PUBLISHER: Bizwit Research & Consulting LLP | PRODUCT CODE: 1389168
PUBLISHER: Bizwit Research & Consulting LLP | PRODUCT CODE: 1389168
Global AI in Medical Coding Market is valued at approximately USD 2.06 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 13.7% over the forecast period 2023-2030. Artificial intelligence (AI) in medical coding refers to the incorporation of AI technology into the process of medical coding. Medical coding is the process of standardizing medical diagnoses, treatments, and services into codes. These codes are necessary for data analysis, billing, and reimbursement in the healthcare sector. AI technologies are being increasingly utilized in medical coding to automate and enhance various aspects of the coding process, leading to increased accuracy, efficiency, and cost-effectiveness. Accordingly, the increase in demand for a standardized language to reduce insurance claim fraud and misinterpretations, and the rising focus on increasing the effectiveness of hospital billing and coding operations are primarily attributed to the global market expansion. Additionally, the rapid penetration of efficient healthcare solutions, coupled with the growing volume of healthcare data is augmenting the growth of the AI in medical coding market during the estimated period.
The rapid shift towards remote work and telehealth services has propelled the demand for these services, allowing remote coders to access and analyze medical records effectively. AI algorithms have been essential in accelerating the coding process, rapidly retrieving pertinent data, and lightening the workload for human programmers. According to Statista, in 2019, the telemedicine sector was estimated to value around USD 49.9 billion around the world. Also, it is anticipated to grow and is expected to reach about USD 277.9 billion by the year 2025. Moreover, the growing advancements in Natural Language Processing (NLP), as well as the rising integration with Electronic Health Records (EHRs) present various lucrative opportunities over the forecasting years. However, the growing inefficiency in medical billing and revenue cycle management, along with increasing privacy concerns are challenging the market growth throughout the forecast period of 2023-2030.
The key regions considered for the Global AI in Medical Coding Market study include Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 owing to the growing burden of chronic diseases in various countries and the expansion of healthcare infrastructure. Also, various key players in the market are increasingly launching innovative solutions and services to maintain a competitive edge further contributing to the regional market expansion. Whereas, Asia Pacific is expected to grow at the highest CAGR over the forecasting years. The regional market is expanding due to increasing expenditures on healthcare, rising initiatives by the government, increased burden of chronic illnesses, and outsourcing opportunities. APAC has developed into a robust market for medical coding because of the increasing emphasis on enhancing healthcare systems, adoption of advanced technologies such as AI, and establishment of new healthcare facilities.
The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.
The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:
List of tables and figures and dummy in nature, final lists may vary in the final deliverable
List of tables and figures and dummy in nature, final lists may vary in the final deliverable