Dublin, Aug. 16, 2023 (GLOBE NEWSWIRE) -- The "AI In Medical Coding Market Size, Share & Trends Analysis Report By Component (In-house, Outsourced), By Region (North America, Europe, APAC, Latin America, MEA), And Segment Forecasts, 2023 - 2030" report has been added to ResearchAndMarkets.com's offering.
The global AI in medical coding market is on the brink of remarkable growth, poised to attain a substantial size of USD 5.71 billion by 2030. The journey toward this achievement is marked by an impressive compound annual growth rate (CAGR) of 13.7% spanning from 2023 to 2030.
A multitude of factors are propelling the expansion of artificial intelligence (AI) in medical coding, prominently including the escalating complexity of healthcare coding processes.
The surge in healthcare data volume has necessitated the incorporation of advanced technologies to streamline and automate coding operations. AI emerges as a powerful solution, adept at analyzing vast datasets, detecting intricate patterns, and precisely assigning codes. This not only enhances operational efficiency but also curbs billing errors, fostering accuracy in the revenue cycle.
The landscape of the AI in medical coding industry has witnessed a profound transformation catalyzed by the COVID-19 pandemic. The elevated influx of healthcare data during the pandemic, coupled with the imperative need for streamlined processes to handle the surge in COVID-19 cases, has led to a swift adoption of AI-powered solutions.
Additionally, the paradigm shift towards remote work and the meteoric rise of telehealth services have further underscored the demand for AI in medical coding. By enabling remote access and analysis of medical records, AI has proven instrumental in accommodating these pandemic-induced changes. The ripple effects of these adaptations are projected to reverberate significantly, fostering robust growth in the years to come.
Automated medical coding offers numerous benefits to healthcare providers, improving efficiency, accuracy, and revenue cycle management. By leveraging artificial intelligence and machine learning algorithms, automated systems can quickly and accurately analyze medical documentation, extract relevant information, and assign appropriate codes. This eliminates the need for manual coding, saving time and reducing the risk of human errors.
Automated systems also enhance compliance with coding guidelines and regulations, reducing the chances of audits and denials. Furthermore, it improves revenue cycle management by accelerating the coding process, optimizing reimbursement, and reducing backlogs. With automated medical coding, healthcare providers can streamline operations, focus on patient care, and achieve better financial outcomes.
Moreover, key players in the market are launching innovative solutions and services to maintain a competitive edge. For instance, in November 2020, Diagnoss introduced an AI assistant to reduce medical coding errors, addressing a critical challenge in healthcare billing processes.
The AI assistant utilizes advanced algorithms to analyze medical documentation, identify potential errors, and provide real-time suggestions for accurate coding. The solution aims to improve accuracy, reduce claim denials, and optimize revenue cycle management. This innovative solution could enhance operational efficiency and financial performance for healthcare providers, ultimately improving patient care and cost savings.
Similarly, in September 2022, AGS Health unveiled an artificial intelligence platform designed for end-to-end revenue cycle management and medical coding. This innovative platform incorporates AI capabilities to optimize various aspects of the revenue cycle, including medical coding, billing, claims management, and reimbursement.
By leveraging advanced algorithms and automation, AGS Health's AI platform aims to enhance operational efficiency, reduce billing errors, accelerate payment cycles, and improve overall revenue performance for healthcare providers. This launch shows the growing adoption of AI in the healthcare industry and its potential to transform medical coding processes.
AI In Medical Coding Market Report Highlights
- Based on component, the outsourced segment accounted for the highest revenue share in 2022. Its revenue share was 66.8% and is expected to grow at the fastest CAGR of 14.5% over the forecast period
- Healthcare providers opt to outsource their medical coding needs to minimize administrative expenses. This approach aids in cost reduction, time savings, and the streamlining of workflows
- North America held the majority share of 31.8% in 2022. Due to technological advancements and improved healthcare infrastructure, the market in North America is projected to have a significant share throughout the forecast period
Competitive Landscape
- Recent Developments And Impact Analysis By Key Market Participants
- Company/competition Categorization (Key Innovators, Market Leaders, And Emerging Players)
- Company Market Position Analysis
- Company Market Share Analysis (%)
Company Profiles
- IBM
- Fathom, Inc.
- Clinion
- BUDDI.AI
- CodaMetrix
- aideo technologies, LLC
- Diagnoss
Key Attributes:
| Report Attribute | Details |
| No. of Pages | 90 |
| Forecast Period | 2022 - 2030 |
| Estimated Market Value (USD) in 2022 | $2.06 billion |
| Forecasted Market Value (USD) by 2030 | $5.71 billion |
| Compound Annual Growth Rate | 13.7% |
| Regions Covered | Global |
Key Topics Covered:
Chapter 1 Methodology and Scope
Chapter 2 Executive Summary
2.1 Artificial Intelligence in Medical Coding Market Outlook
2.2 Artificial Intelligence in Medical Coding Market Segment Outlook
2.3 Artificial Intelligence in Medical Coding Market Competitive Insights
2.4 Artificial Intelligence in Medical Coding Market Snapshot
Chapter 3 Artificial Intelligence in Medical Coding Market Variables, Trends & Scope
3.1 Penetration And Growth Prospect Mapping
3.2 Pricing Analysis
3.3 User Perspective Analysis
3.3.1 Consumer Behavior Analysis
3.3.2 Market Influencer Analysis
3.4 Market Lineage Outlook
3.4.1 Parent Market Outlook
3.4.2 Ancillary Market Outlook
3.5 Regulatory Framework
3.6 Market Dynamics
3.6.1 Market Driver Analysis
3.6.2 Market Restraint Analysis
3.6.3 Industry Challenge
3.7 Artificial Intelligence In Medical Coding Market Analysis Tools
3.7.1 Artificial Intelligence In Medical Coding Market - Porter's Analysis
3.7.2 Pestel Analysis
3.8 Impact Of COVID-19 On Artificial Intelligence In Medical Coding Market
Chapter 4 Artificial Intelligence in Medical Coding Market: Component Estimates & Trend Analysis
4.1 Artificial Intelligence In Medical Coding Market: Component Movement Analysis, 2023 & 2030 (USD Million)
4.2 In-house
4.3 Outsourced
Chapter 5 Artificial Intelligence In Medical Coding Market: Regional Business Analysis
5.1 Regional Market Snapshot
5.1.1 Key Country Dynamics
5.1.2 Regulatory Framework
5.1.3 Reimbursement Scenario
For more information about this report visit https://www.researchandmarkets.com/r/vnbe1t
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