Evidence map›Paper›PMID 30479603›Full record

ArticleEJIFCC2018

Economic Evaluation as a Tool in Emerging Technology Assessment.

Nataša Bogavac-Stanojević

Abstract read
In one paragraph

Article in EJIFCC, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

1 author.

Nataša Bogavac-StanojevićDepartment of Medical Biochemistry, University of Belgrade-Faculty of Pharmacy, Belgrade, Serbia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Medical technologies are part of health technologies and they include medical devices (MD) and in vitro diagnostics (IVD). They have become a vital part of modern healthcare. Framework for introduction of new technology in the healthcare system includes a few steps: analytical and clinical accuracy assessment, clinical utility determination and economic evaluation. In addition, payers are interested whether new technology is adequate for reimbursement. There are fairly enough specific guidelines for implementation of economic methods at the early stage of IVD development. Searching the available literature in this field, this paper discusses the economic evaluations of emerging medical technologies with focus on point of care testing (POCT) and genetic testing. Results of POCT economy studies depend on investigated perspective (payers, policy makers or society), used effectiveness values (utility, effectiveness or consequence estimated as monetary value) and understanding of clinical pathway. There is a need for better understanding of the care pathway, resource utilisation and how they change with the introduction of POCT. Introduction of genetic testing before drug therapy was recommended with the aim to improve treatment benefit and to reduce costs of adverse drug reaction. Clinical utility and cost-effectiveness analyses should be considered for novel genetic testing - guided treatments. Most of the studies considering genetic testing - guided treatments showed that those combinations were cost-saving or cost-effective compared to standard care. For medical tehnology there is no universal guidance for outcomes measurement, cost calculation, performance requirements, use of a certain type of economic studies and economic thresholds.

Indexed as

economic evaluationsgenetic testingin vitro diagnosticspoint of care testing

Identifiers

PMID30479603
PMCPMC6247126

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.