Addressing health information privacy with a novel cloud-based PHR system architecture

Patient Health Records (PHRs) shift the ownership of health data from health providers to patients. Such a shift poses important challenges from the data privacy point of view. Patients would like to be able to selectively reveal information to other stakeholders and, at the same time, be assured that their health information will not be used improperly once shared. Current PHR systems partially fail to satisfy these requirements. In this paper, we show that both requirements can be satisfied fully when adopting a novel cloud-based PHR system architecture.We expain the role of remote virtual machines in this architecture and use interaction models to reason about privacy implications. Finally, we evaluate MyPHRMachines, a prototypical implementation of the architecture: we demonstrate that the system enables the execution of third party genome analysis services on patientowned genome data while ensuring that (1) such services cannot maliciously store this data and (2) patients can show the analysis results to experts without sharing along their full genome

Integrated, reliable and cloud-based personal health record: a scoping review.

Personal Health Records (PHR) emerge as an alternative to integrate patient’s health information to give a global view of patients' status. However, integration is not a trivial feature when dealing with a variety electronic health systems from healthcare centers. Access to PHR sensitive information must comply with privacy policies defined by the patient. Architecture PHR design should be in accordance to these, and take advantage of nowadays technology. Cloud computing is a current technology that provides scalability, ubiquity, and elasticity features. This paper presents a scoping review related to PHR systems that achieve three characteristics: integrated, reliable and cloud-based. We found 101 articles that addressed thosecharacteristics. We identified four main research topics: proposal/developed systems, PHR recommendations for development, system integration and standards, and security and privacy. Integration is tackled with HL7 CDA standard. Information reliability is based in ABE security-privacy mechanism. Cloud-based technology access is achieved via SOA.CONACYT - Consejo Nacional de Ciencia y TecnologíaPROCIENCI

A hybrid model for managing personal health records in South Africa

Doctors can experience difficulty in accessing medical information of new patients. One reason for this is that the management of medical records is mostly institution-centred. The lack of access to medical information may negatively affect patients in several ways. These include new medical tests that may need to be carried out at a cost to the patient and doctors prescribing drugs to which the patient is allergic. This research investigates how patients can play an active role in sharing their personal health records (PHRs) with doctors located in geographically separate areas. In order to achieve the goal of this research, existing literature concerning medical health records and standards was reviewed. A literature review of techniques that can be used to ensure privacy of health information was also undertaken. Interview studies were carried out with three medical practices in Port Elizabeth with the aim of contextualising the findings from the literature study. The Design Science Research methodology was used for this research. A Hybrid Model for Managing Personal Health Records in South Africa is proposed. This model allows patients to view their PHRs on their mobile phones and medical practitioners to manage the patients’ PHRs using a web-based application. The patients’ PHR information is stored both on a cloud server and on mobile devices hence the hybrid nature. Two prototypes were developed as a proof of concept; a mobile application for the patients and a web-based application for the medical practitioners. A field study was carried out with the NMMU health services department and 12 participants over a period of two weeks. The results of the field study were highly positive. The successful evaluation of the prototypes provides empirical evidence that the proposed model brings us closer to the realisation of ubiquitous access to PHRS in South Africa

A Novel Big Data Approach Using Fuzzy Rule Based Multilayer Perceptrons

They are faced with immense quantities and high velocity of data with complicated structures in the big data era. Social networks, sensors, online and offline transactions, and our daily lives can all produce data. When big data is processed correctly, it can lead to relevant, helpful and useful decisions being made in a number of areas, including government, business, management, and medicine and healthcare. Large amounts of data on healthcare have the ability to significantly enhance patient outcomes, predict epidemics, provide insightful information, prevent diseases that may be prevented, reduce the cost of healthcare delivery, and generally increase life. Big data is made up of patient data that is gathered for remote healthcare applications that differs in terms of volume, velocity, variety, veracity, and value.  Healthcare data classification presents a number of challenges for big data since it gathers huge quantities of data. Processing a heterogeneous collection of this size requires a specialized approach, making it one of the most difficult challenges. The paper presents a novel big data approach using fuzzy rule-based multilayer perceptrons to address these problems. Big data offers the ability to accumulate, analyze, manage, and integrate large amounts of disparate, structured, and unstructured information generated by the healthcare systems of currently. A FRCNN (Fuzzy Region based Convolutional Neural Network) classifier is designed to perform normal and disease classification. Accuracy, precision, recall, and F1-score are only some of the performance criteria used to evaluate this model

Cloud Computing in Healthcare – a Literature Review on Current State of Research

Nowadays, IT resources are increasingly being used in all areas of the health sector. Cloud computing offers a promising approach to satisfy the IT needs in a favorable way. Despite numerous publications in the context of cloud computing in healthcare, there is no systematic review on current research so far. This paper addresses the gap and is aimed to identify the state of research and determine the potential areas of future research in the domain. We conduct a structured literature search based on an established framework. Through clustering of the research goals of the found papers we derive research topics including developing cloud-based applications, platforms or brokers, security and privacy mechanisms, and benefit assessments for the use of cloud computing in healthcare. We hence analyze current research results across the topics and deduce areas for future research, e.g., development, validation and improvement of proposed solutions, an evaluation framework

A Review of Blockchain Technology Based Techniques to Preserve Privacy and to Secure for Electronic Health Records

