Evidence map›Paper›PMID 34430138›Full record

ArticleCureus2021

Towards a More Simplified Approach for Evaluating Strength of Evidence in Health Technology Assessments.

Frederick Moore, Betsy H Grunch, Larry E Miller, Michael J Musacchio

Abstract read
In one paragraph

Article in Cureus, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Frederick MooreOrthopedics, Southeast Orthopedic Specialists, Jacksonville, USA.
Betsy H GrunchNeurosurgery, The Longstreet Clinic, Gainesville, USA.
Larry E MillerClinical Research, Miller Scientific, Johnson City, USA.
Michael J MusacchioNeurosurgery, NorthShore Spine Center, Evanston, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is imperative to thoroughly evaluate the safety, effectiveness, and cost-utility of a new medical device prior to the widespread adoption of the technology. Health technology assessment (HTA) is a systematic evaluation of the benefits and harms of a health technology that aims to inform healthcare policy decisions, improve utilization of cost-effective new technologies, and prevent the adoption of devices with harmful or doubtful value for the health system. Even though dozens of organizations perform HTAs, there is no universally accepted criterion for conducting, reporting, and deriving conclusions from an HTA. Thus, there are considerable discrepancies in the methodologies among HTAs such that the same device with the same underlying clinical evidence is often endorsed by one agency but not another, leading to inconsistencies in healthcare coverage policy decisions. Here, we propose a more simplified and unified approach for summarizing clinical effectiveness and safety outcomes for HTAs. We developed a short, semi-quantitative scoring tool that can be used to provide an overall evaluation of evidence strength in HTAs consisting of five categories: (a) the number of randomized controlled trials (RCTs) that have been performed using the technology, (b) the risk of bias among RCTs, (c) the effect size observed for the key effectiveness outcome, (d) the effect size observed for the key safety outcome, and (e) the generalizability of outcomes observed in RCTs to those observed in real-world clinical use. Utilization of this simplified semi-quantitative framework may simplify the HTA process and improve the consistency of the resulting recommendations.

Indexed as

effectivenesshealthcare payerhealth technology assessmenthtamedical devicesafety

Identifiers

PMID34430138
PMCPMC8378323

What OpenQuestion holds

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LicenceCC BY
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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.