On the adoption of personal health records: some problematic issues for patient empowerment

Vezyridis, Paraskevas; Timmons, Stephen

doi:10.1007/s10676-015-9365-x

Cited by 17 publications

(18 citation statements)

References 69 publications

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“…Our critical review and analysis of a representative sample of 58 BDBM studies indicates that the primary focus of the literature is on data users (42 studies), with a particular focus on the question of how BD can be used to create value within an organization (Schroeder, 2016). In contrast, there is only a limited focus on data suppliers (three studies; Rambe and Moeti, 2017; Spiekermann and Novotny, 2015; Vezyridis and Timmons, 2015). These three studies broadly represent data suppliers ranging from Massive Open Online Course (MOOC) providers to personal health information (PHI) vendors.…”

Section: Review Resultsmentioning

confidence: 99%

“…learning analytics) for profit—is at odds with claims about philanthropic and egalitarian considerations driving MOOC offerings. On a related note, Vezyridis and Timmons (2015: 113) question whether the development of PHI records by independent vendors really empowers patients, arguing that the “proclaimed ‘consumer empowerment in healthcare’ is an attempt to introduce [. .…”

Section: Review Resultsmentioning

confidence: 99%

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Big-data business models: A critical literature review and multiperspective research framework

Wiener

Saunders

Marabelli

2020

Journal of Information Technology

104

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The emergence of “big data” offers organizations unprecedented opportunities to gain and maintain competitive advantage. Trying to exploit the strategic business potential embedded in big data, many organizations have started to renovate their business models or develop new ones, giving rise to the phenomenon of big-data business models. Although big-data business model research is still in its infancy, a significant number of studies on the topic have been published since 2014. We thus suggest it is time to perform a critical review and assessment of the literature at the intersection of business models and big data (analytics), thereby responding to recent calls for further research on and sustained analysis of big-data business models. In particular, our review uses three major criteria (big-data business model types, dimensions, and deployment) to assess the state of the big-data business model literature and identify shortcomings in this literature. On this basis, we derive and discuss five central research perspectives (supply chain, stakeholder, ethics, national, and process), providing guidance for future research and theory development in the area. These perspectives also have practical implications on how to address the current big-data business model deployment gap.

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Section: Review Resultsmentioning

confidence: 99%

Section: Review Resultsmentioning

confidence: 99%

Big-data business models: A critical literature review and multiperspective research framework

Wiener

Saunders

Marabelli

2020

Journal of Information Technology

104

View full text Add to dashboard Cite

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“…Empowering patients to "take charge" of their health is an idea frequently championed by politicians [22,16], technologists [27], journalists [19] and healthcare experts alike [37]. Yet, despite both government and industry-led initiatives across both Europe and North America to encourage this "patient-led healthcare revolution," widespread adoption has been slow [41].…”

Section: Introductionmentioning

confidence: 99%

The Quantified Patient in the Doctor's Office

West

Giordano

Kleek

et al. 2016

Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems

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While the Quantified Self and personal informatics fields have focused on the individual's use of self-logged data about themselves, the same kinds of data could, in theory, be used to improve diagnosis and care planning. In this paper, we seek to understand both the opportunities and bottlenecks in the use of self-logged data for differential diagnosis and care planning during patient visits to both primary and secondary care. We first conducted a literature review to identify potential factors influencing the use of self-logged data in clinical settings. This informed the design of our experiment, in which we applied a vignette-based role-play approach with general practitioners and hospital specialists in the US and UK, to elicit reflections on and insights about using patient self-logged data. Our analysis reveals multiple opportunities for the use of self-logged data in the differential diagnosis workflow, identifying capture, representational, and interpretational challenges that are potentially preventing self-logged data from being effectively interpreted and applied by clinicians to derive a patient's prognosis and plan of care.

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“…For example, if given an antibiotic prescription for tonsillitis, an individual has forward-looking moral responsibility for completing the course to ensure the infection clears, and backward-looking responsibility if the infection recurs because they did not take all the doses. Empowering mHealth tools are seen as affording individuals' greater visibility of the processes of the self, which combines with existing free will (Flaskerud 2014) to produce an increase in responsibility (Vezyridis and Timmons 2015;Baistow 1994).…”

Section: The Empowerment Marketing Campaignmentioning

confidence: 99%

The Limits of Empowerment: How to Reframe the Role of mHealth Tools in the Healthcare Ecosystem

Morley

Floridi

2019

Sci Eng Ethics

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This article highlights the limitations of the tendency to frame health-and wellbeing-related digital tools (mHealth technologies) as empowering devices, especially as they play an increasingly important role in the National Health Service (NHS) in the UK. It argues that mHealth technologies should instead be framed as digital companions. This shift from empowerment to companionship is advocated by showing the conceptual, ethical, and methodological issues challenging the narrative of empowerment, and by arguing that such challenges, as well as the risk of medical paternalism, can be overcome by focusing on the potential for mHealth tools to mediate the relationship between recipients of clinical advice and givers of clinical advice, in ways that allow for contextual flexibility in the balance between patiency and agency. The article concludes by stressing that reframing the narrative cannot be the only means for avoiding harm caused to the NHS as a healthcare system by the introduction of mHealth tools. Future discussion will be needed on the overarching role of responsible design.

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On the adoption of personal health records: some problematic issues for patient empowerment

Cited by 17 publications

References 69 publications

Big-data business models: A critical literature review and multiperspective research framework

Big-data business models: A critical literature review and multiperspective research framework

The Quantified Patient in the Doctor's Office

The Limits of Empowerment: How to Reframe the Role of mHealth Tools in the Healthcare Ecosystem

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