HealthLeaders: Are these predictive models, or is that overstating what this is doing? Are you predicting outcomes? Are you modeling outcomes?
Davis: It may be taking a step too far to truly call it predictive, in that we're giving the answer. It's giving you the insights, though, of where to look. With observational data, you always have got to be careful [not] to overstate causality and the associations. It gives you associations between outcomes and the multiple comorbidities to go investigate in the right areas; to use the overused analogy, of making sure that if you drop your keys in the dark, you've got a flashlight that you can search and find the right spots. It's kind of that analogy to do the diagnosis and make sure you're targeting the areas that are going to have high impact to addressing cost issues while not impacting quality.
HealthLeaders: How has this been proven out? What is the evidence you have so far that this combination of insight and services makes a difference?
Davis: We're early in the journey, so we don't have client results that we're talking about yet publicly, but we do have validation from the Intermountain clinical and informatics community, working closely with the Homer Warner Center there, which is a 60-plus person informatics center that were codevelopers in the platform.
HealthLeaders: Is there a double-blinded format that protects PHI [personal health information]? How does that work?
Davis: No PHI data ever makes it into any IT environment where PHI information could be potentially revealed. There's a double-blinded format where there's a blinding step that's done by Intermountain before Deloitte or our platform gets involved, and there's a second double-blinded key—so it's sort of like the old nuclear days where you needed two keys to reidentify, to provide extra protection to make sure that there's never any exposure of PHI through the platform.