Statin prescribing in Northern Ireland and England pre and post introduction of the quality and outcomes framework

Objective The objective of this research was to examine differences in patterns of statin prescribing between Northern Ireland and England both before and after the introduction of the Quality and Outcomes Framework (QOF). Setting: Primary care practices in Northern Ireland and England. Method Northern Ireland practices were matched with practices in England, statin prescribing data and QOF achievement scores (for the first year post-QOF) were obtained. Crude prescribing data from matched practices were manipulated to provide a data set of Defined Daily Doses (DDDs)/1,000 patients and cost/DDD/1,000 patients for each statin drug entity covering 1 year before and after the introduction of QOF. QOF achievements were converted into percentage scores for matched practices. Main outcome measure Cost per defined daily dose (DDD) per 1,000 patients. Results Significantly less statins (DDD/1,000 patients) were dispensed in Northern Ireland compared with the matched region in England both before and after the introduction of QOF (P

Select, Link and Rank: Diversified Query Expansion and Entity Ranking using Wikipedia

A search query, being a very concise grounding of user intent, could potentially have many possible interpretations. Search engines hedge their bets by diversifying top results to cover multiple such possibilities so that the user is likely to be satisfied, whatever be her intended interpretation. Diversified Query Expansion is the problem of diversifying query expansion suggestions, so that the user can specialize the query to better suit her intent, even before perusing search results. We propose a method, Select-Link-Rank, that exploits semantic information from Wikipedia to generate diversified query expansions. SLR does collective processing of terms and Wikipedia entities in an integrated framework, simultaneously diversifying query expansions and entity recommendations. SLR starts with selecting informative terms from search results of the initial query, links them to Wikipedia entities, performs a diversity-conscious entity scoring and transfers such scoring to the term space to arrive at query expansion suggestions. Through an extensive empirical analysis and user study, we show that our method outperforms the state-of-the-art diversified query expansion and diversified entity recommendation techniques.