Qualifying and measuring transparency: A medical data system case study

Abstract. Medical geography and medical cartography can be denoted as classical application domains for Geographical Information Systems (GISs). GISs can be applied to retrospective analysis (e.g., human population health analysis, medical infrastructure development and availability assessment, etc.), and to operative disaster detection and management (e.g., monitoring of epidemics development and infectious diseases spread). Nevertheless, GISs still not a daily-used instrument of medical administrations, especially on the city and municipality scales. In different regions of the world situation varies, however in general case GIS-based medical data accounting and management is the object of interest for researchers and national administrations operated on global and national scales. Our study is focused onto the investigation and design of the methodology and software prototype for GIS-based support of medical administration and planning on a city scale when accounting and controlling infectious diseases. The study area is the administrative territory of the St. Petersburg (Russia). The study is based upon the medical statistics data and data collection system of the St. Petersburg city. All the medical data used in the study are impersonalized accordingly to the Russian laws.

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Healthcare Oriented Smart House for Elderly and/or Disabled People

Wireless Technologies for Ambient Assisted Living and Healthcare ◽

10.4018/978-1-61520-805-0.ch008 ◽

2010 ◽

pp. 116-140

Author(s):

Nicholas S. Samaras ◽

Costas Chaikalis ◽

Giorgios Siafakas

Keyword(s):

Ieee 802.15.4 ◽

Software Tool ◽

Disabled Persons ◽

Modern Technology ◽

Medical Data ◽

Automation System ◽

Web Interface ◽

Medical Sensors ◽

Smart House

Smart houses represent a modern technology which can secure and facilitate our life. The objective of this chapter is to adapt medical sensors to home automated systems, which collect medical data such as blood pressure, heart rate and electrical heart activity for elderly and/or disabled persons. Firstly, the collected data is transferred to a home server and to an external manager for further analysis. Subsequently, data is stored at a database where monitoring is available only for authorized users via a simple web interface. The IEEE 802.15.4 wireless standard has been chosen as the preferred solution for communication in the smart house. Finally, two implementation scenarios of the smart house for an elderly and/or disabled person are simulated using the Custodian software tool. This case study shows that simulating the automation system of a smart house before the implementation is advantageous.

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Framework Design and Case Study for Privacy-Preserving Medical Data Publishing

International Journal of E-Health and Medical Communications ◽

10.4018/ijehmc.2013100104 ◽

2013 ◽

Vol 4 (4) ◽

pp. 48-65 ◽

Cited By ~ 1

Author(s):

Yu Niu ◽

Ji-Jiang Yang ◽

Qing Wang

Keyword(s):

Data Sharing ◽

Personal Information ◽

Real Life ◽

Privacy Preserving ◽

Medical Data ◽

Data Publishing ◽

Free Text ◽

Patient Privacy ◽

Healthcare Data

With the pervasive using of Electronic Medical Records (EMR) and telemedicine technologies, more and more digital healthcare data are accumulated from multiple sources. As healthcare data is valuable for both commercial and scientific research, the demand of sharing healthcare data has been growing rapidly. Nevertheless, health care data normally contains a large amount of personal information, and sharing them directly would bring huge threaten to the patient privacy. This paper proposes a privacy preserving framework for medical data sharing with the view of practical application. The framework focuses on three key issues of privacy protection during the data sharing, which are privacy definition/detection, privacy policy management, and privacy preserving data publishing. A case study for Chinese Electronic Medical Record (ERM) publishing with privacy preserving is implemented based on the proposed framework. Specific Chinese free text EMR segmentation, Protected Health Information (PHI) extraction, and K-anonymity PHI anonymous algorithms are proposed in each component. The real-life data from hospitals are used to evaluate the performance of the proposed framework and system.

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A Fog Computing-Based Architecture for Medical Records Management

Wireless Communications and Mobile Computing ◽

10.1155/2019/1968960 ◽

2019 ◽

Vol 2019 ◽

pp. 1-16 ◽

Cited By ~ 8

Author(s):

Cícero A. Silva ◽

Gibeon S. Aquino ◽

Sávio R. M. Melo ◽

Dannylo J. B. Egídio

Keyword(s):

Medical Records ◽

Fog Computing ◽

Medical Data ◽

Data Sources ◽

Medical Applications ◽

Records Management ◽

Medical Field ◽

Computing Paradigm ◽

And Storage

The aging of the world’s population and the growth in the number of people with chronic diseases have increased expenses with medical care. Thus, the use of technological solutions has been widely adopted in the medical field to improve the patients’ health. In this context, approaches based on Cloud Computing have been used to store and process the information generated in these solutions. However, using Cloud can create delays that are intolerable for medical applications. Thus, the Fog Computing paradigm emerged as an alternative to overcome this problem, bringing computation and storage closer to the data sources. However, managing medical data stored in Fog is still a challenge. Moreover, characteristics of availability, performance, interoperability, and privacy need to be considered in approaches that aim to explore this problem. So, this article shows a software architecture based on Fog Computing and designed to facilitate the management of medical records. This architecture uses Blockchain concepts to provide the necessary privacy features and to allow Fog Nodes to carry out the authorization process in a distributed way. Finally, this paper describes a case study that evaluates the performance, privacy, and interoperability requirements of the proposed architecture in a home-centered healthcare scenario.

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