Clinical Documentation Improvement Enhances Medical Coding to Maximize Revenue Capture
Whether a patient has a routine physical exam or arrives by ambulance at an emergency department, clinical documentation is pivotal to the patient’s outcome and the healthcare organization’s financial health.
Complete and accurate documentation of a patient’s history, condition, needed tests, diagnosis, and treatment plan in the medical record improves collaboration among clinicians involved in the patient’s care. Clinical documentation also forms the foundation for the next step in a healthcare organization’s revenue cycle: coding for medical claims and billing.
The close connection between documentation, coding, and reimbursement explains why healthcare organizations today focus on clinical documentation improvement (CDI) to increase coding accuracy and improve revenue cycle management.
In our experience working with healthcare organizations nationwide, integrated CDI and coding initiatives can unlock unrealized revenue – up to $4,900 per corrected inpatient claim, according to the 2024 MDaudit Benchmark Report.
Moreover, CDI programs today mesh the strengths of human knowledge and experience with technology-driven efficiency and innovation. New technologies like artificial intelligence (AI) and machine learning can take CDI to the next level.
The Strategic and Financial Value of CDI
Healthcare organizations are grappling with evolving care and reimbursement models. They are under pressure from payers to lower costs and improve patient outcomes. Investing in CDI can offer healthcare organizations a strategic and financial advantage by helping them:
- Maximize reimbursement from public and private payers
- Reduce and combat denials
- Helps to ensure compliance with medical coding rules, laws and guidelines
- Meet or exceed outcomes goals embedded in value-based contracts
Improved Reimbursement: Capturing the Full Story
When clinical documentation is accurate and comprehensive, coders can capture the full complexity of each patient encounter, ensuring healthcare organizations receive appropriate reimbursement for their services.
For example, if documentation is incomplete, coders may miss capturing conditions for patients with multiple chronic diseases. This can result in under-reimbursement. CDI can help accurately capture these conditions, mitigating the financial losses from under-coding.
Executed correctly, CDI helps organizations emphasize the importance of accuracy at every documentation touchpoint. This precision translates into increased revenue capture while reducing the likelihood of audits and penalties for over-coding.
How significant is the problem? A report estimates that healthcare clinicians lose 1% to 3% of net revenue annually due to claims underpayments.
CDI initiatives can help. We worked with a network of academic medical centers and teaching hospitals spanning 14 locations. They established clinician-level benchmarks on coding patterns and ICD-10 capture rates and compared those to national benchmarks. They also created a reporting and governance mechanism for evaluating individual clinician performance.
The results showed a 3.38% improvement in work revenue value units (RVUs) and a $3.2 revenue correction per patient visit. We ensured documentation gap closures, thus improving coding compliance.
Reduced Claim Denials
A national rise in claims denial rates increasingly affects healthcare clinicians. According to the Optum 2024 Revenue Cycle Denial Index, denial rates increased from 9% in 2016 to 12% in 2023. Of all denials, 84% are potentially avoidable, the Optum report said.
Clinicians pay the costs of denials at both ends through reduced revenue and increased administrative costs. In 2022, healthcare organizations spent nearly $20 billion fighting denied claims.
Coding errors lead to reworked claims, with an average administrative cost of $118 to $136 per denied claim. The 2024 MDaudit Benchmark Report put the total “at-risk” revenue due to coding inaccuracies reached $11.2 million per healthcare organization.
On average, 42% of all denials are linked to coding errors, according to a 2022 survey. Identifying and resolving coding errors and issues requires significant staff time. CDI addresses the issue before claims submission and mitigates denial rates by:
- Bridging communication gaps between clinical teams and coders
- Prioritizing accuracy and completeness
- Documenting the medical necessity for high-cost services or procedures
Accelerated Value-Based Care Success
Value-based care programs represent a profound shift in medicine. They prioritize patient outcomes and cost efficiency over volume of services, creating higher standards for documentation for:
- Clinicians who enter information into electronic health records (EHRs)
- CDI specialists who review the information and provide the next level of scrutiny
- Coders who translate clinical documentation into claims submissions
Clinicians in value-based contracts use advanced data analytics to identify at-risk patients and address chronic health conditions such as kidney disease, diabetes, and heart disease sooner when they are easier (and less costly) to treat.
