Is the effect of compulsory community treatment on preventable deaths from physical disorders mediated by better access to specialized medical procedures?

Objectives: Compulsory community treatment has been shown to reduce preventable deaths from physical disorders these causes being up to 10 times more common than suicide in psychiatric patients. We investigated whether this was mediated by better access to specialized medical procedures

Optimal algorithms for selecting top-k combinations of attributes : theory and applications

Traditional top-k algorithms, e.g., TA and NRA, have been successfully applied in many areas such as information retrieval, data mining and databases. They are designed to discover k objects, e.g., top-k restaurants, with highest overall scores aggregated from different attributes, e.g., price and location. However, new emerging applications like query recommendation require providing the best combinations of attributes, instead of objects. The straightforward extension based on the existing top-k algorithms is prohibitively expensive to answer top-k combinations because they need to enumerate all the possible combinations, which is exponential to the number of attributes. In this article, we formalize a novel type of top-k query, called top-k, m, which aims to find top-k combinations of attributes based on the overall scores of the top-m objects within each combination, where m is the number of objects forming a combination. We propose a family of efficient top-k, m algorithms with different data access methods, i.e., sorted accesses and random accesses and different query certainties, i.e., exact query processing and approximate query processing. Theoretically, we prove that our algorithms are instance optimal and analyze the bound of the depth of accesses. We further develop optimizations for efficient query evaluation to reduce the computational and the memory costs and the number of accesses. We provide a case study on the real applications of top-k, m queries for an online biomedical search engine. Finally, we perform comprehensive experiments to demonstrate the scalability and efficiency of top-k, m algorithms on multiple real-life datasets.Peer reviewe

A multi-faceted intervention to implement guideline care and improve quality of care for older people who present to the emergency department with falls

<p>Abstract</p> <p>Background</p> <p>Guidelines recommend that older people should receive multi-factorial interventions following an injurious fall however there is limited evidence that this is routine practice. We aimed to improve the delivery of evidence based care to patients presenting to the Emergency Department (ED) following a fall.</p> <p>Methods</p> <p>A prospective before and after study was undertaken in the ED of a medium-sized hospital in Perth, Western Australia. Participants comprised 313 community-dwelling patients, aged 65 years and older, presenting to ED as a result of a fall. A multi-faceted strategy to change practice was implemented and included a referral pathway, audit and feedback and additional falls specialist staff. Key measures to show improvements comprised the proportion of patients reviewed by allied health, proportion of patients referred for guideline care, quality of care index, all determined by record extraction.</p> <p>Results</p> <p>Allied health staff increased the proportion of patients being reviewed from 62.7% in the before period to 89% after the intervention (P < 0.001). Before the intervention a referral for comprehensive guideline care occurred for only 6/177 (3.4%) of patients, afterwards for 28/136 (20.6%) (difference = 17.2%, 95% CI 11-23%). Average quality of care index (max score 100) increased from 18.6 (95% CI: 16.7-20.4) to 32.6 (28.6-36.6).</p> <p>Conclusions</p> <p>A multi-faceted change strategy was associated with an improvement in allied health in ED prioritizing the review of ED fallers as well as subsequent referral for comprehensive geriatric care. The processes of multi-disciplinary care also improved, indicating improved care received by the patient.</p

Compilation of a regionally-extended inter-country input-output table and its application to global value chain analysis

Studies on the rise of global value chains (GVCs) have attracted a great deal of interest in the recent economics literature. However, due to statistical and methodological challenges, most existing research ignores domestic regional heterogeneity in assessing the impact of joining GVCs. GVCs are supported not only directly by domestic regions that export goods and services to the world market, but also indirectly by other domestic regions that provide parts, components, and intermediate services to final exporting regions. To better understand the nature of a country\u27s position and degree of participation in GVCs, we need to fully examine the role of individual domestic regions. Understanding the domestic components of GVCs is especially important for larger economies such as China, the US, India and Japan, where there may be large variations in economic scale, geography of manufacturing, and development stages at the domestic regional level. This paper proposes a new framework for measuring domestic linkages to global value chains. This framework measures domestic linkages by endogenously embedding a target country\u27s (e.g. China and Japan) domestic interregional input–output tables into the OECD inter-country input–output model. Using this framework, we can more clearly understand how global production is fragmented and extended internationally and domestically