[#HITsm Chat, 9.4.15] Beyond Patient-Generated Health Data – What Non-Clinical Data Matters in Health?

Moderated by Mandi Bishop, Health Plan Analytics Innovation Practice Lead,  Dell

Topic: Beyond Patient-Generated Health Data – What Non-Clinical Data Matters in Health?

Chats are held at 11 a.m, CST, every Friday.

Read the full chat transcript, via Symplur.

A few weeks ago, I wrote a LinkedIn blog post about a couple of my Big Ideas for Healthcare Transformation. One of those ideas included leveraging non-clinical data sources such as social media posts, GPS location information, and retail purchases to inform individuals about how their behaviors might be impacting their health. The visceral reactions to this kind of tracking were surprising to me; the responses were polarized, and many vehemently disagreed with the plan to acquire and blend this type of personal data to derive health insights. It was almost universally considered “Big Brother”-ish.

But in positing that idea, I was also asking a research question: is traditional health data necessary to effectively assess health risk, or does the contextual data of the life lived beyond the clinical setting provide ample info to make an educated guess?

As a citizen scientist, I’d venture a hypothesis that the contextual data is likely more accurate and would be important in risk factor determination – but that it is rarely captured, and even more rarely woven into traditional healthcare system encounters and decision-making processes. After all, as Alexandra Drane of Eliza Corporation rightfully said years ago, “Life IS health.”

For this week’s #HITsm chat, I’d like to explore new definitions of health data: what SHOULD be considered relevant information for our healthcare? And how could we imagine that information being made useful at point-of-care?

Chat Topics

Topic 1: #SDOHcropping up everywhere as “critical” to understanding #publichealth. What data points do you think most relevant to you?

Topic 2: Are there non-clinical data points you would NOT want your#healthcare provider to consider in evaluating your #health? And why?

Topic 3: What do you think might be concerns about using alternative#data to assess #health risk? #Privacy#DataQuality? How to address?

Topic 4: Assuming#interoperability solved, how could alternative #data sources be incorporated into #healthcare #workflow, made useful?

Fellow data-philes may enjoy checking out the vast range of data sources freely available, for inspiration (HT Neil Raden for posting the GitHub list for me to find):

List of myriad public data sets via DataScienceCentral: http://www.datasciencecentral.com/profiles/blogs/great-github-list-of-public-data-sets

List of real-time updated open data sets available from Firebase: https://www.firebase.com/docs/open-data/

US poverty data via census: https://www.census.gov/hhes/www/poverty/data/

World climate data via WorldClim: http://www.worldclim.org/

Weather data via NCDC and NOAA: https://www.ncdc.noaa.gov/cdo-web/datasets

Health-related data sets via CDC: http://www.cdc.gov/nchs/data_access/sets/available_data.htm

Education data via National Center for Education Statistics: https://nces.ed.gov/datatools/index.asp?DataToolSectionID=4

Chat stats: 94 participants generated 872 tweets

For those not familiar with #HITsm TweetChats, #HITsm is an acronym for “healthcare IT social media” and we focus on current topics that are influencing healthcare technology, health IT, and the use of social media in healthcare. View a list of future chat moderators on the #HITsm page.

Chats are held at 11 a.m, CST, every Friday.

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Mandi Bishop

Nationally-recognized high-energy and relentlessly social health IT and data management consultant guru and blogger, specializing in rapid solution assessment, brutally honest analysis, actionable findings and recommendations, and leading results-driven systems implementation and integration initiative delivery. Mandi’s accolades include: CEOWorld Top Big Data Executives and Experts to Follow on Twitter; BigDataRepublic Top 100 Big Data Experts; Onalytica Top 100 Big Data Influencers; Analytics Week Top 100 Big Data Influencers; and Health IT Top 100 (#HIT100).