Background: Apps for real-time continuous glucose monitoring (CGM) on smartphones and other devices linked to CGM systems have recently been developed, and such CGM apps are also coming into use in Japan. In comparison with conventional retrospective CGM, the use of CGM apps improves patients' own blood glucose control, which is expected to help slow the progression of type 2 diabetes mellitus (DM) and prevent complications, but the effect of their introduction on medical costs remains unknown.
Objective: Our objective in this study was to perform an economic appraisal of CGM apps from the viewpoint of assessing public medical costs associated with type 2 DM, using the probability of developing type 2 DM-associated complications, and data on medical costs and utility value to carry out a medical cost simulation using a Markov model in order to ascertain the cost-effectiveness of the apps.
Methods: We developed a Markov model with the transition states of insulin therapy, nephrosis, dialysis, and cardiovascular disease, all of which have a major effect on medical costs, to identify changes in medical costs and utility values resulting from the introduction of a CGM app and calculated the incremental cost-effectiveness ratio (ICER).
Results: The ICER for CGM app use was US $33,039/quality-adjusted life year (QALY).
Conclusions: Sensitivity analyses showed that, with the exception of conditions where the transition probability of insulin therapy, utility value, or increased medical costs increases, the ICER for the introduction of CGM apps was below the threshold of US $43,478/QALY used by the Central Social Insurance Medical Council. Our results provide basic data on the cost-effectiveness of introducing CGM apps, which are currently starting to come into use.
Keywords: Markov model; continuous glucose monitoring (CGM); cost-effectiveness; incremental cost and effective ratio (ICER); telehealth; type 2 diabetes mellitus.
©Shintaro Tsuji, Tomoki Ishikawa, Yasuhiro Morii, Hongjian Zhang, Teppei Suzuki, Takumi Tanikawa, Jun Nakaya, Katsuhiko Ogasawara. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 17.09.2020.