Development of a best practice statement on the use of ankle-foot orthoses following stroke in Scotland

A National Health Service Quality Improvement Scotland (NHS QIS) scoping exercise in 2007 identified the use of ankle-foot orthoses (AFOs) following stroke as a clinical improvement priority, leading to the development of a best practice statement (BPS) on AFO use after stroke. This paper outlines the development process of the BPS which is available from NHS QIS. The authors were involved in the development of the BPS as part of a working group that included practitioners from the fields of orthotics, physiotherapy, stroke nursing and bioengineering, and staff of NHS QIS and a patient representative. In consultation with an NHS QIS health services researcher, the authors undertook a systematic literature review to evidence where possible the recommendations made in the BPS. Where evidence was unavailable, consensus was reached by the expert working group. As the BPS was designed for the non-specialist and non-orthotic practitioner the authors also developed educational resources which were included within the BPS to aid the understanding of the principles underpinning orthotic design and prescription. The BPS has been widely distributed throughout the health service in Scotland and is available electronically at no cost via the NHS QIS website. At part of an ongoing evaluation of the impact of the BPS on the quality of orthotic provision, NHS QIS has invited feedback regarding successes and challenges to implementation

Risk of bias: a simulation study of power to detect study-level moderator effects in meta-analysis.

There are both theoretical and empirical reasons to believe that design and execution factors are associated with bias in controlled trials. Statistically significant moderator effects, such as the effect of trial quality on treatment effect sizes, are rarely detected in individual meta-analyses, and evidence from meta-epidemiological datasets is inconsistent. The reasons for the disconnect between theory and empirical observation are unclear. The study objective was to explore the power to detect study level moderator effects in meta-analyses. We generated meta-analyses using Monte-Carlo simulations and investigated the effect of number of trials, trial sample size, moderator effect size, heterogeneity, and moderator distribution on power to detect moderator effects. The simulations provide a reference guide for investigators to estimate power when planning meta-regressions. The power to detect moderator effects in meta-analyses, for example, effects of study quality on effect sizes, is largely determined by the degree of residual heterogeneity present in the dataset (noise not explained by the moderator). Larger trial sample sizes increase power only when residual heterogeneity is low. A large number of trials or low residual heterogeneity are necessary to detect effects. When the proportion of the moderator is not equal (for example, 25% 'high quality', 75% 'low quality' trials), power of 80% was rarely achieved in investigated scenarios. Application to an empirical meta-epidemiological dataset with substantial heterogeneity (I(2) = 92%, τ(2) = 0.285) estimated >200 trials are needed for a power of 80% to show a statistically significant result, even for a substantial moderator effect (0.2), and the number of trials with the less common feature (for example, few 'high quality' studies) affects power extensively. Although study characteristics, such as trial quality, may explain some proportion of heterogeneity across study results in meta-analyses, residual heterogeneity is a crucial factor in determining when associations between moderator variables and effect sizes can be statistically detected. Detecting moderator effects requires more powerful analyses than are employed in most published investigations; hence negative findings should not be considered evidence of a lack of effect, and investigations are not hypothesis-proving unless power calculations show sufficient ability to detect effects

The effectiveness of computerized order entry at reducing preventable adverse drug events and medication errors in hospital settings: A systematic review and meta-analysis

Background: The Health Information Technology for Economic and Clinical Health (HITECH) Act subsidizes implementation by hospitals of electronic health records with computerized provider order entry (CPOE), which may reduce patient injuries caused by medication errors (preventable adverse drug events, pADEs). Effects on pADEs have not been rigorously quantified, and effects on medication errors have been variable. The objectives of this analysis were to assess the effectiveness of CPOE at reducing pADEs in hospital-related settings, and examine reasons for heterogeneous effects on medication errors. Methods: Articles were identified using MEDLINE, Cochrane Library, Econlit, web-based databases, and bibliographies of previous systematic reviews (September 2013). Eligible studies compared CPOE with paper-order entry in acute care hospitals, and examined diverse pADEs or medication errors. Studies on children or with limited event-detection methods were excluded. Two investigators extracted data on events and factors potentially associated with effectiveness. We used random effects models to pool data. Results: Sixteen studies addressing medication errors met pooling criteria; six also addressed pADEs. Thirteen studies used pre-post designs. Compared with paper-order entry, CPOE was associated with half as many pADEs (pooled risk ratio (RR) = 0.47, 95% CI 0.31 to 0.71) and medication errors (RR = 0.46, 95% CI 0.35 to 0.60). Regarding reasons for heterogeneous effects on medication errors, five intervention factors and two contextual factors were sufficiently reported to support subgroup analyses or meta-regression. Differences between commercial versus homegrown systems, presence and sophistication of clinical decision support, hospital-wide versus limited implementation, and US versus non-US studies were not significant, nor was timing of publication. Higher baseline rates of medication errors predicted greater reductions (P < 0.001). Other context and implementation variables were seldom reported. Conclusions: In hospital-related settings, implementing CPOE is associated with a greater than 50% decline in pADEs, although the studies used weak designs. Decreases in medication errors are similar and robust to variations in important aspects of intervention design and context. This suggests that CPOE implementation, as subsidized under the HITECH Act, may benefit public health. More detailed reporting of the context and process of implementation could shed light on factors associated with greater effectiveness

