Use of Decision Analysis and Economic Evaluation in Breast Reconstruction: A Systematic Review.
Plast Reconstr Surg Glob Open
; 8(4): e2786, 2020 Apr.
Article
em En
| MEDLINE
| ID: mdl-32440446
BACKGROUND: Decision analysis allows clinicians to compare different strategies in the context of uncertainty, through explicit and quantitative measures such as quality of life outcomes and costing data. This is especially important in breast reconstruction, where multiple strategies can be offered to patients. This systematic review aims to appraise and review the different decision analytic models used in breast reconstruction. METHODS: A search of English articles in PubMed, Ovid, and Embase databases was performed. All articles regardless of date of publishing were considered. Two reviewers independently assessed each article, based on strict inclusion criteria. RESULTS: Out of 442 articles identified, 27 fit within the inclusion criteria. These were then grouped according to aspects of breast reconstruction, with implant-based reconstruction (n = 13) being the most commonly reported. Decision analysis (n = 19) and/or economic analyses (n = 27) were employed to discuss reconstructive options. The most common outcome was cost (n = 27). The decision analysis models compared and contrasted surgical strategies, management options, and novel adjuncts. CONCLUSIONS: Decision analysis in breast reconstruction is growing exponentially.The most common model used was a simple decision tree. Models published were of high quality but could be improved with a more in-depth sensitivity analysis. It is essential for surgeons to familiarize themselves with the concept of decision analysis to better tackle complicated decisions, due to its intrinsic advantage of being able to weigh risks and benefits of multiple strategies while using probabilistic models.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Health_economic_evaluation
/
Prognostic_studies
/
Systematic_reviews
Idioma:
En
Revista:
Plast Reconstr Surg Glob Open
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
Canadá