Evidence map›Paper›PMID 28864692›Full record

ReviewBMJ open2017

Common evidence gaps in point-of-care diagnostic test evaluation: a review of horizon scan reports.

Jan Y Verbakel, Philip J Turner, Matthew J Thompson, Annette Plüddemann, Christopher P Price, Bethany Shinkins, Ann Van den Bruel

Abstract readReview
In one paragraph

Review in BMJ open, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 4 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

35 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
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  5. Review
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  7. Article
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  9. Implementing in-vitro diagnostic point-of-care tests in community health care: how can we make this work?The British journal of general practice : the journal of the Royal College of General Practitioners · 2025
    Article
  10. Point-of-care tests in the emergency medical services: a scoping review.Scandinavian journal of trauma, resuscitation and emergency medicine · 2025
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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

7 authors.

Jan Y VerbakelNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Philip J TurnerNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Matthew J ThompsonPrimary Care Innovation Lab, Department of Family Medicine, University of Washington, Seattle, Washington, USA.
Annette PlüddemannNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Christopher P PriceNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Bethany ShinkinsTest Evaluation Group, AUHE, Leeds Institute of Health Sciences, University of Leeds, Leeds, UK.
Ann Van den BruelNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveSince 2008, the Oxford Diagnostic Horizon Scan Programme has been identifying and summarising evidence on new and emerging diagnostic technologies relevant to primary care. We used these reports to determine the sequence and timing of evidence for new point-of-care diagnostic tests and to identify common evidence gaps in this process.

designSystematic overview of diagnostic horizon scan reports. PRIMARY OUTCOME MEASURES: We obtained the primary studies referenced in each horizon scan report (n=40) and extracted details of the study size, clinical setting and design characteristics. In particular, we assessed whether each study evaluated test accuracy, test impact or cost-effectiveness. The evidence for each point-of-care test was mapped against the Horvath framework for diagnostic test evaluation.

resultsWe extracted data from 500 primary studies. Most diagnostic technologies underwent clinical performance (ie, ability to detect a clinical condition) assessment (71.2%), with very few progressing to comparative clinical effectiveness (10.0%) and a cost-effectiveness evaluation (8.6%), even in the more established and frequently reported clinical domains, such as cardiovascular disease. The median time to complete an evaluation cycle was 9 years (IQR 5.5-12.5 years). The sequence of evidence generation was typically haphazard and some diagnostic tests appear to be implemented in routine care without completing essential evaluation stages such as clinical effectiveness.

conclusionsEvidence generation for new point-of-care diagnostic tests is slow and tends to focus on accuracy, and overlooks other test attributes such as impact, implementation and cost-effectiveness. Evaluation of this dynamic cycle and feeding back data from clinical effectiveness to refine analytical and clinical performance are key to improve the efficiency of point-of-care diagnostic test development and impact on clinically relevant outcomes. While the 'road map' for the steps needed to generate evidence are reasonably well delineated, we provide evidence on the complexity, length and variability of the actual process that many diagnostic technologies undergo.

Indexed as

Diagnostic Tests, RoutinePoint-of-Care TestingPrimary Health CareTechnology Assessment, BiomedicalHumansDiagnosisevidence based medicineframeworkhorizon scanning reportsPoint-of-care SystemsPRIMARY CARE

Identifiers

PMID28864692
PMCPMC5588931

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.