Online Health Communities: A New Frontier in Health Research

Amrita Bhowmick & Casey Hribar

The Rise of a Plugged-In Health Biome

As we transcend into the Health 2.0 ecosystem, where the notion of patients using technologies to take control of their personal wellbeing has become more commonplace, our entire global healthcare system has begun to shift. A field once dominated by academia and big-name pharmaceutical industries, has now seen the rise of a third category of stakeholders, who have the potential to transform the healthcare industry on levels unseen previously. This rising group is made up of online health communities — patients, caregivers, friends, family members, and interested citizen-scientists — who have begun to rally around specific healthcare conditions and concerns, and who have bonded over their shared experiences, frustrations, elations, and questions.

The True Potential of a Seemingly Innocuous Realm

While the use of social media tools and online health communities as hubs for medical innovation might seem like a stretch, their importance cannot be overstated. Communication is now multidirectional; information is more accessible, and experience-sharing is both simple and fast. Participatory health is on the rise as a result, and patients are becoming more engaged in their healthcare via technologies accessible to them (1–3). In an industry that spends trillions of dollars a year, it can pay both figuratively, and literally, to follow the trend and harness its potential (1,2).

How Can Online Communities Impact Health Research?

Descriptive Cohort and Observational Studies

When trying to better describe patients’ experiences with a condition, what their life is like, what works — and doesn’t work — for them, the most valuable source is patients themselves. By posing questions to an online community, or simply monitoring organic conversations, one can observe naturally occurring trends in desires, symptoms, seemingly positive remedies, and other pieces of information that would not otherwise be revealed. These trends can then be analyzed to streamline or improve care. Information gathered this way is often relatively lower-cost, faster, and more inclusive of a wider variety of patients than traditional methods alone.

Several notable examples of this have been exhibited in research conducted by Health Union, including the “Migraine and Dogs” descriptive cohort study, “In America” studies, and relationship impact surveys that are conducted among members of online communities dedicated to specific chronic illnesses.

Pursuing a potential trend stemming from community engagement, members of Health Union’s Migraine.com were asked to weigh-in on the possibility that their household dog could be aware of and alert them to the onset of a migraine attack. Investigating the potential for a dog to accurately predict the earliest symptoms of an attack could increase medication effectiveness by alerting patients to treat early. (16).

Additionally, “In America” and relationship impact surveys conducted by Health Union gather information on patient experiences with a condition by asking questions that dive deeper than typical diagnostic or treatment experience, and focusing heavily on quality of life, lifestyle, or lesser-known symptoms. These surveys seek to ask questions patients want to answer, whether it allows them to share previously unheard frustrations, or to see how they stack up against other patients. Responses can then be published to alert providers and policymakers to personal and societal issues facing patients (8,9). Research like this can be generated at rapid speeds, and reach a wider network of patients than ever before.

Results from the 2016 Multiple Sclerosis in America Survey

Online Communities as a Diagnostic Tool

Communities can support the diagnostic process of a patient, aiding in the efficiency of the healthcare system as a whole. Some communities are designed for patients who are lacking a definitive diagnosis, leading to thousands of dollars being spent on ineffective treatments or tests. Community members can post medical records, attempted treatments, symptoms, and previous diagnoses for medical “detectives” to research (7).

A recent case study evaluated the benefits of such online communities, and determined that for the small sample of patients who were able to see the process through to completion and provide detailed medical records both pre- and post-community engagement, a significant decrease in physician visits, as well as medical expenditure, was observed (7). While it was a small survey, and there are limitations to this concept, online community research may aid physicians by encouraging patients to participate in the diagnostic process.

Drug Development, Design, and Indication Scaling

Online communities can provide feedback regarding product attributes most important to patients and caregivers. For example, discovering the ideal drug administration method for patients can lead to an effective drug design that will more likely succeed in clinical trials and on the market. This aids researchers in designing a desirable drug, but more importantly it provides patients with a treatment plan that is tailored to their needs — increasing the likelihood of adherence and ultimately effectiveness.

Additionally, online communities can be used to make drug indication curation a less-costly, and more time-efficient process. Using manual curators for biological databases is both expensive and time consuming. Researchers recently catalogued drug indications by crowdsourcing the task to an online community. Not only was this approach significantly less expensive, it was done in a fraction of the time, and with participation from a wide variety of individuals(10). This result shows that there is efficacy and efficiency in assigning some simpler tasks of health research to qualified online communities, allowing resources to be allocated to other pressing innovations.

