ObjectivesTo understand the experience of Metro Vancouver’s Homelessness Partnering Strategy-funded Housing First program and how it is functioning from the perspective of a representative sample of providers and clients who deliver and receive HF services.MethodsThirty-four clients and providers who currently or formerly delivered HF in Metro Vancouver participated in one-on-one interviews (n = 26) or focus groups (n = 8) between March and April 2017 and data were thematically analyzed.ResultsStrengths of the HF program included: the ability to transition persons from the street into housing with individualized service supports and, in certain cases, with 12-month rent subsidies, household goods, and connection to community resources. Identified program weaknesses were: eligibility criteria, limited rent subsidy funds, limited provider capacity, and workload burden. Suggested opportunities to improve HF were: streamlining federal and provincial reporting and rent subsidy systems and building friendly landlord networks. Potential threats to HF described were: limited affordable housing, stigma and discrimination toward clients, inadequate income assistance, and limited opportunity for cross-sector collaboration.ConclusionsThe delivery of HF in regions that have limited affordable housing presents unique challenges. Recommendations are provided to improve HF practice and policy in these contexts. 相似文献
Over the past five years the Artificial Intelligence Center at SRI has been developing a new technology to address the problem of automated information management within real- world contexts. The result of this work is a body of techniques for automated reasoning from evidence that we call evidential reasoning. The techniques are based upon the mathematics of belief functions developed by Dempster and Shafer and have been successfully applied to a variety of problems including computer vision, multisensor integration, and intelligence analysis.
We have developed both a formal basis and a framework for implementating automated reasoning systems based upon these techniques. Both the formal and practical approach can be divided into four parts: (1) specifying a set of distinct propositional spaces, (2) specifying the interrelationships among these spaces, (3) representing bodies of evidence as belief distributions, and (4) establishing paths of the bodies for evidence to move through these spaces by means of evidential operations, eventually converging on spaces where the target questions can be answered. These steps specify a means for arguing from multiple bodies of evidence toward a particular (probabilistic) conclusion. Argument construction is the process by which such evidential analyses are constructed and is the analogue of constructing proof trees in a logical context.
This technology features the ability to reason from uncertain, incomplete, and occasionally inaccurate information based upon seven evidential operations: fusion, discounting, translation, projection, summarization, interpretation, and gisting. These operation are theoretically sound but have intuitive appeal as well.
In implementing this formal approach, we have found that evidential arguments can be represented as graphs. To support the construction, modification, and interrogation of evidential arguments, we have developed Gister. Gister provides an interactive, menu-driven, graphical interface that allows these graphical structures to be easily manipulated.
Our goal is to provide effective automated aids to domain experts for argument construction. Gister represents our first attempt at such an aid. 相似文献
Despite the increasing evidence for the effectiveness of telehealth technology in screening and treating chronic diseases, and comorbid depression among older adults, they have been slowly adopted by home health care (HHC) agencies. Therefore, this study aimed to identify factors that determine telehealth technology adoption. Twenty directors from the National Association for Homecare & Hospice member agencies completed a 45-min telephone interview. Questions were asked regarding their perceptions of telehealth, the key determinants of telehealth adoption and use, and recommendations they would give on telehealth adoption. The majority of the participants perceived telehealth as effective for managing symptoms and reducing cost. Meanwhile, some participants had a mixed feeling toward telehealth for depression care as they did not recognize their agency as equipped with the necessary resources and trained staff. Moreover, significant determinants of telehealth adoption included the agency-related characteristics, the patient-home environment, reimbursement and cost-related factors, and staff telehealth perception. Findings imply that there is a need for financial support both at the state and the federal levels to encourage telehealth adoption among HHC agencies. Future studies should consider exploring strategies used by successful programs to overcome barriers. 相似文献
Random effects model can account for the lack of fitting a regression model and increase precision of estimating area‐level means. However, in case that the synthetic mean provides accurate estimates, the prior distribution may inflate an estimation error. Thus, it is desirable to consider the uncertain prior distribution, which is expressed as the mixture of a one‐point distribution and a proper prior distribution. In this paper, we develop an empirical Bayes approach for estimating area‐level means, using the uncertain prior distribution in the context of a natural exponential family, which we call the empirical uncertain Bayes (EUB) method. The regression model considered in this paper includes the Poisson‐gamma and the binomial‐beta, and the normal‐normal (Fay–Herriot) model, which are typically used in small area estimation. We obtain the estimators of hyperparameters based on the marginal likelihood by using a well‐known expectation‐maximization algorithm and propose the EUB estimators of area means. For risk evaluation of the EUB estimator, we derive a second‐order unbiased estimator of a conditional mean squared error by using some techniques of numerical calculation. Through simulation studies and real data applications, we evaluate a performance of the EUB estimator and compare it with the usual empirical Bayes estimator. 相似文献
BackgroundCaesarean delivery before 39 weeks of gestation increases the risk of morbidity among infants. Taiwan has one of the highest caesarean rates in the world, but little attention has been paid to this issue. This study aimed to describe the rate of caesarean delivery before 39 weeks gestation among women who did not have labour signs and had a non-emergency caesarean delivery in Taiwan and to examine whether the phenomenon was associated with the Chinese cultural practice of selecting an auspicious time for birth.MethodsWe recruited women at 15–28 weeks of pregnancy at 5 hospitals in northern Taiwan and followed them at 4 or 5 weeks after delivery using structured questionnaires. This analysis included 150 primiparous mothers with a singleton pregnancy who had a non-emergency caesarean delivery without the presence of labour signs.ResultsNinety-three of these women (62.0%) had caesarean deliveries before 39 weeks of gestation. Logistic regression analysis showed that women who had selected an auspicious time for delivery (OR = 2.82, 95% CI: 1.15–6.95) and delivered in medical centres (OR = 5.26, 95% CI: 2.25–12.26) were more likely to deliver before 39 weeks of gestation.ConclusionNon-emergency caesarean delivery before 39 weeks of gestation was common among the study women, and was related to the Chinese cultural practice of selecting an auspicious time for birth. Further studies are needed to examine the risks and benefits associated with timing of caesarean delivery in Taiwan in order to generate a consensus among obstetricians and give pregnant women appropriate information. 相似文献
This paper investigates the waste collection problem and characterizes the problem as a set-covering and vehicle routing problem (VRP) complicated by inter-arrival time constraints. The study proposes a bi-level optimization formulation to model the split delivery VRP with multiple trips to determine the minimum-distance route. The first stage optimally plans the collection points that cover all residential blocks. The second stage applies a heuristics method to solve the minimum vehicles used and minimum distance traveled for collecting residential waste. This research contributes to model this period VRP and to introduce the heuristics method to solve the problem efficiently. The study is important in laying the groundwork for understanding the possibility of improving the service level of municipal solid waste collection. 相似文献