Data blindness, measuring policy impact, and healthcare analytics.

1. Crowdsourcing → Machine learning → Micro, macro policy evidence Premise uses a clever combination of machine learning and street-level human intelligence; their economic data helps organizations measure the impact of policy decisions at a micro and macro level. @premisedata recently closed a $50M US funding round.

2. Data blindness → Unfocused analytics → Poor decisions Data blindness prevents us from seeing what the numbers are trying to tell us. In a Read/Write guest post, OnCorps CEO (@OnCorpsHQ) Bob Suh recommends focusing on the decisions that need to be made, rather than on big data and analytics technology. OnCorps offers an intriguing app called Sales Sabermetrics.

3. Health analytics → Evidence in the cloud → Collaboration & learning Evidera announces Evalytica, a SaaS platform promising fast, transparent analysis of healthcare data. This cloud-based engine from @evideraglobal supports analyses of real-world evidence sources, including claims, EMR, and registry data.

Posted by Tracy Allison Altman on 29-Sept-2016.

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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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