Before moving on to Care Coordination as part of our series on accessing food resources, we're pausing for a quick look at using predictive analytics to assess which patients might be at risk of food insecurity and how to best reach them with resources they can use.
This episode references several resources on this topic for learning more, so go check these out:
Also, I told a very simplified version of my graduate thesis - I feel that to defend the honor of my department chair (who may very well be listening) I should add that I did have a more useful theory I was testing. My theory was that traditional customer surveys were over-weighting the opinions of activist consumers, people who felt very strongly that local foods (for example) were important to serve. I came up with this theory while being an activist consumer trying to manipulate surveys. But you could redesign surveys to better pull out the preferences of consumers who, yes, would prefer to eat local foods, but that had other priorities they weren't going to sacrifice along the way. That would allow for offering menu options with broader appeal and pulling products like local foods further into the mainstream. This, by the way, tells you how long ago I was in grad school because at the time eating local was still considered a bit fringe.
The most interesting thing I learned from that experiment? When you redesign customer surveys so that activist students can't game the system, many of them get into a huff, refuse to complete the survey, and send you nasty emails.
And in case you're wondering why the local vegetarian option in that example was so expensive, it's not just that the ingredients were pricey - building an organic local vegetarian entree meant a lot of hand processing of whole ingredients in a kitchen where that was not the norm for other dishes, which utilized pre-sliced, pre-cubed, and otherwise lightly processed ingredients from national suppliers. This time cost will become important in other episodes, so go ahead and keep it in mind.