Autonomous Medical Coding Market is projected to reach the value of $88 billion by 2030

According to the report published by Virtue Market Research, the Global Autonomous Medical Coding Market was valued at $35.54 billion in 2022 and is projected to reach a market capitalization of $88 billion by 2030. Over the forecast period of 2023-2030, the market is estimated to grow at a CAGR of 12%. Due to the rising use of electronic health records and the demand for effective coding procedures, the market for autonomous medical coding is anticipated to rise at a CAGR. The accuracy and speed of autonomous coding systems are anticipated to be improved by developments in natural language processing and machine learning technologies, further fueling market expansion.

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The healthcare industry is currently facing a significant transformation regarding the usage of sophisticated medical coding systems that utilize artificial intelligence, machine learning, and natural language processing abilities. There is a rising need for more precise and effective medical coding solutions as healthcare firms try to improve revenue cycle management and reduce administrative costs. The complexity of medical coding standards has increased, especially with the adoption of the ICD-10 coding system, which has created the demand for advanced medical coding solutions that might speed up the coding process and reduce errors. Additionally, there is a growing need for sophisticated medical coding technology that can handle huge volumes of clinical data and process it rapidly and effectively due to the rising frequency of chronic diseases and the number of patient visits. Future market expansion for medical coding technology is anticipated to be fueled by these main factors.

The COVID-19 pandemic has had an impact on the healthcare IT sector as healthcare providers look for creative ways to cut costs and improve patient care management. The pandemic has had a favorable effect on the computer-assisted coding (CAC) business, increasing adoption by healthcare facilities all around the world. This has been prompted in part by the necessity to manage the increasing number of confirmed COVID-19 cases, for which the World Health Organization created an emergency ICD-10-CM code in March 2020. The CAC market has now been given the chance to broaden its scope and provide coding solutions for COVID-19-related issues. Additionally, as healthcare providers look to cut down on revenue leakage brought on by incorrect coding, improve efficiency, and meet evolving regulatory requirements, the movement towards automation in medical coding has been gaining traction. The demand for precise and effective coding solutions across a greater range of specializations and healthcare settings is projected to fuel the growth of the market for autonomous coding systems.

Segmentation Analysis:
The global Autonomous Medical Coding Market segmentation includes:
By Mode of Delivery:
• Web & Cloud-based
• On-Premises.

By delivery method, the global autonomous medical coding market is divided into on-premises and online & cloud-based segments. The web-based delivery technique does not require the device to have any software installed because it connects to a distant server using internet protocols. This method of delivery is affordable, needs no internal maintenance, and is simple to access using a web browser. On the other side, cloud-based solutions are becoming more and more popular because they require less internal maintenance and have lower installation costs. The market for autonomous medical coding is expanding as a result of the growing need for accurate and effective medical coding solutions as well as the complexity of medical coding regulations. With the rising frequency of chronic diseases and the increased adoption of automation in the healthcare sector, the market is anticipated to grow even more. In terms of market share, North America now dominates, followed by Europe and the Asia-Pacific area.
By End-User:
• Hospitals
• Clinical Laboratories, and Diagnostics Centre
• Other

Hospitals, clinical laboratories, diagnostics facilities, and other end-users are included in the end-user segments of the global autonomous medical coding market. Health information management and revenue cycle professionals encounter more and more difficulties as the healthcare sector grows, including a lack of skilled coders as a result of senior experts leaving the field, taking medical leave, and changing jobs. The COVID-19 outbreak has also made coding specialists' availability unpredictable. The impetus to address these coding difficulties is increasing as healthcare organizations strive for quicker and higher quality coding outputs to guarantee revenue integrity, lower reimbursement recoupments, and improve bottom lines. A 350-bed hospital's typical revenue cycle is $22 million, or about 3-5 percent of total income. Autonomous medical coding solutions are rising in popularity in the healthcare sector in response to the growing demand to expedite the medical coding process and give a viable answer to the existing coding issues experienced by healthcare providers.

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Regional Analysis:
In North America, the usage of computer-assisted coding and electronic health records (EHR) has expanded as a result of the Health Information Technology for Economic and Clinical Health (HITECH) Act, which was passed in 2009. This law pushed health IT use among medical personnel to increase efficiency. Similarly to this, electronic medical records are used by a substantial percentage of doctors in Canada, improving patient care. The Trump Administration's MyHealthEData Initiative aims to empower patients by giving them access to and control over their medical data. The Centers for Medicare & Medicaid Services (CMS) EHR Incentive Programs are therefore anticipated to be revised. To manage the increased coding effort brought on by the adoption of ICD-10 standards, numerous hospitals in North America are utilizing computer-assisted coding (CAC) systems. Government assistance is therefore likely to persuade healthcare providers to utilize computer-assisted coding and alter how industry players behave. Europe, Asia-Pacific, Latin America, the Middle East, and Africa are all part of the global autonomous medical coding market, and these regions are projected to see comparable trends develop.

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Latest Industry Developments:
• In September 2022, renowned healthcare software provider Alpha II registered with the athenahealth Marketplace program to provide its E&M GenerateTM solution. By providing an automated and audit-ready solution for E&M coding to athenahealth's vast network of healthcare providers, this new integration streamlines a historically subjective procedure. Alpha II hopes to simplify E&M coding and boost provider effectiveness with this agreement.

• In November 2022, A Memorandum of Understanding (MoU) was recently signed by Artificial Medical Intelligence (AMI) and Octopian Global Services to work together on the creation of sophisticated autonomous clinical coding solutions for the Middle East, North Africa, and Asia Pacific regions. Following the agreement, Octopian Digital, a division of Octopian Global Services, will incorporate EMscribe, a platform from AMI, into its automated workflows to assist businesses in boosting productivity and cutting costs. It is anticipated that this collaboration between AMI and Octopian Digital will mark a significant advancement in the creation of autonomous coding solutions in the identified markets.

• In January 2021, the capacity to automatically create an ongoing SOFA score from current clinical documentation in real-time has been unveiled by Artificial Medical Intelligence (AMI) as a breakthrough new feature for its EMscribe® Artificial Intelligence-Computer Assisted Coding (CAC) platform. With the help of this function, medical professionals can evaluate a patient's sickness swiftly and accurately and base choices on the most recent data. The way healthcare providers handle their patients will undoubtedly be revolutionised by this cutting-edge technology.

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This release was published on openPR.