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data & donuts

"Maybe stories are just data with a soul." -- Brene Brown

The data that didn't bark...

5/29/2019

 
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Are you a Sherlock Holmes fan by any chance? One of the more famous tomes involves the disappearance of a valuable racehorse.
The "curious incident of the dog in the night-time" is easily explained: the dog made no noise, because no stranger was there. As Holmes explains: "I had grasped the significance of the silence of the dog, for one true inference invariably suggests others.... Obviously the midnight visitor was someone whom the dog knew well. It was Straker who removed Silver Blaze from his stall and led him out on to the moor"--The Adventure of Silver Blaze (Wikipedia)
Obviously there are other reasons the dog may not have barked but the most dramatic of course, was described by Holmes. This reminded me of silent data. Hear my out--I am going some where with this.
We are accustomed to looking at the same things the same way. I attended the Committee on Informing the Selection of Leading Health Indicators for Healthy People 2030. I remain unimpressed by the Healthy People 2020 metrics for many reasons. Sure it's a start but the problem remains--if data is old, aggregated to too high of a level, and chock full of low hanging fruit--what are we striving for?

Amy O'Hara from the Massive Data Institute at McCourt School of Public Policy, Georgetown University discussed data sources for objectives and the Leading Health Indicators. I could relate with her tasks the most. It is all about what you measure. The data that is now being gathered to expand definitions of poverty was not gathered to be shared. These were all internal databases not designed for harmonization--hence we have this massive problem with data quality and intersectionality.

Should we do what we have done before because it is easy and the data is ready?

​The non-barking dog--or should we evolve our questions and take the practical steps to build a system that we can improve. Incentivize people to understand what is being measured. Head over to HealthyPeople.gov and you will see what I mean.

If reducing diabetes-related deaths (age adjusted, per 100,000 population) is the target, how are we going to focus on the disparities in counties, zip codes, and communities? We are not measuring the right things. I would argue that within National Target Met (green states) areas are many communities suffering from disease. We need granularity. We need new measures--we need a barking dog.
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Akimbo is one of those podcasts that delivers time and time again. Seth's clarity and insight can help redirect your focus if you start monitoring the wrong things.
 Seth Godin argues we need to place the right metrics on the table. What story do we tell ourselves, our co-workers, and customers? It matters...
Money has one advantage. It is easy to measure but that isn't the point. We want change we can be proud of. Lots of organizations measure money but they are leaving a trail of obesity or disease, discomfort or unhappiness. This creates systems that can't sustain for the long haul.--Seth Godin

What are you measuring?

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  • Data & Donuts (thinky thoughts)
  • COLLABORATor
  • Data talks, people mumble
  • Cancer: The Brand
  • Time to make the donuts...
  • donuts (quick nibbles)
  • Tools for writers and soon-to-be writers
  • datamonger.health
  • The "How" of Data Fluency