Evidence map›Paper›PMID 27561872›Full record

ArticleBMC medical research methodology2016

The use of rapid review methods in health technology assessments: 3 case studies.

Eva Kaltenthaler, Katy Cooper, Abdullah Pandor, Marrissa Martyn-St James, Robin Chatters, Ruth Wong

Abstract read
In one paragraph

Article in BMC medical research methodology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Rapid literature review: definition and methodology.Journal of market access & health policy · 2023
    Review
  4. Toward an inclusive digital health system for sexual and gender minorities in Canada.Journal of the American Medical Informatics Association : JAMIA · 2022
    Article
  5. Review
  6. Article
  7. A rapid review of gender, sex, and sexual orientation documentation in electronic health records.Journal of the American Medical Informatics Association : JAMIA · 2020
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Eva KaltenthalerSchool of Health and Related Research (ScHARR), University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK. e.kaltenthaler@sheffield.ac.uk.ORCID 0000-0002-6185-8321
Katy CooperSchool of Health and Related Research (ScHARR), University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK.
Abdullah PandorSchool of Health and Related Research (ScHARR), University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK.
Marrissa Martyn-St JamesSchool of Health and Related Research (ScHARR), University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK.
Robin ChattersSchool of Health and Related Research (ScHARR), University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK.
Ruth WongSchool of Health and Related Research (ScHARR), University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRapid reviews are of increasing importance within health technology assessment due to time and resource constraints. There are many rapid review methods available although there is little guidance as to the most suitable methods. We present three case studies employing differing methods to suit the evidence base for each review and outline some issues to consider when selecting an appropriate method.

methodsThree recently completed systematic review short reports produced for the UK National Institute for Health Research were examined. Different approaches to rapid review methods were used in the three reports which were undertaken to inform the commissioning of services within the NHS and to inform future trial design. We describe the methods used, the reasoning behind the choice of methods and explore the strengths and weaknesses of each method.

resultsRapid review methods were chosen to meet the needs of the review and each review had distinctly different challenges such as heterogeneity in terms of populations, interventions, comparators and outcome measures (PICO) and/or large numbers of relevant trials. All reviews included at least 10 randomised controlled trials (RCTs), each with numerous included outcomes. For the first case study (sexual health interventions), very diverse studies in terms of PICO were included. P-values and summary information only were presented due to substantial heterogeneity between studies and outcomes measured. For the second case study (premature ejaculation treatments), there were over 100 RCTs but also several existing systematic reviews. Data for meta-analyses were extracted directly from existing systematic reviews with new RCT data added where available. For the final case study (cannabis cessation therapies), studies included a wide range of interventions and considerable variation in study populations and outcomes. A brief summary of the key findings for each study was presented and narrative synthesis used to summarise results for each pair of interventions compared.

conclusionsRapid review methods need to be chosen to meet both the nature of the evidence base of a review and the challenges presented by the included studies. Appropriate methods should be chosen after an assessment of the evidence base.

Indexed as

Meta-Analysis as TopicHumansRandomized Controlled Trials as TopicReview Literature as TopicHealth technology assessmentRapid review methodsSystematic review

Identifiers

PMID27561872
PMCPMC5000433

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.