{"id":30479,"date":"2018-11-13T12:31:03","date_gmt":"2018-11-13T17:31:03","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/social-networks-in-healthcare-can-crowdsourcing-patient-data-improve-outcomes\/"},"modified":"2018-11-13T12:31:52","modified_gmt":"2018-11-13T17:31:52","slug":"healthcare-social-networks-can-crowdsourcing-patient-reported-data-improve-outcomes","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/healthcare-social-networks-can-crowdsourcing-patient-reported-data-improve-outcomes\/","title":{"rendered":"Healthcare Social Networks: Can Crowdsourcing Patient-Reported Data Improve Outcomes?"},"content":{"rendered":"

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In the United States, fifteen new cases of ALS are discovered every day, an estimated 1 million people suffer from multiple sclerosis, and an estimated additional 1 million people suffer from Parkinson\u2019s disease. [1] These are the three main disease categories that PatientsLikeMe sought to address when they created an online platform for patients to share personal health information. Founded in 2004, PatientsLikeMe created a platform to crowdsource self-reported patient medical data to in an effort to 1) educate patients within disease-specific communities and empower them in their health journey and 2) advance the pace of medical research. <\/span><\/p>\n

The Platform <\/b><\/p>\n

PatientsLikeMe (PLM) has built an online social network for patients to exchange information within their disease-specific communities. Patients upload demographic information to their personal profile and share information on their disease, treatment plan, and symptoms. They can post and comment on articles, discuss new clinical trials, and direct message other patients for more in-depth conversations. Since 2004, the PLM network has grown to over 650,000 patients covering 2,800 different conditions. [2]<\/span><\/p>\n

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Figure 1: Visualization tools offered on PLM platform for patients with fibromyalgia. Patients can research information about the disease as well as compare treatment plans and reported side effects.<\/span><\/p>\n

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Educating and Empowering Patients – <\/b>\u201cLearn From Patients Like You\u201d<\/i><\/b><\/p>\n

<\/b>The PLM platform offers an opportunity for patients to learn, connect, and own their health. <\/span>Patients can review information to understand their best path given their condition and \u201cDoctor Visit Templates\u201d are available to empower patients to have more effective conversations with their doctor. [3] A 2010 study of PLM showed that 57% of patients found the site helpful for understanding treatment side effects and that 12% changed their physician as a result using the site. [4] In addition to providing information, PLM also provides an outlet for social and emotional relief. Patients can connect with a community of peers suffering from the same disease. In the same 2010 study, 41% of HIV patients and 22% of mood disorder patients reported community-specific benefits. [4] <\/span><\/p>\n

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Figure 2. Patient biography on PLM platform.<\/span><\/p>\n

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Collecting Data to Advance Medical Research – <\/b>\u201cWe\u2019re more than a disease. Together, we\u2019re the answer\u201d <\/i><\/b><\/p>\n

In creating a space for information-sharing, PLM has been able to collect large amounts of data and share them with 80 plus partners spanning biotech, pharmaceutical, and research. [2] They have partnered with the Journal of Medical Internet Research on numerous occasions. In one instance, it was to study the impact of two drugs (amitriptyline and modafinil) on patients within 5 disease categories (multiple sclerosis, Parkinson’s disease, mood conditions, fibromyalgia\/chronic fatigue syndrome, and amyotrophic lateral sclerosis). [5] More recently, PLM data was used to observe the patient perspective on neuromyelitis optica spectrum disorders. [6]<\/span><\/p>\n

A core competency in this process is PLM\u2019s ability to de-identify patient information and convert it into structured, medically-accepted data. In 2018, an evaluative study showed that 97.09% of PLM-assigned codes, generated from their patient reported database, were compatible with FDA coding requirements. [7] This suggests that PLM reported data is reliably being converted into medically-accepted data. Managing this process and increasing coding reliability will continue to be essential to PLM\u2019s model.<\/span><\/p>\n

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Open Questions<\/b><\/p>\n

Crowdsourcing patient-data to improve the patient experience and accelerate medical research continues to generate enthusiasm within the healthcare community. Just last week, FDA Commissioner Dr. Scott Gottlieb announced that the FDA is launching a new app to gather patient-reported data for clinical trials. [8] PLM has built a strong platform to benefit from this trend, but there are some important questions that still need to be addressed:<\/span><\/p>\n

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  1. Can PLM overcome patient and population bias and leverage data to make meaningful medical advances?<\/span>\n