiourtis ◽  
Argyro Mavrogiorgou ◽  
Dimosthenis Kyriazis
Keyword(s):  
Information Exchange ◽  
Data Exchange ◽  
Health Information Exchange ◽  
State Of The Art ◽  
Communication Technologies ◽  
Health Data ◽  
Third Party ◽  
Healthcare Data ◽  
Efficient Data ◽  
Distance Communication

Objectives: Current research aims to address the challenges of exchanging healthcare information, since when this information has to be shared, this happens by specifically designed medical applications or even by the patients themselves. Among the problems that the Health Information Exchange (HIE) initiative is facing are that (i) third party health data cannot be accessed without internet, (ii) there exist crucial delays in accessing citizens’ data, (iii) the direct HIE can only happen among Healthcare Institutions. Methods: Towards the solution of these issues, a Device-to-Device (D2D) protocol has been specified, running on top of the Bluetooth protocol for efficient data exchange. This research is focused on this D2D protocol, by comparing the different Bluetooth profiles that can be used for transmitting this data, based on specific metrics considering the probabilities of transferring erroneous data. Findings: An evaluation of three Bluetooth profiles takes place, concluding that two of the three profiles must be used to respect the D2D protocol nature and be fully supported by the main market vendors’ operating systems. Novelty:Based on this evaluation, the specified D2D protocol has been built on top of state-of-the-art short-range distance communication technologies, fully supporting the healthcare ecosystem towards the HIE paradigm. Doi: 10.28991/esj-2021-01276 Full Text: PDF

Practical Picture Processing

1974 ◽  
Vol 32 ◽  
pp. 338-339
Author(s):  
T. A. Welton
Keyword(s):  
Radiation Damage ◽  
Coherence Length ◽  
Spatial Information ◽  
State Of The Art ◽  
Coherent Radiation ◽  
The State ◽  
Energy Spread ◽  
Electron Micrograph ◽  
Picture Processing ◽  
Molecular Skeleton

Various authors have emphasized the spatial information resident in an electron micrograph taken with adequately coherent radiation. In view of the completion of at least one such instrument, this opportunity is taken to summarize the state of the art of processing such micrographs. We use the usual symbols for the aberration coefficients, and supplement these with £ and 6 for the transverse coherence length and the fractional energy spread respectively. He also assume a weak, biologically interesting sample, with principal interest lying in the molecular skeleton remaining after obvious hydrogen loss and other radiation damage has occurred.

A Macintosh Interface for the Cameca Camebax-Micro Electron Microprobe

1990 ◽  
Vol 48 (1) ◽  
pp. 438-439
Author(s):  
Carl E. Henderson
Keyword(s):  
Electron Microprobe ◽  
Processing Speed ◽  
Word Processing ◽  
State Of The Art ◽  
Computer Control ◽  
Third Party ◽  
Disk Storage ◽  
The Past ◽  
User Facility ◽  
Instrument Control

Over the past few years it has become apparent in our multi-user facility that the computer system and software supplied in 1985 with our CAMECA CAMEBAX-MICRO electron microprobe analyzer has the greatest potential for improvement and updating of any component of the instrument. While the standard CAMECA software running on a DEC PDP-11/23+ computer under the RSX-11M operating system can perform almost any task required of the instrument, the commands are not always intuitive and can be difficult to remember for the casual user (of which our laboratory has many). Given the widespread and growing use of other microcomputers (such as PC’s and Macintoshes) by users of the microprobe, the PDP has become the “oddball” and has also fallen behind the state-of-the-art in terms of processing speed and disk storage capabilities. Upgrade paths within products available from DEC are considered to be too expensive for the benefits received. After using a Macintosh for other tasks in the laboratory, such as instrument use and billing records, word processing, and graphics display, its unique and “friendly” user interface suggested an easier-to-use system for computer control of the electron microprobe automation. Specifically a Macintosh IIx was chosen for its capacity for third-party add-on cards used in instrument control.

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