ROI from evidence-based government, milking data for cows, and flu shot benefits diminishing.

1. Evidence standards → Knowing what works → Pay for success Susan Urahn says we’ve reached a Tipping Point on Evidence-Based Policymaking. She explains in @Governing that 24 US governments have directed $152M to programs with an estimated $521M ROI: “an innovative and rigorous approach to policymaking: Create an inventory of currently funded programs; review which ones work based on research; use a customized benefit-cost model to compare programs based on their return on investment; and use the results to inform budget and policy decisions.”

2. Sensors → Analytics → Farming profits Precision dairy farming uses RFID tags, sensors, and analytics to track the health of cows. Brian T. Horowitz (@bthorowitz) writes on TechCrunch about how farmers are milking big data for insight. Literally. Thanks to @ShellySwanback.

3. Public acceptance → Annual flu shots → Weaker response? Yikes. Now that flu shot programs are gaining acceptance, there’s preliminary evidence suggesting that repeated annual shots can gradually reduce their effectiveness under some circumstances. Scientists at the Marshfield Clinic Research Foundation recently reported that “children who had been vaccinated annually over a number of years were more likely to contract the flu than kids who were only vaccinated in the season in which they were studied.” Helen Branswell explains on STAT.

4. Opportunistic experiments → Efficient evidence → Informed family policy New guidance details how researchers and program administrators can recognize opportunities for experiments and carry them out. This allows people to discover effects of planned initiatives, as opposed to analyzing interventions being developed specifically for research studies. Advancing Evidence-Based Decision Making: A Toolkit on Recognizing and Conducting Opportunistic Experiments in the Family Self-Sufficiency and Stability Policy Area.

Posted by Tracy Allison Altman on 17-Feb-2017.

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Museum musings.

Pondering the places where people interact with artificial intelligence: Collaboration on evidence-based decision-making, automation of data-driven processes, machine learning, things like that.

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