Specifically, healthcare organizations identify and document hierarchical category codes (HCCs) that map to various acute and chronic patient conditions to maximize revenue. Insurers, including Medicare, use HCC codes to assign patients a risk adjustment factor (RAF). HCCs and RAFs have a direct effect on the reimbursement clinicians can expect.
IKS Health analyzed over 125,000 charts through a Clinical Chart Review across four healthcare organizations. Our clinicians conducted a detailed analysis of the last two years of patient records to capture previously undiagnosed HCC eligible chronic conditions.
The results were:
- 0.70 more potential HCCs per chart on an average, leading to a 19X return on program investment
- 0.207 improvement in RAF score per patient across four clients
How Technology Is Shaping the Future of CDI and Coding
Technology advancements are shifting nearly every aspect of healthcare, and CDI and coding are no exceptions.
Traditional CDI and coding relied heavily on human-operated, manual processes. AI tools automate transcription with speech recognition, draft clinical notes, and loop in humans for validation and enhancement.
As a result, information flows more quickly through a health system, its clinicians, clinical documentation specialists, and medical coders. AI and machine learning can suggest ways to improve the accuracy and quality of information in real time. This benefits revenue cycle management and patient health by:
- Prioritizing cases
- Automating repetitive tasks
- Enhancing data insights
- Supporting healthcare clinicians
Prioritizing Cases for Review
AI can scan patient records and flag documentation that appears to have the most opportunities for improvement. This helps clinical documentation specialists manage their time effectively and focus on the work that potentially has the greatest value for patients and the healthcare system.
Specialists then apply the human touch by reviewing the AI-generated insights and referencing clinical guides and other sources to ensure accuracy.
Automating Repetitive Tasks
AI can help automate repetitive tasks, like electronic queries of clinicians, improving productivity and satisfaction.
A 2022 survey by the Association of Clinical Documentation Integrity Specialists (ACDIS) found that 22% of respondents experienced increased productivity immediately after implementing electronic querying. Nearly 40% said productivity increased following an adjustment period after implementation.
The automation capabilities offered by AI speed up workflows and eliminate manual and repetitive tasks. This allows humans to make quick decisions and focus their time on more complex problems.
Enhancing Data Insights
Advanced CDI technologies work with value-based care reporting platforms, ensuring organizations can quickly analyze and act on population health strategies, risk adjustment, and compliance trends. These insights help organizations achieve long-term success in value-based care.
Supporting Healthcare Clinicians
Clinicians often document patient conditions synchronously while in exam rooms and offices. While this can improve accuracy and thoroughness, it can also increase the stress on doctors, nurses, and other healthcare clinicians.
Indeed, a Harris Poll for Athena Health found that 57% of physicians surveyed cited excessive documentation requirements as one of the leading causes of burnout.
AI tools can lend a helping hand by suggesting improvements, clarifying, and providing additional details. For example, a doctor may note that a patient has neuropathy but doesn’t specify the cause(s) or whether it is idiopathic. AI can prompt the doctor to add the details, affecting follow-up, treatment, and revenue.
IKS’s Coding and CDI Solution
Despite its game-changing impact, technology doesn’t completely replace the human role in CDI. The most effective CDI programs require close collaboration between clinicians, coders, and administrative teams.
The IKS coding suite is an autonomous, preemptive, end-to-end coding solution that automates up to 70% of the coding volume with 98%+ accuracy. Then, it processes 100% of claims through IKS Review, our pre-bill engine for charge assurance and denial prevention, ensuring fewer coding-related denials and maximum reimbursement the first time.
Contact IKS Health to learn more about how our generative AI and tech-enabled coding solution with a human-in-the-loop increases the quality and compliance of coding using the full clinical context of the patient visit.
