Evidence map›Paper›PMID 36073595›Full record

ArticleInternational wound journal2023

Challenges around quantifying uncertainty in a holistic approach to hard-to-heal wound management: Health economic perspective.

Vladica Veličković, Dina Janković

Abstract read
In one paragraph

Article in International wound journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

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

  1. Pooled it
  2. Trial
  3. Article
  4. Harnessing population genetics and animal models to uncover the genetics of skin scarring.Journal of plastic, reconstructive & aesthetic surgery : JPRAS · 2026
    Review
  5. Review
  6. Review
  7. Article
  8. Revisiting Heinz-Lippman disease as a complication of chronic venous insufficiency.Journal of vascular surgery cases and innovative techniques · 2024
    Article
  9. 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

2 authors.

Vladica VeličkovićHealth Economics and Outcome Research, Hartmann Group, Heidenheim, Germany.ORCID https://orcid.org/0000-0001-7146-1267
Dina JankovićCentre for Health Economics, University of York, York, UK.ORCID https://orcid.org/0000-0002-9311-1409

Funding

HARTMANN GROUP Advanced Predictive Analytic (APA) Program
6 · The paper itself

Abstract

Treatment of hard-to-heal wounds involves a holistic approach for choosing between available treatment options. However, evidence for informing these choices is sparse, introducing uncertainty into decisions about the optimum treatment pathways that reflect the vast heterogeneity in this patient population. This paper discusses the existing clinical and health economic literature in order to provide insight into sources of uncertainty in the evaluation of the holistic approach to management of the hard-to-heal wounds, and how this uncertainty can be appropriately reflected in research. We identified three key sources of uncertainty in the evaluation of chronic wound treatments, namely heterogeneity in aetiology and patient populations, heterogeneity in treatment pathways, and challenges around capturing all relevant outcomes. Reflecting these complexities requires sophisticated modelling of treatment sequencing and long-term outcomes. The paper discusses how the scope specification, scenario analyses, and sensitivity analyses can be used to fully characterise analytical uncertainty.

Indexed as

Wound HealingHumansUncertaintychronic woundscost-effectiveness analysiseconomic evaluationuncertaintywound management

Identifiers

PMID36073595
PMCPMC9927906

What OpenQuestion holds

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LicenceCC BY-NC
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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.