Patterns of Treatment Switching in Multiple Sclerosis Therapies in US Patients Active on Social Media: Application of Social Media Content Analysis to Health Outcomes Research

Abstract

BackgroundSocial media analysis has rarely been applied to the study of specific questions in outcomes research.ObjectiveThe aim was to test the applicability of social media analysis to outcomes research using automated listening combined with filtering and analysis of data by specialists. After validation, the process was applied to the study of patterns of treatment switching in multiple sclerosis (MS).MethodsA comprehensive listening and analysis process was developed that blended automated listening with filtering and analysis of data by life sciences-qualified analysts and physicians. The population was patients with MS from the United States. Data sources were Facebook, Twitter, blogs, and online forums. Sources were searched for mention of specific oral, injectable, and intravenous (IV) infusion treatments. The representativeness of the social media population was validated by comparison with community survey data and with data from three large US administrative claims databases: MarketScan, PharMetrics Plus, and Department of Defense.ResultsA total of 10,260 data points were sampled for manual review: 3025 from Twitter, 3771 from Facebook, 2773 from Internet forums, and 691 from blogs. The demographics of the social media population were similar to those reported from community surveys and claims databases. Mean age was 39 (SD 11) years and 14.56% (326/2239) of the population was older than 50 years. Women, patients aged 30 to 49 years, and those diagnosed for more than 10 years were represented by more data points than other patients were. Women also accounted for a large majority (82.6%, 819/991) of reported switches. Two-fifths of switching patients had lived with their disease for more than 10 years since diagnosis. Most reported switches (55.05%, 927/1684) were from injectable to oral drugs with switches from IV therapies to orals the second largest switch (15.38%, 259/1684). Switches to oral drugs accounted for more than 80% (927/1114) of the switches away from injectable therapies. Four reasons accounted for more than 90% of all switches: severe side effects, lack of efficacy, physicians’ advice, and greater ease of use. Side effects were the main reason for switches to oral or to injectable therapies and search for greater efficacy was the most important factor in switches to IV therapies. Cost of medication was the reason for switching in less than 0.5% of patients.ConclusionsSocial intelligence can be applied to outcomes research with power to analyze MS patients’ personal experiences of treatments and to chart the most common reasons for switching between therapies.

Hastane-Hasta İlişkisi Bağlamında Hasta Sadakati: Sosyal Medyanın Aracı Rolü

“…Finally, while people were getting medicine and treatment suggestions from family members or friends for their illnesses in the past, today, it seems that online resources and social media are the routes people use when searching for medicine and treatment (De Martino et al, 2017;Risson et al, 2016). Moreover, since individuals direct their attention to new communication channels instead of e-mail or telephone, sector representatives should use social media more actively by informing patients about encountered health-related problems and sharing useful health-related strategies through social media.…”

“…Moreover, compared to previous years, there are more conscious patient profiles about services and illnesses through changes in technology, including online platforms, which enable interactions about various health topics related to informing patients (Househ et al, 2014). In parallel, the Internet has been the first source of information used by many patients (Hesse et al, 2010;Risson et al, 2016). Thus, patients can evaluate and compare the given health service, or they can get more information about the illness through different online resources, such as social media, before even taking the offered service.…”

The positive impacts of Real-World Data on the challenges facing the evolution of biopharma

“…The immediacy of these data, along with their widespread availability, could provide insights into adverse effects and noncompliance. Indeed, social listening can be used to track the most-common reasons for patients switching between therapies [65]. It has the potential to provide a large amount of information about 'real-world benefit' as discussed from the patient's perspective [66].…”

Developing an integrated strategy for evidence generation

“…One innovative method that can help ensure this information is captured is social media listening. With the correct structure and context, social media listening can provide insights into patient characteristics, treatment satisfaction, treatment switching, reasons for switching and much more [9]. Studies capturing this patient-reported data can be extended by linking data from claims and electronic medical record data systems to obtain a more complete picture [10].…”