Trial Design and Execution

Clinical Trials

Online communities are providing feedback on protocols, consent forms, endpoints, and trial designs for clinical studies on experimental treatments. Participation rates for clinical trials have been decreasing in recent years due to lack of enthusiasm, lack of feasibility, incredibly strict inclusion criteria, or lack of awareness. In fact, an estimated 40% of trials struggle to meet goals due to low recruitment (17). Although financial compensation and philanthropic fulfillment can be motivating factors for participation, the potential for receiving a placebo, inconvenient treatment regimens, or inflexible follow-up demands contribute to participant drop-out or refusal to join (1,3). Low recruitment numbers, high costs, and long trial times are stunting the speed of innovation.

Previously, trials were designed and evaluated for the sponsor’s convenience, and without much regard for patient or caregiver feasibility and lifestyle (1,5,6). However, as patients become more informed and involved in their care via technology, their relationship with researchers is evolving. This paradigm shift has resulted in the recognition of patients as critical stakeholders to be considered during trial design. The move from sponsor-only consideration, towards increasing stakeholder input is now seen as a critical step towards increasing trial success.

This concept has become so important; it has even caught the attention of major healthcare forces. The FDA and Duke University’s Clinical Trials Transformation Initiative (CTTI), is releasing recommendations advising researchers to consider all potential stakeholders involved in a potential trial, from physicians, to disease-specific advocacy groups, to patients themselves (17). Patient input via online sites has proven to be a major source for collaboration, and has since led to changes in treatment location and administration (11,12). By engaging more stakeholders via online communities, trials can be tailor-made for a larger pool of individuals, increasing participation rates and overall success.

Crowdsourcing techniques to gain patient and physician input on clinical trial design, as well as communities in which participants can work together to create their own clinical trial protocol for sponsors to consider, have resulted in several completely crowdsourced protocols for studies on conditions from multiple sclerosis to prostate cancer (1,3,5,6). While this approach can have its limitations, it does increase retention rates, enthusiasm, and informed patients, whose personal stake in a trial can foster a desire to participate.

Online communities can also be used to alert potential participants to trials in their area, as well as create reserves of individuals who may be inclined to participate in a trial in the future. This provides researchers with access to many more patients, including those who are interested in clinical trials, but who previously would not have heard about them, as well as the underinsured, rurally-located, and time-restricted. Thousands of potential participants can initially be screened from their home in a matter of minutes, reducing travel time, manual screening costs, and the overall timeline from screening to the start of a trial (12).

While stakeholder engagement, crowdsourced research design, and established reserves of potential participants can all increase participation rates in trials, barriers to clinical trial enrollment remain. In the public domain, there is still a general lack of knowledge about clinical trials, and well as a fear of the unknown. In a meta-analysis of data from their 2014 and 2015 “In America” studies, Health Union focused on identifying why although 69% of respondents reported being interested in participating in clinical trials, the actual participation rate is drastically lower. The data came from self-reported questionnaires completed by 21,627 patients with chronic conditions (18).

Results from Health Union’s meta-analysis predicting patient interest and participation in clinical trials (18)

Though the focus of the “In America” study series is much broader in nature, several questions addressed the topic of clinical trials. The majority of the 31% who reported no interest in trial participation cited fear of the unknown or untested treatments. This fear can be combatted, and can affect participation rates. In fact, the analysis also revealed that those who had previously participated in clinical trials were significantly more likely to be interested in future clinical trial participation (77%) than their counterparts who had never participated (66%) (n=16,623; p<0.0001) (18). This result suggests that those who had experience with and background knowledge on the process of a clinical trial, were more inclined to come back.

Education and transparency can be provided via online communities and other web-based programs such as PRE-ACT (Preparatory Education About Clinical Trials), developed in part by the National Cancer Institute, to provide patients with information and an understanding of the way trials work or what exactly they are (17, 19). Helping patients understand the process and diminishing their fear of the unknown, could potentially break this participation barrier, and lead to an overall increase in recruitment.

The Rise of Patient-Driven Research

While this is a less controlled form of study, and certainly can be more dangerous as patients are often experimenting on themselves with off-label medication use or by engaging in potentially risky behaviors, there is potential for patient-driven research to complement controlled, scientific studies. Many online communities allow participants to create or participate in independent research endeavors created by their peers (13,14). Scientific strictness, and goals of the studies can vary significantly, and are completely community generated, monitored, and reported.

Although there is the possibility for noisy or inaccurate data, there is significant potential for fast, large-scale, and low-cost data collection. An example of this type of engagement is a recent online community’s participant-led study of the effects of lithium on patients with amyotrophic lateral sclerosis (ALS). The study had no control arm, and required patients in the community to self-report their experience and ALS symptom progression while taking lithium (2,4).

The results found by the community indicated that there was no connection between lithium and symptom progression. A scientific study was then completed by researchers who analyzed the patient data, and compared the experimental group to a control arm utilizing existing electronic patient records. It was confirmed that the results of the patient-driven study held validity (2,4). These results also confirmed the results of a previously conducted clinical trial investigating the same hypothesis — that lithium did not affect ALS progression.

