The 2020 UHMLG Spring Forum is focusing on getting involved with systematic reviews. With six presentations, it promises to be an interesting and informative day. With the opportunity to network with colleagues from across the HE and NHS sectors, it’s a great value event for all health and medical librarians.
UPDATE: Unfortunately Lynda and Paul are unable to deliver their presentation in the online version of our conference. We regret that this presentation has therefore been withdrawn from the Spring Forum.
Details of the filters that would have been highlighted in the presentation are included below.
Improving information support processes for systematic reviews at NICE
The purpose of this session is to share examples of project work conducted at NICE to improve information support for systematic reviews. The session will discuss the challenges of adopting new processes and consider how we might prepare for future developments. We will cover the following:
- Search filter development to improve the effectiveness and efficiency of systematic literature searches
- Screening the results of literature searches to support the evidence selection process
- Incorporating text mining technologies into search development and screening
- Practical tips for conducting research projects to improve information support for systematic reviews
Search filter development at the National Institute for Health and Care Excellence (NICE)
The National Institute for Health and Care Excellence (NICE) provides national guidance and advice to improve health and social care. NICE information specialists have developed and validated search filters for MEDLINE and Embase (Ovid) to improve the effectiveness of literature searches for NICE guidance. Search filters are different to search strategies because their retrieval performance has been tested (validated). This means that users have an understanding about how well the filters work for retrieving the type of evidence that they require.
The NICE filters can be used by anyone who requires them for similar literature search topics. Please contact Lynda Ayiku if you have any queries about the NICE search filters: email@example.com .
Filter topic 1: Geographic filters
Introduction: Some research topics are context-sensitive and require evidence that is about a specific geographic region such as a country or a continent. Geographic filters are applied to literature searches with the aim of retrieving geographic-specific evidence.
NICE UK filters
The NICE UK filters retrieve evidence about the UK with high recall and high precision. The filters are openly available to users in Word documents via the ‘Geographic filters’ page of the InterTASC Information Specialists’ Sub-Group (ISSG) Search Filter Resource. Detailed information about their development, validation and evaluation can be found in the references below:
- Ayiku L, Levay P, Hudson T et al. (2017) The MEDLINE UK filter: development and validation of a geographic search filter to retrieve research about the UK from OVID MEDLINE. Health Information and Libraries Journal 34 (3): 200-216.
- Ayiku L, Levay P, Hudson T et al. (2019) The Embase UK filter: validation of a geographic search filter to retrieve research about the UK from OVID Embase. Health Information and Libraries Journal 36 (2): 121-133.
- Ayiku L & Finnegan A. (2019) OP23 Smart Searches For Context-Sensitive Topics: Geographic Search Filters. International Journal of Technology Assessment in Health Care. 35 (S1): 5
Methodological advice for developing validated geographic search filters
There are currently only 3 validated sets of geographic filters for the UK, Africa and Spain. We have written a journal paper to (a) increase awareness and use of the existing filters and (b) provide methodological advice on developing validated geographic filters to encourage the creation of new filters for more places in the world:
- Ayiku L, Craven J, Hudson T, et al. (2020) How to develop a validated geographic search filter: Five key steps. Evidence Based Library and Information Practice 15 (1): 170-178.
Filter topic 2: Digital health apps
Introduction: NICE has started to produce guidance and advice on digital interventions including health apps. Health apps are software programmes for preventing, diagnosing and managing conditions. They can be accessed via mobile devices such as smartphones as well as via the web on desktop computers.
NICE health apps search filters
The NICE health apps search filters retrieve evidence about apps with high recall. A forthcoming journal paper about their development and validation is currently in peer review. However, we can share the filters plus details of their development and validation on request.
Two new filters are currently being developed at NICE. These filters will be made available when they are complete:
- NICE health economics filters – study-design filters that aim to retrieve evidence on cost-utilities
- NICE OECD countries filters – geographic filters that aim to retrieve evidence about Organisation for Economic Co-operation and Development (OECD) member countries
Lynda is an information specialist at NICE. She conducts expert searches for a range of NICE guidance products including; guidelines, medical technologies guidance, diagnostics guidance, evidence summaries and technology appraisals. Lynda has a research interest in search filter development to improve searching practice. She was the project lead for the NICE UK geographic search filters (MEDLINE and Embase, OVID). Lynda is currently leading another project to create a new filter for the retrieval of evidence on digital health apps.
Paul is an information specialist at NICE. Paul’s role focuses on supporting technology appraisals and providing expert searches for guidelines on public health topics. His research interests include making searches more efficient and assessing the contribution of different databases to systematic reviews on a range of topics. Paul has previously worked in libraries providing criminal justice and environmental information to government bodies. Paul is the joint editor, with Jenny Craven, of “Systematic Searching: Practical Ideas for Improving Results”, published by Facet in 2019.