Phil 12.13.16

7:00 – 5:30 ASRC

  • Added a page for my model notes
  • Continuing with Sociophysics
  • Integrity meeting
    • Bellrock needs a summary of why no HCAHPS display. We could put something really simple that does not get rolled into the scoring of the impactors. Like claim numbers. Katy suggests a ‘ticker’ (Sparkline?)  of claim volume/amounts
    • Need Gregg’s suggestion of what the ‘hot button’ indicators should be (action item), based on the claims data.
    • Small number of items that we can be tracking the actual values of (no calculation) that we can roll up and display.
    • NPPS as an input that gets added to stand in for self-reported flags??
    • Goal of the system is to decide whether the users should spend coordination time on expensive patients.
    • NDC – National Drug Code. Counts of drugs by claim period. Where does this come from? Counts of denied?
    • Claim period is monthly?
  • Having issues with getting lines read cleanly. For the time being, I’m going to throw away the bad lines, but later, I want to make persistent objects and get the data from postgres directly.
  • Tensor spectral clustering for partitioning higher-order network structures
  • Multilinear PageRankIn this paper, we first extend the celebrated PageRank modification to a higher-order Markov chain. Although this system has attractive theoretical properties, it is computationally intractable for many interesting problems. We next study a computationally tractable approximation to the higher-order PageRank vector that involves a system of polynomial equations called multilinear PageRank. This is motivated by a novel “spacey random surfer” model, where the surfer remembers bits and pieces of history and is influenced by this information. The underlying stochastic process is an instance of a vertex-reinforced random walk. We develop convergence theory for a simple fixed-point method, a shifted fixed-point method, and a Newton iteration in a particular parameter regime. In marked contrast to the case of the PageRank vector of a Markov chain where the solution is always unique and easy to compute, there are parameter regimes of multilinear PageRank where solutions are not unique and simple algorithms do not converge. We provide a repository of these non-convergent cases that we encountered through exhaustive enumeration and randomly sampling that we believe is useful for future study of the problem

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