Sharing Health Data for Better Outcomes on PatientsLikeMe
By Paul Wicks, Michael Massagli, Jeana Frost, Catherine Brownstein, S. Okun, Timothy E Vaughan, Richard Bradley, James Heywood. Journal of Medical Internet Research, 2010
633 citations recorded by the source corpus.
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.
Subfields: General Health Professions, Neurology, Speech and Hearing
View Paper: https://www.semanticscholar.org/paper/489177028f8d4c3cd2e0a7f6560b89b1eec3caf2
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Citations in the corpus
- Features of Mobile Diabetes Applications: Review of the Literature and Analysis of Current Applications Compared Against Evidence-Based Guidelines (2011, background): “Chen’s findings underscore the importance of individuality and the need for tailored social interactions, which resonate with the concept of “PatientsLikeMe” [33,34], which has recently received enormous attention.”
- Social Networks, Interpersonal Social Support, and Health Outcomes: A Health Communication Perspective (2016, background): “Due to these issues, many individuals feel that they receive inadequate informational support from their traditional social networks and health-care providers; and they may perceive online support groups/communities as a better alternative for receiving health information (Wicks et al., 2010).”
- EventAction (2019, background): “For example, in bioinformatics for gene sequence alignment [35] or protein clustering [38], in linguistics for approximate string matching [52] or text categorization [11], in computer vision for face recognition [62], and in healthcare for identifying similar patients [73, 81].”
- Accelerated clinical discovery using self-reported patient data collected online and a patient-matching algorithm (2011, methodology): “Results Participants As of the date that our data set was finalized (28 February 2010), there were 4,318 ALS patients on PatientsLikeMe, all of whom were invited to report their FRS scores, symptoms, treatments (with start and stop dates), site of ALS onset and demographic data using online”
- A New Dimension of Health Care: Systematic Review of the Uses, Benefits, and Limitations of Social Media for Health Communication (2013, background): “Social media provided health information on a range of conditions to the general public [36,61,71,74,103], patients [47,63,71,75,98,103], and health professionals [36,47,98].”
- It's not that i don't have problems, i'm just not putting them on facebook: challenges and opportunities in using online social networks for health (2011, background): “A substantial body of prior research has looked at specific online health communities and characterized what makes them effective and valuable for their members (e.g., [18, 23 ]).”
- Social media use in healthcare: A systematic review of effects on patients and on their relationship with healthcare professionals (2016, background): “Other types of effects Diminished subjective well-being [13, 16, 25, 26, 35, 36]”
- The influence of social networking sites on health behavior change: a systematic review and meta-analysis (2015, background): “At the individual level, they are able to facilitate access to health-related information and social support,(7,17) promoting better-informed treatment decisions.(18,19) Given that lifestyle behaviors are”