Bounds for Rating Override Rates

Improving Override Rates for Computerized Prescribing Alerts in Ambulatory Care

Computerized drug prescribing alerts can improve patient safety, but are often overridden because of poor specificity and alert overload. We developed a selective knowledge base of only clinically significant drug alerts and designated only critical-high severity alerts to be interruptive to clinician workflow (a tiered approach). Using this approach, we were able to achieve a 67% clinician acc...

Drug interaction alert override rates in the Meaningful Use era

Background: Interruptive drug interaction alerts may reduce adverse drug events and are required for Stage I Meaningful Use attestation. For the last decade override rates have been very high. Despite their widespread use in commercial EHR systems, previously described interventions to improve alert frequency and acceptance have not been well studied. Objectives: (1) To measure override rates o...

Upper bounds on oarsening rates

Upper bounds on mixing rates

We prove upper bounds on the rate, called ”mixing rate”, at which the von Neumann entropy of the expected density operator of a given ensemble of states changes under nonlocal unitary evolution. For an ensemble consisting of two states, with probabilities of p and 1 − p, we prove that the mixing rate is bounded above by 4 √ p(1− p) for any Hamiltonian of norm 1. For a general ensemble of states...

Lower Bounds for BMRM and Faster Rates for Training SVMs

Regularized risk minimization with the binary hinge loss and its variants lies at the heart of many machine learning problems. Bundle methods for regularized risk minimization (BMRM) and the closely related SVMStruct are considered the best general purpose solvers to tackle this problem. It was recently shown that BMRM requires O(1/ε) iterations to converge to an ε accurate solution. In the fir...