Living systematic reviews: 4. Living guideline recommendations

While it is important for the evidence supporting practice guidelines to be current, that is often not the case. The advent of living systematic reviews has made the concept of "living guidelines" realistic, with the promise to provide timely, up-to-date and high-quality guidance to target users. We define living guidelines as an optimization of the guideline development process to allow updating individual recommendations as soon as new relevant evidence becomes available. A major implication of that definition is that the unit of update is the individual recommendation and not the whole guideline. We then discuss when living guidelines are appropriate, the workflows required to support them, the collaboration between living systematic reviews and living guideline teams, the thresholds for changing recommendations, and potential approaches to publication and dissemination. The success and sustainability of the concept of living guideline will depend on those of its major pillar, the living systematic review. We conclude that guideline developers should both experiment with and research the process of living guidelines

Living systematic reviews:2. Combining human and machine effort

New approaches to evidence synthesis, which utilise human effort and machine automation in mutually reinforcing ways, can enhance the feasibility and sustainability of living systematic reviews. Human effort is a scarce and valuable resource, required when automation is impossible or undesirable, and includes contributions from online communities ('crowds') as well as more conventional contributions from review authors and information specialists. Automation can assist with some systematic review tasks, including searching, eligibility assessment, identification and retrieval of full text reports, extraction of data, and risk of bias assessment. Workflows can be developed in which human effort and machine automation can each enable the other to operate in more effective and efficient ways, offering substantial enhancement to the productivity of systematic reviews. This paper describes and discusses the potential - and limitations - of new ways of undertaking specific tasks in living systematic reviews, identifying areas where these human / machine 'technologies' are already in use, and where further research and development is needed. While the context is living systematic reviews, many of these enabling technologies apply equally to standard approaches to systematic reviewing

Meeting the review family : exploring review types and associated information retrieval requirements

Background and objectives The last decade has witnessed increased recognition of the value of literature reviews for advancing understanding and decision making. This has been accompanied by an expansion in the range of methodological approaches and types of review. However, there remains uncertainty over definitions and search requirements beyond those for the ‘traditional’ systematic review. This study aims to characterise health related reviews by type and to provide recommendations on appropriate methods of information retrieval based on the available guidance. Methods A list of review types was generated from published typologies and categorised into ‘families’ based on their common features. Guidance on information retrieval for each review type was identified by searching pubmed, medline and Google Scholar, supplemented by scrutinising websites of review producing organisations. Results Forty‐eight review types were identified and categorised into seven families. Published guidance reveals increasing specification of methods for information retrieval; however, much of it remains generic with many review types lacking explicit requirements for the identification of evidence. Conclusions Defining review types and utilising appropriate search methods remain challenging. By familiarising themselves with a range of review methodologies and associated search methods, information specialists will be better equipped to select suitable approaches for future projects

Living systematic reviews : 3. Statistical methods for updating meta-analyses

A living systematic review (LSR) should keep the review current as new research evidence emerges. Any meta-analyses included in the review will also need updating as new material is identified. If the aim of the review is solely to present the best current evidence standard meta-analysis may be sufficient, provided reviewers are aware that results may change at later updates. If the review is used in a decision-making context, more caution may be needed. When using standard meta-analysis methods, the chance of incorrectly concluding that any updated meta-analysis is statistically significant when there is no effect (the type I error) increases rapidly as more updates are performed. Inaccurate estimation of any heterogeneity across studies may also lead to inappropriate conclusions. This paper considers four methods to avoid some of these statistical problems when updating meta-analyses: two methods, that is, law of the iterated logarithm and the Shuster method control primarily for inflation of type I error and two other methods, that is, trial sequential analysis and sequential meta-analysis control for type I and II errors (failing to detect a genuine effect) and take account of heterogeneity. This paper compares the methods and considers how they could be applied to LSRs

Living systematic review: 1. Introduction-the why, what, when, and how.

Systematic reviews are difficult to keep up to date, but failure to do so leads to a decay in review currency, accuracy, and utility. We are developing a novel approach to systematic review updating termed "Living systematic review" (LSR): systematic reviews that are continually updated, incorporating relevant new evidence as it becomes available. LSRs may be particularly important in fields where research evidence is emerging rapidly, current evidence is uncertain, and new research may change policy or practice decisions. We hypothesize that a continual approach to updating will achieve greater currency and validity, and increase the benefits to end users, with feasible resource requirements over time