Implementation of a Standardized Handoff System for a General Surgery Residency Program

Introduction: The I-PASS Handoff Bundle is an evidence based standardized set of educational materials designed to decrease handoff failures in patient care. Two of every three sentinel events , the most serious events reported to the Joint Commission, are due to failures of communication, including miscommunication during patient care handoffs. Implementation of the I-PASS method results in decreased medical errors and preventable adverse events There are few studies that evaluate this validated method in the context of a General Surgery resident program We aim to implement the I-PASS system into the transition of care process for General Surgery residents at our institution, and to analyze of the quality of the handoff process before and after the implementation.https://jdc.jefferson.edu/patientsafetyposters/1047/thumbnail.jp

A unifying framework for seed sensitivity and its application to subset seeds

We propose a general approach to compute the seed sensitivity, that can be applied to different definitions of seeds. It treats separately three components of the seed sensitivity problem -- a set of target alignments, an associated probability distribution, and a seed model -- that are specified by distinct finite automata. The approach is then applied to a new concept of subset seeds for which we propose an efficient automaton construction. Experimental results confirm that sensitive subset seeds can be efficiently designed using our approach, and can then be used in similarity search producing better results than ordinary spaced seeds

Dictionary Matching with One Gap

The dictionary matching with gaps problem is to preprocess a dictionary $D$ of $d$ gapped patterns $P_1,\ldots,P_d$ over alphabet $\Sigma$, where each gapped pattern $P_i$ is a sequence of subpatterns separated by bounded sequences of don't cares. Then, given a query text $T$ of length $n$ over alphabet $\Sigma$, the goal is to output all locations in $T$ in which a pattern $P_i\in D$, $1\leq i\leq d$, ends. There is a renewed current interest in the gapped matching problem stemming from cyber security. In this paper we solve the problem where all patterns in the dictionary have one gap with at least $\alpha$ and at most $\beta$ don't cares, where $\alpha$ and $\beta$ are given parameters. Specifically, we show that the dictionary matching with a single gap problem can be solved in either $O(d\log d + |D|)$ time and $O(d\log^{\varepsilon} d + |D|)$ space, and query time $O(n(\beta -\alpha )\log\log d \log ^2 \min \{ d, \log |D| \} + occ)$, where $occ$ is the number of patterns found, or preprocessing time and space: $O(d^2 + |D|)$, and query time $O(n(\beta -\alpha ) + occ)$, where $occ$ is the number of patterns found. As far as we know, this is the best solution for this setting of the problem, where many overlaps may exist in the dictionary.Comment: A preliminary version was published at CPM 201

Computing discriminating and generic words

International audienceWe study the following three problems of computing generic or discriminating words for a given collection of documents. Given a pattern P and a threshold d, we want to report (i) all longest extensions of P which occur in at least d documents, (ii) all shortest extensions of P which occur in less than d documents, and (iii) all shortest extensions of P which occur only in d selected documents. For these problems, we propose efficient algorithms based on suffix trees and using advanced data structure techniques. For problem (i), we propose an optimal solution with constant running time per output word

A suffix tree or not a suffix tree?

In this paper we study the structure of suffix trees. Given an unlabeled tree τ on n nodes and suffix links of its internal nodes, we ask the question ”Is τ a suffix tree?”, i.e., is there a string S whose suffix tree has the same topological structure as τ? We place no restrictions on S, in particular we do not require that S ends with a unique symbol. This corresponds to considering the more general definition of implicit or extended suffix trees. Such general suffix trees have many applications and are for example needed to allow efficient updates when suffix trees are built online. Deciding if τ is a suffix tree is not an easy task, because, with no restrictions on the final symbol, we cannot guess the length of a string that realizes τ from the number of leaves. And without an upper bound on the length of such a string, it is not even clear how to solve the problem by an exhaustive search. In this paper, we prove that τ is a suffix tree if and only if it is realized by a string S of length n−1, and we give a linear-time algorithm for inferring S when the first letter on each edge is known. This generalizes the work of I et al. [Discrete Appl. Math. 163, 2014]