Feasibility and impact of providing feedback to vaccinating medical clinics: evaluating a public health intervention

<p>Abstract</p> <p>Background</p> <p>Vaccine coverage (VC) at a given age is a widely-used indicator for measuring the performance of vaccination programs. However, there is increasing data suggesting that measuring delays in administering vaccines complements the measure of VC. Providing feedback to vaccinators is recognized as an effective strategy for improving vaccine coverage, but its implementation has not been widely documented in Canada. The objective of this study was to evaluate the feasibility of providing personalized feedback to vaccinators and its impact on vaccination delays (VD).</p> <p>Methods</p> <p>In April and May 2008, a one-hour personalized feedback session was provided to health professionals in vaccinating medical clinics in the Quebec City region. VD for vaccines administered at two and twelve months of age were presented. Data from the regional vaccination registry were analysed for participating clinics. Two 12-month periods before and after the intervention were compared, namely from April 1^st, 2007 to March 31^st, 2008 and from June 1^st, 2008 to May 31^st, 2009.</p> <p>Results</p> <p>Ten medical clinics out of the twelve approached (83%), representing more than 2500 vaccinated children, participated in the project. Preparing and conducting the feedback involved 20 hours of work and expenses of $1000 per clinic. Based on a delay of one month, 94% of first doses of DTaP-Polio-Hib and 77% of meningococcal vaccine doses respected the vaccination schedule both before and after the intervention. Following the feedback, respect of the vaccination schedule increased for vaccines planned at 12 months for the four clinics that had modified their vaccination practices related to multiple injections (depending on the clinic, VD decreased by 24.4%, 32.0%, 40.2% and 44.6% respectively, p < 0.001 for all comparisons).</p> <p>Conclusions</p> <p>The present study shows that it is feasible to provide personalized feedback to vaccinating clinics. While it may have encouraged positive changes in practice concerning multiple injections, this intervention on its own did not impact vaccination delays of the clinics visited. It is possible that feedback integrated into other types of effective interventions and sustained over time may have more impact on VD.</p

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research