Objective Physiotherapy (PT), which is an effective strategy for managing Parkinson’s disease (PD), can influence health care utilization. We analyzed trends in health care utilization, PT interventions, and medical costs among patients with PD.
Methods Using data from the Korean National Health Insurance Service from 2011 to 2020, we analyzed the number of patients with PD and their health care utilization and assessed the odds ratio (OR) for receiving regular PTs.
Results Over 10 years, 169,613 patients with PD were included in the analysis. The number of patients with PD increased annually from 49,417 in 2011 to 91,841 in 2020. The number of patients with PD receiving PT increased from 4,847 (9.81%) in 2011 to 13,163 (14.33%) in 2020, and the number of PT prescriptions increased from 81,220 in 2011 to 377,651 in 2019. Medical costs per patient with PD increased from 1,686 United States dollars (USD) in 2011 to 3,202 USD in 2020. The medical expenses for each patient with PD receiving PT increased from 6,582 USD in 2011 to 13,475 USD in 2020. Moreover, regular PTs were administered to 31,782 patients (18.74%) and were administered only through hospitalization. Those patients in their 50s with disabilities demonstrated a high OR for regular PTs, whereas those aged 80 years or older and residing outside of Seoul had a low OR.
Conclusion The PD burden increased in South Korea between 2011 and 2020, as did health care utilization and medical costs. A significant increase in medical expenses can be associated with increased PD incidence and PT interventions. Regular PT applications remain restricted and have barriers to access.
Citations
Citations to this article as recorded by
Clinical efficacy of a non-immersive virtual reality-based balance training device in improving balance and gait in Parkinson's disease; A randomized controlled trial Soohyun Lim, Jinse Park, Juhee Kim, Sang-Myung Cheon, Bong Kyun Kim, Jimin Choi Parkinsonism & Related Disorders.2026; 146: 108270. CrossRef
Global, regional, and national burden of Early-onset Parkinson’s disease: A comprehensive analysis and forecast, 1990–2021 Qing Shen, Fengrui Zheng, Yun Dong, Hongping Yang, Jie Zhu, Shun Chen, Zujuan Shan Neurological Sciences.2026;[Epub] CrossRef
AI FRAMEWORK FOR PREDICTING PHYSIOLOGICAL INDICATORS FROM HIGH-RESOLUTION IRIS IMAGES IN PARKINSON’S DISEASE PATIENTS HAKWON KIM, JEONG-WOO SEO, SEONG-IL PARK, JUNYOUNG HUR, MISO S. PARK, HORYONG YOO Journal of Mechanics in Medicine and Biology.2025;[Epub] CrossRef