A comprehensive model for measuring real‐life cost‐effectiveness in eyecare: automation in care and evaluation of system (aces‐rwm™). Issue 3 (14th July 2021)

• Record Type: Journal Article
• Authors: Tuulonen, Anja; Kataja, Marko; Aaltonen, Vesa; Kinnunen, Kati; Moilanen, Jukka; Saarela, Ville; Linna, Miika; Malmivaara, Antti; Uusitalo‐Jarvinen, Hannele
• Is Part Of: Acta ophthalmologica. Volume 100:Issue 3(2022)
• Page Start: e833
• Page End: e840
• Publication Date: 2021-07-14
• Subjects: age‐related macular degeneration -- cataract -- diabetic retinopathy -- ecosystem -- glaucoma -- real‐world cost‐effectiveness -- real‐world data; Ophthalmology -- Periodicals; 617.7005
• DOI: 10.1111/aos.14959
• Languages: English
• ISSNs: 1755-375X

Abstract

Abstract: This paper describes a holistic, yet simple and comprehensible, ecosystem model to deal with multiple and complex challenges in eyecare. It aims at producing the best possible wellbeing and eyesight with the available resources. When targeting to improve the real‐world cost‐effectiveness, what gets done in everyday practice needs be measured routinely, efficiently and unselectively. Collection of all real‐world data of all patients will enable evaluation and comparison of eyecare systems and departments between themselves nationally and internationally. The concept advocates a strategy to optimize real‐life effectiveness, sustainability and outcomes of the service delivery in ophthalmology. The model consists of three components: (1) resource‐governing principles (i.e., to deal with increasing demand and limited resources), (2) real‐world monitoring (i.e., to collect structured real‐world data utilizing automation and visualization of clinical parameters, health‐related quality of life and costs), and (3) digital innovation strategy (i.e., to evaluate and benchmark real‐world outcomes and cost‐effectiveness). The core value and strength of the model lies in the consensus and collaboration of all Finnish university eye clinics to collect and evaluate the uniformly structured real‐world outcomes data. In addition to ophthalmology, the approach is adaptable to any medical discipline to efficiently generate real‐world insights and resilience in health systems.