Research has been done to broaden the block chain’s use cases outside of finance since Bitcoin introduced it. One sector where block chain is anticipated to have a big influence is healthcare. Researchers and practitioners in health informatics constantly struggle to keep up with the advancement of this field's new but quickly expanding body of research. This paper provides a thorough analysis of recent studies looking into the application of block chain based technology within the healthcare sector. Electronic health records (EHRs) are becoming a crucial tool for health care practitioners in achieving these objectives and providing high-quality treatment. Technology and regulatory barriers, such as concerns about results and privacy issues, make it difficult to use these technologies. Despite the fact that a variety of efforts have been introduced to focus on the specific privacy and security needs of future applications with functional parameters, there is still a need for research into the application, security and privacy complexities, and requirements of block chain based healthcare applications, as well as possible security threats and countermeasures. The primary objective of this article is to determine how to safeguard electronic health records (EHRs) using block chain technology in healthcare applications. It discusses contemporary HyperLedgerfabrics techniques, Interplanar file storage systems with block chain capabilities, privacy preservation techniques for EHRs, and recommender systems

Balancing patient control and practical access policy for electronic health records via blockchain technology

Electronic health records (EHRs) have revolutionized the health information technology domain, as patient data can be easily stored and accessed within and among medical institutions. However, in working towards nationwide patient engagement and interoperability goals, recent literature adopts a very patient-centric model---patients own their universal, holistic medical records and control exactly who can access their health data. I contend that this approach is largely impractical for healthcare workflows, where many separate providers require access to health records for care delivery. My work investigates the potential of a blockchain network to balance patient control and provider accessibility with a two-fold approach. First, I conduct a survey investigation to identify patient concerns and determine the level of control patients would like over their health information. Second, I implement a blockchain network prototype to address the spectrum of patient control preferences and automate practical access policy. There are conflicting demands amongst patients and providers for EHR access---privacy versus flexibility. Yet, I find blockchain technology, when manipulated to model access states, automate an organizational role-based access scheme, and provide an immutable history of behavior in the network, to be a very plausible solution for balancing patient desires and provider needs. My approach is, to my knowledge, the first example of blockchain\u27s use for less patient-centric, nudge theory-based EHR access control, an idea that could align access control interests as academics, the government, and the healthcare industry make strides towards interoperable, universal patient records

Privacy-Conflict Resolution for Integrating Personal and Electronic Health Records in Blockchain-Based Systems

Integrating personal health records (PHRs) and electronic health records (EHRs) facilitates the provision of novel services to individuals, researchers, and healthcare practitioners. Simultaneously, integrating healthcare data leads to complexities arising from the structural and semantic heterogeneity within the data. The subject of healthcare data evokes strong emotions due to concerns surrounding privacy breaches. Blockchain technology is employed to address the issue of patient data privacy in inter-organizational processes, as it facilitates patient data ownership and promotes transparency in its usage. At the same time, blockchain technology creates new challenges for e-healthcare systems, such as data privacy, observability, and online enforceabil-ity. This article proposes designing and formalizing automatic conflict resolution techniques in decentralized e-healthcare systems. The present study expounds upon our concepts by employing a running case study centered around preventive and personalized healthcare domains. © 2023, Partners in Digital Health. All rights reserved

NEW SECURE SOLUTIONS FOR PRIVACY AND ACCESS CONTROL IN HEALTH INFORMATION EXCHANGE

In the current digital age, almost every healthcare organization (HCO) has moved from storing patient health records on paper to storing them electronically. Health Information Exchange (HIE) is the ability to share (or transfer) patients’ health information between different HCOs while maintaining national security standards like the Health Insurance Portability and Accountability Act (HIPAA) of 1996. Over the past few years, research has been conducted to develop privacy and access control frameworks for HIE systems. The goal of this dissertation is to address the privacy and access control concerns by building practical and efficient HIE frameworks to secure the sharing of patients’ health information. The first solution allows secure HIE among different healthcare providers while focusing primarily on the privacy of patients’ information. It allows patients to authorize a certain type of health information to be retrieved, which helps prevent any unintentional leakage of information. The privacy solution also provides healthcare providers with the capability of mutual authentication and patient authentication. It also ensures the integrity and auditability of health information being exchanged. The security and performance study for the first protocol shows that it is efficient for the purpose of HIE and offers a high level of security for such exchanges. The second framework presents a new cloud-based protocol for access control to facilitate HIE across different HCOs, employing a trapdoor hash-based proxy signature in a novel manner to enable secure (authenticated and authorized) on-demand access to patient records. The proposed proxy signature-based scheme provides an explicit mechanism for patients to authorize the sharing of specific medical information with specific HCOs, which helps prevent any undesired or unintentional leakage of health information. The scheme also ensures that such authorizations are authentic with respect to both the HCOs and the patient. Moreover, the use of proxy signatures simplifies security auditing and the ability to obtain support for investigations by providing non-repudiation. Formal definitions, security specifications, and a detailed theoretical analysis, including correctness, security, and performance of both frameworks are provided which demonstrate the improvements upon other existing HIE systems

Big Data and the Internet of Things

Advances in sensing and computing capabilities are making it possible to embed increasing computing power in small devices. This has enabled the sensing devices not just to passively capture data at very high resolution but also to take sophisticated actions in response. Combined with advances in communication, this is resulting in an ecosystem of highly interconnected devices referred to as the Internet of Things - IoT. In conjunction, the advances in machine learning have allowed building models on this ever increasing amounts of data. Consequently, devices all the way from heavy assets such as aircraft engines to wearables such as health monitors can all now not only generate massive amounts of data but can draw back on aggregate analytics to "improve" their performance over time. Big data analytics has been identified as a key enabler for the IoT. In this chapter, we discuss various avenues of the IoT where big data analytics either is already making a significant impact or is on the cusp of doing so. We also discuss social implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski (eds.) Big Data Analysis: New algorithms for a new society, Springer Series on Studies in Big Data, to appea