191,432 research outputs found
Dwarna : a blockchain solution for dynamic consent in biobanking
Dynamic consent aims to empower research partners and facilitate active participation in the research process. Used within
the context of biobanking, it gives individuals access to information and control to determine how and where their
biospecimens and data should be used. We present Dwarnaâa web portal for âdynamic consentâ that acts as a hub
connecting the different stakeholders of the Malta Biobank: biobank managers, researchers, research partners, and the
general public. The portal stores research partnersâ consent in a blockchain to create an immutable audit trail of research
partnersâ consent changes. Dwarnaâs structure also presents a solution to the European Unionâs General Data Protection
Regulationâs right to erasureâa right that is seemingly incompatible with the blockchain model. Dwarnaâs transparent
structure increases trustworthiness in the biobanking process by giving research partners more control over which research
studies they participate in, by facilitating the withdrawal of consent and by making it possible to request that the biospecimen
and associated data are destroyed.peer-reviewe
Evaluation of patient perception towards dynamic health data sharing using blockchain based digital consent with the Dovetail digital consent application : a cross sectional exploratory study
Background
New patient-centric integrated care models are enabled by the capability to exchange the patientâs data amongst stakeholders, who each specialise in different aspects of the patientâs care. This requires a robust, trusted and flexible mechanism for patients to offer consent to share their data. Furthermore, new IT technologies make it easier to give patients more control over their data, including the right to revoke consent. These characteristics challenge the traditional paper-based, single-organisation-led consent process. The Dovetail digital consent application uses a mobile application and blockchain based infrastructure to offer this capability, as part of a pilot allowing patients to have their data shared amongst digital tools, empowering patients to manage their condition within an integrated care setting.
Objective
To evaluate patient perceptions towards existing consent processes, and the Dovetail blockchain based digital consent application as a means to manage data sharing in the context of diabetes care.
Method
Patients with diabetes at a General Practitioner practice were recruited. Data were collected using focus groups and questionnaires. Thematic analysis of the focus group transcripts and descriptive statistics of the questionnaires was performed.
Results
There was a lack of understanding of existing consent processes in place, and many patients did not have any recollection of having previously given consent. The digital consent application received favourable feedback, with patients recognising the value of the capability offered by the application. Patients overwhelmingly favoured the digital consent application over existing practice.
Conclusions
Digital consent was received favourably, with patients recognising that it addresses the main limitations of the current process. Feedback on potential improvements was received. Future work includes confirmation of results in a broader demographic sample and across multiple conditions
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The chaotic nature of healthcare information systems: The need for transdisciplinary collaboration
Copyright @ 2013 EMCIS.This paper demonstrates one of the challenges of the healthcare information systems development, namely the chaotic nature of healthcare systems. Although the reliable evidence demonstrating the positive effects of health information systems on safety and quality remains inconclusive (a growing body of research revealing the unintended consequences and potentially error producing effects of health information systemsâ implementation. Different arguments from the literature concerning the chaotic nature of healthcare, including but not limited to the nature of patients and disease have been presented. The requirements of new ways of systems design and the need for transdisciplinary dynamic teams within the requirements engineering phase as a start has been discussed. These arguments have been investigated in the context of an exploratory case addressing one of the advanced oncology centres in the US. This paper concludes that there is an important need to rethink healthcare information systems development method, which has to be in a dynamic ongoing manner for some major issues
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A survey of simulation techniques in commerce and defence
Despite the developments in Modelling and Simulation (M&S) tools and techniques over the past years, there has been a gap in the M&S research and practice in healthcare on developing a toolkit to assist the modellers and simulation practitioners with selecting an appropriate set of techniques. This study is a preliminary step towards this goal. This paper presents some results from a systematic literature survey on applications of M&S in the commerce and defence domains that could inspire some improvements in the healthcare. Interim results show that in the commercial sector Discrete-Event Simulation (DES) has been the most widely used technique with System Dynamics (SD) in second place. However in the defence sector, SD has gained relatively more attention. SD has been found quite useful for qualitative and soft factors analysis. From both the surveys it becomes clear that there is a growing trend towards using hybrid M&S approaches
Identifying healthcare actors involved in the adoption of information systems
The adoption of information systems in healthcare is no less significant than in
any other commercial or caring organisation. The literature on IS adoption in
healthcare, makes it clear that the actors involved in the adoption process are
almost universally seen as crucial, which matches our research results too.
However, how such actors should be identified remains a topic for investigatory
work since these are early days in achieving this. We derive and propose a
structured method to model how actors might be identified: structured
because such a rationale is explicable and such a method is more readily usable
when transferred to others. Our structured method, named IGOHcaps, uses a
static and then a dynamic step to pull out the individual, group, organisational
and human determinants of the critical actors. In this process, the individual
actorsâ differing views emerge which could enable decision-making bodies to
produce more robust proposals if they incorporated some of the appropriate
views. We discuss the application of IGOHcaps through a hospital case study.
While a single case study cannot be a proof, the engagement of the actors was
encouraging
Authorization and access control of application data in Workflow systems
Workflow Management Systems (WfMSs) are used to support the modeling and coordinated execution of business processes within an organization or across organizational boundaries. Although some research efforts have addressed requirements for authorization and access control for workflow systems, little attention has been paid to the requirements as they apply to application data accessed or managed by WfMSs. In this paper, we discuss key access control requirements for application data in workflow applications using examples from the healthcare domain, introduce a classification of application data used in workflow systems by analyzing their sources, and then propose a comprehensive data authorization and access control mechanism for WfMSs. This involves four aspects: role, task, process instance-based user group, and data content. For implementation, a predicate-based access control method is used. We believe that the proposed model is applicable to workflow applications and WfMSs with diverse access control requirements
An authorization policy management framework for dynamic medical data sharing
In this paper, we propose a novel feature reduction approach to group words hierarchically into clusters which can then be used as new features for document classification. Initially, each word constitutes a cluster. We calculate the mutual confidence between any two different words. The pair of clusters containing the two words with the highest mutual confidence are combined into a new cluster. This process of merging is iterated until all the mutual confidences between the un-processed pair of words are smaller than a predefined threshold or only one cluster exists. In this way, a hierarchy of word clusters is obtained. The user can decide the clusters, from a certain level, to be used as new features for document classification. Experimental results have shown that our method can perform better than other methods.<br /
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