Computer-Assisted versus Oral-and-Written History Taking for the Prevention and Management of Cardiovascular Disease: a Systematic Review of the Literature

Background and objectives: CVD is an important global healthcare issue; it is the leading cause of global mortality, with an increasing incidence identified in both developed and developing countries. It is also an extremely costly disease for healthcare systems unless managed effectively. In this review we aimed to: – Assess the effect of computer-assisted versus oral-and-written history taking on the quality of collected information for the prevention and management of CVD. – Assess the effect of computer-assisted versus oral-and-written history taking on the prevention and management of CVD. Methods: Randomised controlled trials that included participants of 16 years or older at the beginning of the study, who were at risk of CVD (prevention) or were either previously diagnosed with CVD (management). We searched all major databases. We assessed risk of bias using the Cochrane Collaboration tool. Results: We identified two studies. One comparing the two methods of history-taking for the prevention of cardiovascular disease n = 75. The study shows that generally the patients in the experimental group underwent more laboratory procedures, had more biomarker readings recorded and/or were given (or had reviewed), more dietary changes than the control group. The other study compares the two methods of history-taking for the management of cardiovascular disease (n = 479). The study showed that the computerized decision aid appears to increase the proportion of patients who responded to invitations to discuss CVD prevention with their doctor. The Computer-Assisted History Taking Systems (CAHTS) increased the proportion of patients who discussed CHD risk reduction with their doctor from 24% to 40% and increased the proportion who had a specific plan to reduce their risk from 24% to 37%. Discussion: With only one study meeting the inclusion criteria, for prevention of CVD and one study for management of CVD we did not gather sufficient evidence to address all of the objectives of the review. We were unable to report on most of the secondary patient outcomes in our protocol. Conclusions: We tentatively conclude that CAHTS can provide individually-tailored information about CVD prevention. However, further primary studies are needed to confirm these findings. We cannot draw any conclusions in relation to any other clinical outcomes at this stage. There is a need to develop an evidence base to support the effective development and use of CAHTS in this area of practice. In the absence of evidence on effectiveness, the implementation of computer-assisted history taking may only rely on the clinicians’ tacit knowledge, published monographs and viewpoint articles

What We Mean When We Talk About Adherence In Respiratory Medicine

The Respiratory Effectiveness Group (REG; www.effectivenessevaluation.org) supported the Expert Adherence Panel Meeting at which many of the concepts presented in this paper were first discussed. REG also supported the manuscript submission costs. ALD, EvG, and MdB have received funding from the European Community's 7th Framework (FP7/2007-2013) under grant agreement no. 282593. Teva supported the meeting costs at which the concepts in this paper were discussed by the co-authors and the open access publication fee for this article. The authors had full editorial control over the ideas presented.Peer reviewedPublisher PD

Grid multi-category response logistic models.

BackgroundMulti-category response models are very important complements to binary logistic models in medical decision-making. Decomposing model construction by aggregating computation developed at different sites is necessary when data cannot be moved outside institutions due to privacy or other concerns. Such decomposition makes it possible to conduct grid computing to protect the privacy of individual observations.MethodsThis paper proposes two grid multi-category response models for ordinal and multinomial logistic regressions. Grid computation to test model assumptions is also developed for these two types of models. In addition, we present grid methods for goodness-of-fit assessment and for classification performance evaluation.ResultsSimulation results show that the grid models produce the same results as those obtained from corresponding centralized models, demonstrating that it is possible to build models using multi-center data without losing accuracy or transmitting observation-level data. Two real data sets are used to evaluate the performance of our proposed grid models.ConclusionsThe grid fitting method offers a practical solution for resolving privacy and other issues caused by pooling all data in a central site. The proposed method is applicable for various likelihood estimation problems, including other generalized linear models

The role of statins in prevention and treatment of community acquired pneumonia: a systematic review and meta-analysis.

BACKGROUND: Emerging epidemiological evidence suggests that statins may reduce the risk of community-acquired pneumonia (CAP) and its complications. PURPOSE: Performed a systematic review to address the role of statins in the prevention or treatment of CAP. DATA SOURCE: Ovid MEDLINE, Cochrane, EMBASE, ISI Web of Science, and Scopus from inception through December 2011 were searched for randomized clinical trials, cohort and case-control studies. STUDY SELECTION: Two authors independently reviewed studies that examined the role of statins in CAP. DATA EXTRACTION: Data about study characteristics, adjusted effect-estimates and quality characteristics was extracted. DATA SYNTHESIS: Eighteen studies corresponding to 21 effect-estimates (eight and 13 of which addressed the preventive and therapeutic roles of statins, respectively) were included. All studies were of good methodological quality. Random-effects meta-analyses of adjusted effect-estimates were used. Statins were associated with a lower risk of CAP, 0.84 (95% CI, 0.74-0.95), I(2) = 90.5% and a lower short-term mortality in patients with CAP, 0.68 (95% CI, 0.59-0.78), I(2) = 75.7%. Meta-regression did not identify sources of heterogeneity. A funnel plot suggested publication bias in the treatment group, which was adjusted by a novel regression method with a resultant effect-estimate of 0.85 (95% CI, 0.77-0.93). Sensitivity analyses using the rule-out approach showed that it is unlikely that the results were due to an unmeasured confounder. CONCLUSIONS: Our meta-analysis reveals a beneficial role of statins for the risk of development and mortality associated with CAP. However, the results constitute very low quality evidence as per the GRADE framework due to observational study design, heterogeneity and publication bias

Advocacy Coalition Framework Lens on Pressing Healthcare Issues

In deciding how to interpret and understand public policy, many experts use theories and frameworks to justify their reasoning. One of the most common avenue of viewing policy involves the advocacy coalition framework based on its broad applicability. This popular framework consists of banding like-minded individuals together into a coalition to advance the narrative by creating acceptable policies for their group. These coalitions normally include a wide range of professional backgrounds from interest groups, elected officials, researchers in academia. These groups utilize special events to influence subfields consisting of actors who decide the solutions for policy problems. Subfields normally are made up of key players employed in government institutions and private industrial groups who willingly agree to work toward a compromise with the goal to create policy acceptable for both sides (Cairney 2014) These coalitions influence the subfield in different ways through capitalizing on their influential power or by ignoring the alliances and mergers of the groups. This paper shall explore how advocacy coalition framework works for three pressing issues facing the healthcare industry. These three policies focus on drug pricing, heath data privacy and opioid liability. This paper will explore the policy in depth, provide historical context and the major players while outlining how the specific proposals fit in the framework as well as identifying the framework’s limitations with the policy