MicroShare: Privacy-Preserved Medical Resource Sharing through MicroService Architecture

Yang, Yu-Bin; Zu, Quan; Liu, Peng; Ouyang, Defang; Li, Xiaoshan

doi:10.7150/ijbs.24617

Cited by 26 publications

(9 citation statements)

References 27 publications

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“…A microservice architecture is one that decomposes a monolithic application into a set of smaller loosely coupled services communicating over well-defined interfaces [ 20 ]. Advantages of a microservice architecture as opposed to a monolithic approach have been known in the IT industry in recent years (e.g., Amazon [ 21 ], Netflix [ 22 ]) and recently for health data [ 23 ].…”

Section: Discussionmentioning

confidence: 99%

An extensible big data software architecture managing a research resource of real-world clinical radiology data linked to other health data from the whole Scottish population

et al. 2020

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Aim To enable a world-leading research dataset of routinely collected clinical images linked to other routinely collected data from the whole Scottish national population. This includes more than 30 million different radiological examinations from a population of 5.4 million and >2 PB of data collected since 2010. Methods Scotland has a central archive of radiological data used to directly provide clinical care to patients. We have developed an architecture and platform to securely extract a copy of those data, link it to other clinical or social datasets, remove personal data to protect privacy, and make the resulting data available to researchers in a controlled Safe Haven environment. Results An extensive software platform has been developed to host, extract, and link data from cohorts to answer research questions. The platform has been tested on 5 different test cases and is currently being further enhanced to support 3 exemplar research projects. Conclusions The data available are from a range of radiological modalities and scanner types and were collected under different environmental conditions. These real-world, heterogenous data are valuable for training algorithms to support clinical decision making, especially for deep learning where large data volumes are required. The resource is now available for international research access. The platform and data can support new health research using artificial intelligence and machine learning technologies, as well as enabling discovery science.

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Section: Discussionmentioning

confidence: 99%

An extensible big data software architecture managing a research resource of real-world clinical radiology data linked to other health data from the whole Scottish population

et al. 2020

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“…Cloud computing is considered to be an immediate solution for medical data storage and sharing [6,18,19] because it is scalable, highly available, and flexible in pricing. Yet, due to the privacy and confidentiality requirements in healthcare data sharing, additional security means must be applied to mitigate the risks of cloud sourcing in healthcare and public health industry [7].…”

Section: Related Workmentioning

confidence: 99%

MedChain: Efficient Healthcare Data Sharing via Blockchain

2019

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Healthcare information exchange is an important research topic, which can benefit both healthcare providers and patients. In healthcare data sharing, many cloud-based solutions have been proposed, but the trustworthiness of a third-party cloud service is questionable. Recently, blockchain has been introduced in healthcare record sharing, which does not rely on trusting a third party. However, existing approaches only focus on the records collected from medical examination. They are not efficient in sharing data streams continuously generated from sensors and other monitoring devices. Today, IoT devices have been widely deployed and sensors and mobile applications can monitor patients’ body conditions. The collected data are shared to laboratories and institutions for diagnosis and further study. Moreover, existing approaches are too rigid to efficiently support metadata change. In this paper, an efficient data-sharing scheme is proposed, called MedChain, which combines blockchain, digest chain, and structured P2P network techniques to overcome the above efficiency issues in the existing approaches for sharing both types of healthcare data. Based on MedChain, a session-based healthcare data-sharing scheme is devised, which brings flexibility in data sharing. The evaluation results show that MedChain can achieve higher efficiency and satisfy the security requirements in data sharing.

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“…To increase the scalability and ensure the reliability of the software, developers need to respond to user's needs and consider continuous delivery to establish a culturally and environmentally adaptive software [36]. Therefore, the MicroService architecture [36][37][38], an emerging architectural design, was applied in the development of iCARE. MicroService is used for handling complex systems that require highly repetitive and frequent changes and allows continuous delivery of software in short circles; it was identified with increased deployability and modifiability among researchers.…”

Section: Design Architecture Of Icarementioning

confidence: 99%

An Intelligent Individualized Cardiovascular App for Risk Elimination (iCARE) for Individuals With Coronary Heart Disease: Development and Usability Testing Analysis

Chen¹,

Ji²,

Wu³

et al. 2021

JMIR Mhealth Uhealth

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Background Death and disability from coronary heart disease (CHD) can be largely reduced by improving risk factor management. However, adhering to evidence-based recommendations is challenging and requires interventions at the level of the patient, provider, and health system. Objective The aim of this study was to develop an Intelligent Individualized Cardiovascular App for Risk Elimination (iCARE) to facilitate adherence to health behaviors and preventive medications, and to test the usability of iCARE. Methods We developed iCARE based on a user-centered design approach, which included 4 phases: (1) function design, (2) iterative design, (3) expert inspections and walkthroughs of the prototypes, and (4) usability testing with end users. The usability testing of iCARE included 2 stages: stage I, which included a task analysis and a usability evaluation (January to March 2019) of the iCARE patient app using the modified Health Information Technology Usability Survey (Health-ITUES); and stage II (June 2020), which used the Health-ITUES among end users who used the app for 6 months. The end users were individuals with a confirmed diagnosis of CHD from 2 university-affiliated hospitals in Beijing, China. Results iCARE consists of a patient app, a care provider app, and a cloud platform. It has a set of algorithms that trigger tailored feedback and can send individualized interventions based on data from initial assessment and health monitoring via manual entry or wearable devices. For stage I usability testing, 88 hospitalized patients (72% [63/88] male; mean age 60 [SD 9.9] years) with CHD were included in the study. The mean score of the usability testing was 90.1 (interquartile range 83.3-99.0). Among enrolled participants, 90% (79/88) were satisfied with iCARE; 94% (83/88) and 82% (72/88) reported that iCARE was useful and easy to use, respectively. For stage II usability testing, 61 individuals with CHD (85% [52/61] male; mean age 53 [SD 8.2] years) who were from an intervention arm and used iCARE for at least six months were included. The mean total score on usability testing based on the questionnaire was 89.0 (interquartile distance: 77.0-99.5). Among enrolled participants, 89% (54/61) were satisfied with the use of iCARE, 93% (57/61) perceived it as useful, and 70% (43/61) as easy to use. Conclusions This study developed an intelligent, individualized, evidence-based, and theory-driven app (iCARE) to improve patients’ adherence to health behaviors and medication management. iCARE was identified to be highly acceptable, useful, and easy to use among individuals with a diagnosis of CHD. Trial Registration Chinese Clinical Trial Registry ChiCTR-INR-16010242; https://tinyurl.com/2p8bkrew

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MicroShare: Privacy-Preserved Medical Resource Sharing through MicroService Architecture

Cited by 26 publications

References 27 publications

An extensible big data software architecture managing a research resource of real-world clinical radiology data linked to other health data from the whole Scottish population

An extensible big data software architecture managing a research resource of real-world clinical radiology data linked to other health data from the whole Scottish population

MedChain: Efficient Healthcare Data Sharing via Blockchain

An Intelligent Individualized Cardiovascular App for Risk Elimination (iCARE) for Individuals With Coronary Heart Disease: Development and Usability Testing Analysis

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