PatientsLikeMe Researchers Score a Hat Trick

The term “hat trick” originated in 1858 after English cricketer HH Stephenson successfully bowled out three batsmen with consecutive bowls and he was presented with a hat to commemorate his feat. In June, PatientsLikeMe’s research team scored a hat trick of our own by publishing three new studies in scientific journals in just four days, bringing our total number of published studies to 27.

An Image from the Third Published Study in Our June Hat Trick:  "Mining Social Network Data for Biomedical Research"

As employees at a start-up company, we all wear many hats – literally, as you can see from the photos below, and figuratively, in terms of our responsibilities as scientists, product developers and business people across different disease areas. For instance, in this trio of papers, we address research issues in multiple sclerosis (MS), ALS and mood disorders. Click on the study titles below to read the full papers and a big thank you to all of our patients for sharing your voices and making this research possible.

Monday, June 18th – First PatientsLikeMe study published.

The multiple sclerosis rating scale, revised (MSRS-R): Development, refinement, and psychometric validation using an online community

Members of our MS community will be familiar with the MS Rating Scale (MSRS), which is their primary outcome measure. We developed it a few years ago to address an unmet need for a brief, easy-to-use rating tool that covered more areas than simply walking. In collaboration with a neurologist, we sketched out our first version of the MSRS, which has now been used over 90,000 times by our 28,000+ MS members to share your progress, track your relapses and disability, and gain insight into how your treatments are working.

PatientsLikeMe Research Scientist Dr. Tim Vaughan

Published in the Journal of Medical Internet Research, this new study describes work to improve the MSRS to a revised version (the MSRS-R) and establish that the instrument measures what it is supposed to measure (reliability), that it correlates well with other instruments (concurrent validity) and that it allows differences between groups of patients (sensitivity to change). This process of “validating” a patient-reported outcome (PRO) is an important step in increasing the value of the data that we produce for researchers. Studies are underway right now to continue improving the instrument and compare it to doctors’ ratings of patient disability.

As with all outcome measures we develop at PatientsLikeMe, we have licensed the MSRS-R for anyone to use freely in their own research studies. This work also serves as a foundation for our resident predictive modeler and particle physicist Dr. Tim Vaughan to begin work on predicting the course of an individual patient’s disease using your MSRS scores!

Tuesday, June 19th – Second PatientsLikeMe study published.

E-mental health: A medium reaches maturity

PatientsLikeMe Research & Development Director Dr. Paul Wicks

The Internet has transformed many aspects of healthcare in the past decade, and to open a special issue on “E-Mental Health” in the Journal of Mental Health, our R&D Director Dr. Paul Wicks was commissioned to write a special editorial.

Available by clicking the link above, the paper describes the progress of online systems for people with mental health issues, from government-provided resources (such as this UK NHS Choices site about self-harm) to commercial, computerized cognitive-behavioral therapy programs like “Beating the Blues” and collaborations between different sectors of the health system. For instance, in the UK if you Google “suicide” there is a special message from the Samaritans mental health support service right at the top of the page.

At PatientsLikeMe, our vibrant mood community has been active since 2008, and our published research has shown that it provides improved outcomes to many of our members.

Thursday, June 21st – Third PatientsLikeMe study published.  Hat trick completed.

Mining Online Social Network Data for Biomedical Research: A Comparison of Clinicians’ and Patients’ Perceptions About Amyotrophic Lateral Sclerosis Treatments

As you probably know, the story of PatientsLikeMe starts with ALS and trying to find treatments that can improve the symptoms, including anxiety, stiffness, or constipation. Back in 2003, ALS nurse Dallas Forshew and Dr. Mark Bromberg published a small study describing massive variation in the way ALS doctors from 39 specialist centers treat the symptoms of ALS. This data was also described in our 2010 TEDx Berkshires talk about the value of crowd-sourced data.

PatientsLikeMe Research Assistant/Software Engineer Shivani Bhargava

In this new study published in the Journal of Medical Internet Research, we collaborated with researchers at the University of Utah to compare the passively collected ALS patient data from our system with what the clinicians said. Although they agreed in most areas, there were split opinions too, particularly when it came to the perceived level of efficacy that these treatments had. Click the link above to read more.

This paper is also notable for being our own Shivani Bhargava’s very first scientific publication! Shivani started with us as an intern, then became a research assistant, and has recently made a career change to start studying as a software engineer. A true renaissance woman!

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2 thoughts on “PatientsLikeMe Researchers Score a Hat Trick”

  1. I just received a newsletter from PatientsLikeme and was horified to learn that me data has been shared with the US government. How do I have my information removed from the government list?

    If had known this at the begining, I would never have joined your group. This is a travesty, and breach of confidence.

  2. Hi Raid,

    Our newsletter mentioned that the U.S. government is another institution—like PatientsLikeMe—that’s committed to using a data-driven approach to learning and eager to see what ‘big data’ can reveal. We don’t have a ‘government list’ and aren’t currently partnering with the government, but we do share aggregated de-identified data with our partners. We think this openness will help advance medicine in an unprecedented way.

    I hope you’ll read more in our Openness Philosophy and our Read This! FAQs. Please continue to express any concerns or thoughts—we’re here listening!

    http://www.patientslikeme.com/about/openness
    http://www.patientslikeme.com/help/faq/Read%20This!
    http://www.patientslikeme.com/about/partners

    Best wishes,
    Liz Morgan
    Community Manager at PatientsLikeMe

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