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Report Scope:
In this report, the market has been segmented based on offering, technology, application, and geography. The report provides an overview of the global AI in remote patient monitoring market and analyzes market trends. Using 2021 as the base year, the report provides estimated market data for the forecast period, 2022-2027. Revenue forecasts for this period are segmented based on offering, technology, applications, and geography. Market values have been estimated based on the total revenue of AI in remote patient monitoring application providers.
The report covers the market for AI in remote patient monitoring with regard to the user base, across different regions. It also highlights major trends and challenges that affect the market and the vendor landscape. The report estimates the global market for AI in remote patient monitoring in 2021 and provides projections for the expected market size through 2027.
The scope of the study includes the AI in remote patient monitoring care platform and associated services.
Report Includes:
- A brief general outlook of the global market for AI in remote patient monitoring (RPM)
- Analyses of the global market trends, with market revenue/sales data for 2021, estimates for 2022, forecasts for 2023 and 2025, and projections of compound annual growth rates (CAGRs) through 2027
- Understanding of the upcoming market potential for AI in remote monitoring solutions with an emphasis on new products and technologies, and areas of focus to forecast this market into various segments and sub-segments
- Estimation of the actual market size and revenue forecast for AI remote patient monitoring market, and corresponding market share analysis based on offering, technology, application and region
- In-depth information (facts and figures) concerning major market dynamics, technology adaptations in digital health solutions, latest developments, govt. regulations, and macroeconomic forces affecting the global AI in RPM market outlook
- Company profiles of the major industry players, and their offerings (of relevant products and solutions) and the recent industry developments
Summary:
AI and remote patient monitoring are powerful tools for providing insight into the factors that impact an individual's health on a day-to-day basis. Remote patient monitoring program implementation can be made more successful by leveraging AI before it even begins. Using advanced algorithms, one can gain a more holistic understanding of an individual by analyzing large data sets such as clinical, socioeconomic, and experiential data. In addition to identifying risk levels, stratification can be used to determine which individuals would benefit most from remote patient monitoring.
Factors such as the growing population of geriatrics, an increasing prevalence of chronic diseases, a global shortage of healthcare professionals, technological advancements in telehealth and remote patient monitoring, and a growing awareness of the benefits of remote patient monitoring are significantly driving this market's growth. Some patients have concerns pertaining to data accuracy and are hesitant to use remote monitoring technologies. However, it is predicted that the market will grow significantly over the next few years as artificial intelligence (AI) is adopted in RPM and emerging economies with a large patient population. However, factors such as data security, privacy concerns, and increased overheads associated with employing an additional workforce for the RPM system may hinder companies from entering this market.
In remote patient monitoring, AI is in high demand due to its critical role in monitoring patients with diseases prone to fatal adverse events. The use of telehealth in remote monitoring has increasingly benefitted patients with neurological and cardiovascular diseases. This preference will continue in the future since reducing morbidity and mortality from these diseases is a pressing need.
In this report, the global market for AI in remote patient monitoring (RPM) has been segmented based on offering, technology, application, and geography. Based on offering, the AI in RPM market has been categorized into solutions and services. Based on technology, the AI in RPM market has been segmented into machine learning (ML), NLP, and others.
By geography, the AI in RPM market has been segmented into North America, Europe, Asia-Pacific, and RoW. The North America region is currently the most dominant market for global AI in the remote patient monitoring market. Smartphone adoption, network advancements, and internet and social media penetration drive the market. The growth of mHealth apps and extensive R&D in health wearables drive the demand for AI-based RPM solutions in the North America region. Due to advancements in telehealth and telemedicine, the Asia-Pacific region grows with the highest CAGR for AI in remote patient monitoring.