A Systematic Review of Model-Based Economic Evaluations of Treatments for Venous Leg Ulcers

Ashley Layer, Emma McManus () and N. J. Levell
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Ashley Layer: University of East Anglia
Emma McManus: University of East Anglia
N. J. Levell: Norfolk and Norwich University Hospitals NHS Foundation Trust

PharmacoEconomics - Open, 2020, vol. 4, issue 2, No 3, 222 pages

Abstract: Abstract Objective The aim of this review was to identify, and assess the quality of, published model-based economic evaluations relating to treatments for patients with venous leg ulcers to help inform future decision-analytic models in this clinical area. Methods A systematic literature search was performed on six electronic databases, from database inception until 21 May 2018. Search results were screened against predefined criteria by two independent reviewers. Data was then extracted from the included studies using a standardised form, whilst the decision-analytic model-specific Philips Checklist was used to assess quality and to inform model critique. Results A total of 23 models were identified, 12 studies used a Markov modelling approach, five used decision trees and six studies did not detail the model type. Studies were predominantly from the National Health Service (NHS)/payer perspective, with only two taking a societal perspective. Interventions were wide ranging, but dressing technologies (11/23) were most common. The intervention studied was found to be dominant in 22/23 studies. The reporting quality of papers was mostly low, with evidence behind model structures, time horizons and data selection consistently underreported across the included papers. Conclusions This review has identified a sizeable literature of model-based economic evaluations, evaluating treatments for venous leg ulcers. However, the methods used to conduct such studies were generally poorly reported. In particular, the reporting of evidence surrounding the model structure, justification of the time horizon used and the rationale for selecting data inputs should be focused on in any future models developed.

Date: 2020
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DOI: 10.1007/s41669-019-0148-x

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