Published in:
Open Access 21-06-2023 | Parkinson's Disease | Systematic Review
Modelling the Cost Effectiveness of Treatments for Parkinson’s Disease: An Updated Methodological Review
Published in: PharmacoEconomics | Issue 10/2023
Login to get accessAbstract
Objective
This article systematically reviewed the methodological quality of modelling approaches for economic evaluations of the treatment of motor symptoms in Parkinson’s disease in studies published after 2010.
Methods
A systematic literature search was undertaken using PubMed, EconLit, the Cochrane Database of Systematic Reviews, National Health Service Economic Evaluation Database and Health Technology Assessment databases of the UK National Health Service Centre for Review and Dissemination (March 2010 to July 2022). Quality was assessed using a checklist from the German Scientific Working Group.
Results
A total of 20 studies were evaluated, with the majority based on Markov models (n = 18). Studies assessed the cost effectiveness of medical (n = 12) or surgical (n = 8) treatment, and included costs from a payer or healthcare provider’s perspective (n = 17). Furthermore, all studies included quality-adjusted life-years as an effect measure. In the quality assessment of the literature, a mean score of 42.1 points (out of 56 points) on the checklist of the German Scientific Working Group was achieved. Seventeen studies concluded the intervention under study was (likely) cost effective. No intervention was classified as cost ineffective.
Conclusions
The quality of economic evaluation models in Parkinson’s disease has improved in terms of calculating cost and transition parameters, as well as carrying out probabilistic sensitivity analyses, compared with the published literature of previous systematic reviews up to 2010. However, there is still potential for further development in terms of the integration of non-motor complications and treatment changes, the transparent presentation of parameter estimates, as well as conducting sensitivity analyses and validations to support the interpretation of results.