“Digital Health Humanities, part 1”

Kirsten Ostherr, PhD, MPH@kirstenostherr

oEvolution of health blogging & patient storytelling online

oEmergence of “big health data” onlineoConcepts: Datafication, Dataveillance,

Citizen Data-MakingoAnalysis of harms

Outline

Exercise: Daily mediascape1. Solo: list your typical daily online,

mobile, digital habits2. Pair & share3. Group discussion

oWhich of your typical daily online, mobile, digital habits have health relevance?

oWho has access to the resulting data? oWho would you choose to share it with, &

why?

1. Health Datafication

(Pai et al., 2012)

datafication:“the effect of individual actions, sensory data, and other real world measurements creating a digital image of our reality”

(Viktor Mayer-Schonberger & Kenneth Cukier, 2013)

datafication: a process of “rendering into data aspects of the world not previously quantified”

(Helen Kennedy et al., 2015)

user-generated content: regular people’s data, information, or media provided for public use, e.g. restaurant ratings, wikis, how-to videos, etc.

(Krumm et al., 2008; Van Dijck, 2009)

more data = more knowledge = better health outcomes?

what new kinds of knowledge might these insights reveal, and for whom might they improve outcomes?

“The social determinants of health (SDH) are the conditions in which people are born, grow, work, live, and age, and the wider set of forces and systems shaping the conditions of daily life.”

World Health Organization

Datafication: a new social determinant of health with capacity to shape the conditions of daily life

If wearable health technologies capture SDoH, can they democratize access to care? Will they exacerbate health disparities? Or both? Discuss.

From Datafication to Dataveillance

Credit: Kevin Hong/Wired magazine

Networks of doctors used WhatsApp to identify Zika outbreak

new Zika media iconography: people staring at smartphone screens

Health communications via WhatsApp: from command and control to decentralized

network

cartoon graphics & animation from health organizations

From datafication to data-making

dataficationbenefits medical corporate paternalism

data-makingbenefits individual autonomy (maybe)

“metaclinical user-generated health data”

• data captured through devices or software• purpose-built or commercially available • tracks personal health data • e.g. wearable heart rate monitors, step-counters, sleep trackers • used outside of traditional clinical settings = metaclinical

“medical contexts”

• aka “traditional clinical settings” • doctor-patient interaction governed by health law (e.g. Health

Information Portability and Accountability Act of 1996 (HIPAA)) • medical device use governed by U.S Food and Drug

Administration (FDA) approval & regulatory procedures

Does putting health measurement and quantification into the hands of ordinary users become a democratizing force that challenges traditional doctor-patient or state-citizen power and knowledge hierarchies?

oMight distribution of healthcare to metaclinicalsettings disrupt health infrastructures that citizens have come to depend on?

oMight metaclinical tools make users vulnerable to third-party exploitation?

oWhat factors might tip the scales in one direction or another?

key takeaways, part 1

1. Patients don’t experience clinical & metaclinical ecosystems as separate.

2. Corporations use both clinical & metaclinicaldata sources for digital profiling.

3. Big data & digital health are critical sites of emergent health disparities.

key takeaways, part 2

4. Not being subject to dataveillance may produce more health disparities than being subject to dataveillance

5. Distributed networks of dataveillance technologies do not necessarily equate to distributed access to power

Lilly Irani, Asst. Prof Science & Technology Studies, UCSD