Healthcare IoT - Lithuania

Usage of Internet of Things (IoT) technologies has especially been beneficial during the COVID-19 pandemic when the need for telehealth as well as home care have been introduced to minimize hospital and clinic visits. The IoT devices made remote monitoring in healthcare possible, resulting in reduced length of hospital stays and decreased need of re-admission.

One of the key drivers of Healthcare IoT growth is the increasing prevalence of chronic diseases, which require ongoing monitoring and management. IoT connected medical devices and remote monitoring systems can help to improve patient outcomes by enabling continuous monitoring of vital signs and other health data. The ageing population in developed countries is adding additional pressure on the healthcare systems which drives the investment in research by both private companies and governments.

Another driver of Healthcare IoT growth is the increasing focus on patient-centered care. Patients are becoming more active in managing their own health, and IoT devices can help to facilitate this by providing patients with real-time data on their health status and enabling them to track their progress towards health goals.

Data coverage

The data encompasses B2B, B2C and B2G revenues. The revenue only refers to the spending share of the Internet of Things components.

Modeling approach/ Market size:

The segment size is determined through a combination of top-down and bottom-up approaches. We use annual financial reports of the market-leading companies and industry associations, as well as third-party studies and reports to analyze the markets. To estimate the market size for each country individually, we use relevant key market indicators and data from country-specific industry associations, such as consumer spending, internet penetration, 4G coverage, and current and historical developments. This data helps us estimate the market size for each country individually.

Forecasts:

In our forecasts, we apply diverse forecasting techniques but primarily exponential smoothing. The selection of forecasting techniques is based on the behavior of the relevant market. The main drivers are the GDP and the level of digitization.

Additional notes:

The data is modeled using current exchange rates. The market is updated twice a year in case market dynamics change.