5 resultados para proactive policing
em Duke University
Resumo:
BACKGROUND: Accurate detection of persons in need of mental healthcare is crucial to reduce the treatment gap between psychiatric burden and service use in low- and middle-income (LAMI) countries. AIMS: To evaluate the accuracy of a community-based proactive case-finding strategy (Community Informant Detection Tool, CIDT), involving pictorial vignettes, designed to initiate pathways for mental health treatment in primary care settings. METHOD: Community informants using the CIDT identified screen positive (n = 110) and negative persons (n = 85). Participants were then administered the Composite International Diagnostic Interview (CIDI). RESULTS: The CIDT has a positive predictive value of 0.64 (0.68 for adults only) and a negative predictive value of 0.93 (0.91 for adults only). CONCLUSIONS: The CIDT has promising detection properties for psychiatric caseness. Further research should investigate its potential to increase demand for, and access to, mental health services.
Resumo:
BACKGROUND: Many patients with diabetes have poor blood pressure (BP) control. Pharmacological therapy is the cornerstone of effective BP treatment, yet there are high rates both of poor medication adherence and failure to intensify medications. Successful medication management requires an effective partnership between providers who initiate and increase doses of effective medications and patients who adhere to the regimen. METHODS: In this cluster-randomized controlled effectiveness study, primary care teams within sites were randomized to a program led by a clinical pharmacist trained in motivational interviewing-based behavioral counseling approaches and authorized to make BP medication changes or to usual care. This study involved the collection of data during a 14-month intervention period in three Department of Veterans Affairs facilities and two Kaiser Permanente Northern California facilities. The clinical pharmacist was supported by clinical information systems that enabled proactive identification of, and outreach to, eligible patients identified on the basis of poor BP control and either medication refill gaps or lack of recent medication intensification. The primary outcome is the relative change in systolic blood pressure (SBP) measurements over time. Secondary outcomes are changes in Hemoglobin A1c, low-density lipoprotein cholesterol (LDL), medication adherence determined from pharmacy refill data, and medication intensification rates. DISCUSSION: Integration of the three intervention elements--proactive identification, adherence counseling and medication intensification--is essential to achieve optimal levels of control for high-risk patients. Testing the effectiveness of this intervention at the team level allows us to study the program as it would typically be implemented within a clinic setting, including how it integrates with other elements of care. TRIAL REGISTRATION: The ClinicalTrials.gov registration number is NCT00495794.
Resumo:
© 2012 by Oxford University Press. All rights reserved.This article considers the determinants and effects of M&As in the pharmaceutical industry, with a particular focus on innovation and R&D productivity. As is the case in other industries, mergers in the pharmaceutical field are driven by a variety of company motives and conditions. These include defensive responses to industry shocks as well as more proactive rationales, such as economies of scale and scope, access to new technologies, and expansion to new markets. It is important to take account of firms' characteristics and motivations in evaluating merger performance, rather than using a broad aggregate brushstroke. Research to date on pharmaceuticals suggests considerable variation in both motivation and outcomes. From an antitrust policy standpoint, the larger horizontal mergers in pharmaceuticals have run into few challenges from regulatory authorities in the United States and the European Union, given the option to spin off competing therapeutic products to other drug firms.
Resumo:
BACKGROUND/AIMS: The obesity epidemic has spread to young adults, and obesity is a significant risk factor for cardiovascular disease. The prominence and increasing functionality of mobile phones may provide an opportunity to deliver longitudinal and scalable weight management interventions in young adults. The aim of this article is to describe the design and development of the intervention tested in the Cell Phone Intervention for You study and to highlight the importance of adaptive intervention design that made it possible. The Cell Phone Intervention for You study was a National Heart, Lung, and Blood Institute-sponsored, controlled, 24-month randomized clinical trial comparing two active interventions to a usual-care control group. Participants were 365 overweight or obese (body mass index≥25 kg/m2) young adults. METHODS: Both active interventions were designed based on social cognitive theory and incorporated techniques for behavioral self-management and motivational enhancement. Initial intervention development occurred during a 1-year formative phase utilizing focus groups and iterative, participatory design. During the intervention testing, adaptive intervention design, where an intervention is updated or extended throughout a trial while assuring the delivery of exactly the same intervention to each cohort, was employed. The adaptive intervention design strategy distributed technical work and allowed introduction of novel components in phases intended to help promote and sustain participant engagement. Adaptive intervention design was made possible by exploiting the mobile phone's remote data capabilities so that adoption of particular application components could be continuously monitored and components subsequently added or updated remotely. RESULTS: The cell phone intervention was delivered almost entirely via cell phone and was always-present, proactive, and interactive-providing passive and active reminders, frequent opportunities for knowledge dissemination, and multiple tools for self-tracking and receiving tailored feedback. The intervention changed over 2 years to promote and sustain engagement. The personal coaching intervention, alternatively, was primarily personal coaching with trained coaches based on a proven intervention, enhanced with a mobile application, but where all interactions with the technology were participant-initiated. CONCLUSION: The complexity and length of the technology-based randomized clinical trial created challenges in engagement and technology adaptation, which were generally discovered using novel remote monitoring technology and addressed using the adaptive intervention design. Investigators should plan to develop tools and procedures that explicitly support continuous remote monitoring of interventions to support adaptive intervention design in long-term, technology-based studies, as well as developing the interventions themselves.