It is important to note that while these types of trials can have academic merit, they are not a suitable replacement for FDA-approved clinical trials (2,3). They do, however, show promise as a means of validating previous study results, or generating interest in a particular treatment method.

Limitations

Whether it be an observational study, or participant-driven research, most data are self-reported, with no requirement for diagnosis confirmation, clinician information, or medical records (2). Essentially, there is no “proof” that what a patient is reporting to others has any validity. While it seems unlikely that many would falsify data, it is a risk to consider in addition to basic misinterpretation of terminology. New technologies could be used to verify patient reporting data, however, this could create a higher cost for research, as well as limit the accessibility of participants.

Additionally, for patient-driven research, self-reporting subjective data (with no blinding or control arm) to a hopeful community can lead to the overstatement of results, or reporting of data that a patient perceives to be happening, that actually isn’t. This self-reporting bias may be completely unintentional, but may be manufactured by the extreme desire for success. Furthermore, the lack of strict protocol design can lead to results that are unverifiable, or that are overstated, as the design could lack control over confounding variables, or inadvertently harbor a specific result, not to mention put a patient in extreme danger. It is for these reasons that participant-driven research should be used in conjunction with clinical trials and controlled scientific exploration, as opposed to in place of. Without proper approval and overview, even the strongest results of patient-driven studies must be questioned and verified.

Although online communities can utilize technology to reach patients on a much larger scale, there is still potential for sample bias. Many of the individuals currently using online communities are technologically literate, and have access to the Internet or other often costly devices used to access it. While more people can be reached, often at faster speeds and lower cost, there is a chance that many of these individuals are more homogeneous than desired.

The rise of technology, online communities, and social media outlets have also created one more potential issue to the legitimacy of health research: revealing supposedly confidential trial details. Although patients may sign contracts indicating they will not share their trial experiences without permission, social media can make this hard to control. For example, patients in trials could potentially find each other via social media or online communities and compare experiences to try to “un-blind” experiments. This can lead to participants who believe they are in the placebo group to drop out before completion, thus, potentially jeopardizing the study (15). Social media can also be used for participants to swap advice on how to get into a clinical trial they may otherwise be excluded from, further jeopardizing its outcome.

As with any type of research, utilizing online communities for health investigation has potential risks. However, with stronger, more efficient quality control methods, as well as a potential increase in FDA regulation of social media and participant-driven research, these limitations could be minimized.

The Incredible Potential of Online Communities in Health Research

Ultimately, online communities can change the efficiency, feasibility, and speed of health research, while engaging a larger population than ever before. Trials have the possibility to be designed for maximum retention and filled with ease; observational studies can inform researchers about real patient experiences; patient-driven research can serve as a starting point for future trials, or as verification of previous results. The possibilities are quite vast within this realm, and if treated with appropriate caution, can have a tremendous impact on patient care, as well as the quality of health research and innovation.

References:

1. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4504054/

2. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3376509/

3. http://jnci.oxfordjournals.org/content/106/10/dju258.abstract

4. http://www.nature.com/nbt/journal/v29/n5/full/nbt.1837.html

5. https://connection.asco.org/blogs/three-ways-improve-clinical-trials-through-crowdsourcing

6. http://journals.lww.com/oncology-times/Fulltext/2014/03250/Crowdsourcing_Clinical_Trial_Protocols.1.aspx

7. http://www.jmir.org/2016/6/e127/

8. http://onlinelibrary.wiley.com/doi/10.1002/msc.1039/abstract

9. https://www.dovepress.com/migraine-treatments-comorbidities-and-quality-of-life-in-the-usa-peer-reviewed-article-JPR

10. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4369375/

11. http://mobihealthnews.com/36739/how-genentech-taps-into-online-patient-communities-to-improve-clinical-trials

12. https://migraine.com/clinical/you-can-make-a-difference-with-migraine-com-triallink/

13. http://www.rwjf.org/en/library/articles-and-news/2014/03/patientslikeme-invite-patients-lead-open-research-exchange.html

14. http://www.medscape.com/viewarticle/713872

15. http://www.wsj.com/articles/researchers-fret-as-social-media-lift-veil-on-drug-trials-1406687404

16. http://online.liebertpub.com/doi/abs/10.1089/acm.2012.0234

17. http://www.wsj.com/articles/clinical-trials-need-more-subjects-1460407076

18. What really matters? Predicting patient interest in clinical trials. Health Union White Paper. Available upon request.

19. http://www.cancer.net/navigating-cancer-care/how-cancer-treated/clinical-trials/pre-act