The attrition rate of licensed chiropractors in California: an exploratory ecological investigation of time-trend data

<p>Abstract</p> <p>Background</p> <p>The authors hypothesized the attrition rate of licensed chiropractors in California has gradually increased over the past several decades. "Attrition" as determined for this study is defined as a loss of legal authority to practice chiropractic for any reason during the first 10 years after the license was issued. The percentage of license attrition after 10 years was determined for each group of graduates licensed in California each year between 1970 and 1998. The cost of tuition, the increase in the supply of licensed chiropractors and the ratio of licensed chiropractors to California residents were examined as possible influences on the rate of license attrition.</p> <p>Methods</p> <p>The attrition rate was determined by a retrospective analysis of license status data obtained from the California Department of Consumer Affairs. Other variables were determined from US Bureau of Census data, survey data from the American Chiropractic Association and catalogs from a US chiropractic college.</p> <p>Results</p> <p>The 10-year attrition rate rose from 10% for those graduates licensed in 1970 to a peak of 27.8% in 1991. The 10-year attrition rate has since remained between 20-25% for the doctors licensed between 1992-1998.</p> <p>Conclusions</p> <p>Available evidence supports the hypothesis that the attrition rate for licensed chiropractors in the first 10 years of practice has risen in the past several decades.</p

Improving the use of research evidence in guideline development: 5. Group processes

BACKGROUND: The World Health Organization (WHO), like many other organisations around the world, has recognised the need to use more rigorous processes to ensure that health care recommendations are informed by the best available research evidence. This is the fifth of a series of 16 reviews that have been prepared as background for advice from the WHO Advisory Committee on Health Research to WHO on how to achieve this. OBJECTIVE: In this review we address approaches to facilitate sound processes within groups that develop recommendations for health care. METHODS: We searched PubMed and three databases of methodological studies for existing systematic reviews and relevant methodological research. We did not conduct systematic reviews ourselves. Our conclusions are based on the available evidence, consideration of what WHO and other organisations are doing and logical arguments. KEY QUESTION AND ANSWER: What should WHO do to ensure appropriate group processes? Various strategies can be adopted to ensure that the group processes in play when panels are developing recommendations are inclusive, so that all voices can be heard and all arguments given fair weight, including • the use of formal consensus development methods, such at the Nominal Group Technique or the Delphi method • the selection of a group leader who is qualified and responsible for facilitating an appropriate group process

Identifying null meta-analyses that are ripe for updating

BACKGROUND: As an increasingly large number of meta-analyses are published, quantitative methods are needed to help clinicians and systematic review teams determine when meta-analyses are not up to date. METHODS: We propose new methods for determining when non-significant meta-analytic results might be overturned, based on a prediction of the number of participants required in new studies. To guide decision making, we introduce the "new participant ratio", the ratio of the actual number of participants in new studies to the predicted number required to obtain statistical significance. A simulation study was conducted to study the performance of our methods and a real meta-analysis provides further evidence. RESULTS: In our three simulation configurations, our diagnostic test for determining whether a meta-analysis is out of date had sensitivity of 55%, 62%, and 49% with corresponding specificity of 85%, 80%, and 90% respectively. CONCLUSIONS: Simulations suggest that our methods are able to detect out-of-date meta-analyses. These quick and approximate methods show promise for use by systematic review teams to help decide whether to commit the considerable resources required to update a meta-analysis. Further investigation and evaluation of the methods is required before they can be recommended for general use