Sharing Health Data for Better Outcomes on PatientsLikeMe
Open accessAbstract
BACKGROUND: PatientsLikeMe is an online quantitative personal research platform for patients with life-changing illnesses to share their experience using patient-reported outcomes, find other patients like them matched on demographic and clinical characteristics, and learn from the aggregated data reports of others to improve their outcomes. The goal of the website is to help patients answer the question: "Given my status, what is the best outcome I can hope to achieve, and how do I get there?" OBJECTIVE: Using a cross-sectional online survey, we sought to describe the potential benefits of PatientsLikeMe in terms of treatment decisions, symptom management, clinical management, and outcomes. METHODS: Almost 7,000 members from six PatientsLikeMe communities (amyotrophic lateral sclerosis [ALS], Multiple Sclerosis [MS], Parkinson's Disease, human immunodeficiency virus [HIV], fibromyalgia, and mood disorders) were sent a survey invitation using an internal survey tool (PatientsLikeMe Lens). RESULTS: Complete responses were received from 1323 participants (19% of invited members). Between-group demographics varied according to disease community. Users perceived the greatest benefit in learning about a symptom they had experienced; 72% (952 of 1323) rated the site "moderately" or "very helpful." Patients also found the site helpful for understanding the side effects of their treatments (n = 757, 57%). Nearly half of patients (n = 559, 42%) agreed that the site had helped them find another patient who had helped them understand what it was like to take a specific treatment for their condition. More patients found the site helpful with decisions to start a medication (n = 496, 37%) than to change a medication (n = 359, 27%), change a dosage (n = 336, 25%), or stop a medication (n = 290, 22%). Almost all participants (n = 1,249, 94%) were diagnosed when they joined the site. Most (n = 824, 62%) experienced no change in their confidence in that diagnosis or had an increased level of confidence (n = 456, 34%). Use of the site was associated with increasing levels of comfort in sharing personal health information among those who had initially been uncomfortable. Overall, 12% of patients (n = 151 of 1320) changed their physician as a result of using the site; this figure was doubled in patients with fibromyalgia (21%, n = 33 of 150). Patients reported community-specific benefits: 41% of HIV patients (n = 72 of 177) agreed they had reduced risky behaviors and 22% of mood disorders patients (n = 31 of 141) agreed they needed less inpatient care as a result of using the site. Analysis of the Web access logs showed that participants who used more features of the site (eg, posted in the online forum) perceived greater benefit. CONCLUSIONS: We have established that members of the community reported a range of benefits, and that these may be related to the extent of site use. Third party validation and longitudinal evaluation is an important next step in continuing to evaluate the potential of online data-sharing platforms.
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Some online communities are built around data-sharing platforms where patients share quantitative medical information to learn from aggregated reports and improve their own outcomes.
“Other social networking online communities are built around data-sharing platforms, where patients share quantitative information about their medical conditions to learn from the aggregated data reports to improve their own outcomes.10”
From Social Media and Clinical Care: Ethical, Professional, and Social Implications (2013) · cites this paper as [10]
Members of data-sharing communities have reported benefits including better informed treatment decisions, symptom management, higher quality of life, and perceived control over their condition; a minority use their data in visits with providers, though the ways and utility are unclear.
“Members have reported benefits from participation including better informed treatment decisions, symptom management, higher quality of life, and perceived control over their condition; a minority use their data in their visits with their healthcare providers, although it is unclear in what ways and to what utility.10”
From Social Media and Clinical Care: Ethical, Professional, and Social Implications (2013) · cites this paper as [10]
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- Authors
- Wicks, P., Massagli, M., Frost, J., Brownstein, C., Okun, S., Vaughan, T., Bradley, R., & Heywood, J.
- Affiliations
- PatientsLikeMe (United States) (US)
- Corresponding author
- Wicks, Paul
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2010-06-14
- Volume
- 12
- Issue
- 2
- Pages
- e19
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC2956230
- OpenAlex
- W2105752956
- Cited by
- 603
- References
- 36
- Citations by year
- 2026: 7 · 2025: 16 · 2024: 17 · 2023: 32 · 2022: 31 · 2021: 37 · 2020: 47 · 2019: 37 · 2018: 50 · 2017: 47 · 2016: 54 · 2015: 50 · 2014: 48 · 2013: 53 · 2012: 44
- FWCI
- 73.27
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- other-oa
- Locations
- Journal of Medical Internet Research (publishedVersion, other-oa)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Health Professions › General Health Professions › Health Literacy and Information Accessibility
- Health Sciences › Health Professions › General Health Professions › Mental Health and Patient Involvement
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Keywords
- PatientsLikeMe, patient-reported outcomes, patient-generated health data, online patient communities, shared decision-making, treatment decision-making, symptom management, amyotrophic lateral sclerosis, multiple sclerosis, Parkinson's disease, HIV, fibromyalgia, mood disorders
- MeSH terms
- Adult, Community Participation, Cross-Sectional Studies, Data Display, Decision Support Techniques, Female, Humans, Male, Middle Aged, Online Systems, Physician-Patient Relations, Population Surveillance, Self Care, Self-Help Groups, Social Support, Disease Management, Internet, Information Dissemination, Rare Diseases, Health Records, Personal
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