Last week I was part of the first community meeting for Data for Health, a program sponsored by the Robert Wood Johnson Foundation. It was held in Philadelphia on October 30 (an absolutely beautiful fall day).
You can catch up on the #data4health tweets thanks to Symplur — and there were some good ones:
Some themes of #Data4Health: building trust, the gulf between knowledge/info and action, & the relevance of data (timely, actionable) — Emmy Ganos (@emmyganos) October 30, 2014
“People have a right to their own bad news. Change only happens when truth is revealed.” @don_HB #data4health — EmilyKramerGolinkoff (@emilykg1) October 30, 2014
.@PHInformatics: Building trust is really key to unlocking data for use. People have to shake hands before they share data. #Data4Health
— Philly Public Health (@PHLPublicHealth) October 30, 2014
The day was also captured in a Storify: #Data4Health: Learning What Works for Philadelphia
Once again I was struck by how wide open the definition of “data” can be. I shared the following data points, based on a Pew Research study I led:
- 7 in 10 U.S. adults track a health indicator for themselves or someone else.
- Half track regularly, half track when something comes up.
- Technology plays a minor role — about 1 in 5 trackers use a medical device, an app, or any other digital tool.
- 1 in 3 trackers uses paper and pencil to take notes.
- Fully half of trackers say they do so in their heads (and that includes me).
- 1 in 3 trackers share their data with family members or clinicians, but many do not. They are asking secret questions and we must not only respect that, but build it into our planning.
- 45% of U.S. adults live with a chronic health condition; of those, 8 in 10 track some aspect of health.
- Tracking data is not a hobby for this group, but rather a way to see themselves more clearly. This might be true of public health in general — data is a mirror we try to use to make good decisions, based on facts.
In a break-out session, people shared how they track their health:
- A man who commutes by bike said he notices how he can take a certain hill so much faster at the end of the summer than in the spring, after a full season of training.
- A woman tracks how many times per week she cooks at home vs. eating take-out or going to restaurants — a proxy for good nutrition without all the annoying calorie-counting or photo-taking.
- A man tracks how many hours of sleep he gets per night.
- A woman noted that tracking can have negative effects, such as weight obsession.
- A man starts each day with a list of what he enjoys, sort of a spiritual check-in about being grateful. (I would have loved to hear more about this. I wonder if the list is longer on some days and if he tracks that or takes any action.)
- A woman noted that caregivers often track more diligently for a loved one than for themselves. “Being aware, you help the other person.”
- Someone responded with a comment: “Caregivers see the data disconnects that clinicians and public health workers cannot. How might we tap into that knowledge?”
- A third person spoke up: “My mother carefully tracked my grandmother’s health and, when she died, my mom was left with notebooks of data — the narrative arc of her illness, which could inform other people’s health journeys. Mom was left wondering what to do and thought about volunteering at a local senior center, accompanying older people to their medical appointments since she had developed that unique skill set.”
- A woman noted that trauma often triggers note-taking as a coping mechanism.
- A man said that he wishes we could collect data about people we *don’t* see in clinic. Where else are they? How can we measure something that is not there? What proxy measures can we use?
- A woman noted that mental health data is a challenge. What measures are useful?
My favorite insight of the day came from someone who, when discussing who should be part of the design process for health data systems, said that front desk workers are the ones who know the community best.
For example, if it is determined that a patient needs nutritional counseling (based on their data, let’s say), the front desk worker (not the MD or RN) will be able to say to that person: “To get to the nutrition counselor’s clinic, don’t take the 22, take the Broad Street line.” (Translation: they’ll know the city — particularly the public transportation options — better than the executives will. And that’s where the rubber hits the road, when the health data meets community data, such as traffic patterns and bus lines.)
If this quick summary intrigues you, stay tuned to the #data4health tweets and see if you can join an upcoming meeting in Phoenix, Arizona; Des Moines, Iowa; San Francisco; and Charleston, South Carolina.
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