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Emerging Patient-Driven Health Care Models: An Examination of Health Social Networks, Consumer Personalized Medicine and Quantified Self-Tracking
Open accessAbstract
A new class of patient-driven health care services is emerging to supplement and extend traditional health care delivery models and empower patient self-care. Patient-driven health care can be characterized as having an increased level of information flow, transparency, customization, collaboration and patient choice and responsibility-taking, as well as quantitative, predictive and preventive aspects. The potential exists to both improve traditional health care systems and expand the concept of health care though new services. This paper examines three categories of novel health services: health social networks, consumer personalized medicine and quantified self-tracking.
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“The “quantified self” movement is the driving force behind wearable technologies involving acquisition of data on daily activities, sport performance, and health status.1”
From Wearables in Medicine (2018) · cites this paper as [1]
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Metadata
- Authors
- Swan, M.
- Affiliations
- Futures Group (United States) (US)
- Corresponding author
- Swan, Melanie
- ORCID
- Swan, Melanie
- Venue
- International Journal of Environmental Research and Public Health
- Publisher
- MDPI AG
- Published
- 2009-02-05
- Volume
- 6
- Issue
- 2
- Pages
- 492-525
- ISSN
- 1660-4601 (ISSN-L)
- PMC
- PMC2672358
- OpenAlex
- W2054712596
- Cited by
- 730
- References
- 14
- Citations by year
- 2026: 7 · 2025: 11 · 2024: 17 · 2023: 30 · 2022: 37 · 2021: 53 · 2020: 53 · 2019: 62 · 2018: 67 · 2017: 66 · 2016: 70 · 2015: 73 · 2014: 64 · 2013: 46 · 2012: 35
- FWCI
- 44.78
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- International Journal of Environmental Research and Public Health (publishedVersion, cc-by)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Health Professions › Health Information Management › Innovation in Digital Healthcare Systems
- Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
- Keywords
- health social networks, patient self-care, health data transparency, models of care, patient empowerment
- MeSH terms
- Delivery of Health Care, Patient Participation, Patients, Social Support, Models, Organizational
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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