Cameron C.,Canadian Agency for Drugs and Technologies in Health CADTH |
Coyle D.,University of Ottawa |
Ur E.,University of British Columbia |
Ur E.,Medication Review |
And 2 more authors.
CMAJ | Year: 2010
Background: The benefits of self-monitoring blood glucose levels are unclear in patients with type 2 diabetes mellitus who do not use insulin, but there are considerable costs. We sought to determine the cost effectiveness of self-monitoring for patients with type 2 diabetes not using insulin. Methods: We performed an incremental cost-effectiveness analysis of the self-monitoring of blood glucose in adults with type 2 diabetes not taking insulin. We used the United Kingdom Prospective Diabetes Study (UKPDS) model to forecast diabetes-related complications, corresponding quality-adjusted life years and costs. Clinical data were obtained from a systematic review comparing self-monitoring with no self-monitoring. Costs and utility decrements were derived from published sources. We performed sensitivity analyses to examine the robustness of the results. Results: Based on a clinically modest reduction in hemoglobin A1c of 0.25% (95% confidence interval 0.15-0.36) estimated from the systematic review, the UKPDS model predicted that self-monitoring performed 7 or more times per week reduced the lifetime incidence of diabetes-related complications compared with no self-monitoring, albeit at a higher cost (incremental cost per quality-adjusted life year $113 643). The results were largely unchanged in the sensitivity analysis, although the incremental cost per quality-adjusted life year fell within widely cited cost-effectiveness thresholds when testing frequency or the price per test strip was substantially reduced from the current levels. Interpretation: For most patients with type 2 diabetes not using insulin, use of blood glucose test strips for frequent self-monitoring (≥ 7 times per week) is unlikely to represent efficient use of finite health care resources, although periodic testing (e.g., 1 or 2 times per week) may be costeffective. Reduced test strip price would likely also improve cost-effectiveness. © 2010 Canadian Medical Association or its licensors.
Ford C.,Canadian Agency for Drugs and Technologies in Health CADTH |
Tolmie D.,Bastyr University
Journal of Hospital Librarianship | Year: 2016
ABSTRACT: The object of this study was to explore how medical librarians use Twitter to collaborate with colleagues. A weekly #medlibs Twitter chat was analyzed and coded by researchers. Based on this analysis, a 19 question survey was developed and disseminated online. From the 151 responses, 125 met inclusion criteria; n = 125). Themes regarding the use and value of Twitter emerged, including: using Twitter to keep current; Twitter as a knowledge base for professional development; as a place to facilitate collaboration and networking with colleagues, to promote services or self. Of those surveyed, 74.2% found Twitter professionally valuable. Medical librarians use Twitter to varying degrees and with varying success. Those who use Twitter as a part of their professional lives appear to draw a great deal of value for communication and collaborating with professional peers. Published with license by Taylor & Francis © Caitlyn Ford and David Tolmie.
Jansen J.P.,Mapi Values |
Fleurence R.,Oxford Outcomes |
Devine B.,University of Washington |
Itzler R.,Merck And Co. |
And 6 more authors.
Value in Health | Year: 2011
Evidence-based health-care decision making requires comparisons of all relevant competing interventions. In the absence of randomized, controlled trials involving a direct comparison of all treatments of interest, indirect treatment comparisons and network meta-analysis provide useful evidence for judiciously selecting the best choice(s) of treatment. Mixed treatment comparisons, a special case of network meta-analysis, combine direct and indirect evidence for particular pairwise comparisons, thereby synthesizing a greater share of the available evidence than a traditional meta-analysis. This report from the ISPOR Indirect Treatment Comparisons Good Research Practices Task Force provides guidance on the interpretation of indirect treatment comparisons and network meta-analysis to assist policymakers and health-care professionals in using its findings for decision making. We start with an overview of how networks of randomized, controlled trials allow multiple treatment comparisons of competing interventions. Next,anintroduction to the synthesis of the available evidence with a focus on terminology, assumptions, validity, and statistical methods is provided, followed by advice on critically reviewing and interpreting an indirect treatment comparison or network meta-analysis to inform decision making. We finish with a discussion of what to do if there are no direct or indirect treatment comparisons of randomized, controlled trials possible and a health-care decision still needs to be made. Copyright © 2011, International Society for Pharmacoeconomics and Outcomes Research (ISPOR).
Richter T.,Canadian Agency for Drugs and Technologies in Health CADTH |
Nestler-Parr S.,Roboleo and Co |
Babela R.,St Elizabeth University |
Khan Z.M.,Celgene |
And 3 more authors.
Value in Health | Year: 2015
Background At present, there is no universal definition of rare disease. Objective To provide an overview of rare disease definitions currently used globally. Methods We systematically searched for definitions related to rare disease from organizations in 32 international jurisdictions. Descriptive statistics of definitions were generated and prevalence thresholds were calculated. Results We identified 296 definitions from 1109 organizations. The terms "rare disease(s)" and "orphan drug(s)" were used most frequently (38% and 27% of the definitions, respectively). Qualitative descriptors such as "life-threatening" were used infrequently. A prevalence threshold was specified in at least one definition in 88% of the jurisdictions. The average prevalence threshold across organizations within individual jurisdictions ranged from 5 to 76 cases/100,000 people. Most jurisdictions (66%) had an average prevalence threshold between 40 and 50 cases/100,000 people, with a global average of 40 cases/100,000 people. Prevalence thresholds used by different organizations within individual jurisdictions varied substantially. Across jurisdictions, umbrella patient organizations had the highest (most liberal) average prevalence threshold (47 cases/100,000 people), whereas private payers had the lowest threshold (18 cases/100,000 people). Conclusions Despite variation in the terminology and prevalence thresholds used to define rare diseases among different jurisdictions and organizations, the terms "rare disease" and "orphan drug" are used most widely and the average prevalence threshold is between 40 and 50 cases/100,000 people. These findings highlight the existing diversity among definitions of rare diseases, but suggest that any attempts to harmonize rare disease definitions should focus on standardizing objective criteria such as prevalence thresholds and avoid qualitative descriptors. © 2015 International Society for Pharmacoeconomics and Outcomes Research (ISPOR).
Andrews J.C.,Vanderbilt University |
Schunemann H.J.,McMaster University |
Oxman A.D.,Norwegian Knowledge Center for the Health Services |
Pottie K.,University of Ottawa |
And 15 more authors.
Journal of Clinical Epidemiology | Year: 2013
In the GRADE approach, the strength of a recommendation reflects the extent to which we can be confident that the composite desirable effects of a management strategy outweigh the composite undesirable effects. This article addresses GRADE's approach to determining the direction and strength of a recommendation. The GRADE describes the balance of desirable and undesirable outcomes of interest among alternative management strategies depending on four domains, namely estimates of effect for desirable and undesirable outcomes of interest, confidence in the estimates of effect, estimates of values and preferences, and resource use. Ultimately, guideline panels must use judgment in integrating these factors to make a strong or weak recommendation for or against an intervention. © 2013 Published by Elsevier Inc.