Accurate revenue capture is crucial to protecting your bottom line, improving financial performance, and reducing the risks of audits and penalties. Most importantly, it informs strategic decision-making around pricing, investments, and resource allocation that drives future profitability of cardiology services and revenue cycle optimization. While claims data has traditionally been the method of choice for coding audits, relying solely on claims data for comprehensive coding audits brings several limitations.
Limitations of Claims Data in Healthcare Audits
Claims data comes from the information healthcare providers submit to insurance companies for reimbursement. Each data source includes details about procedures performed, diagnoses, medical prescriptions, and associated costs.
However, there are limitations to relying solely on claims data for revenue capture, primarily rooted in the following coding quality issues that many cardiovascular providers face today1:
- Difficulties Keeping Pace with Changing Payer Requirements: Health insurers continually update and change coding requirements. For example, a new guideline for implanting a pacemaker may suddenly become available, and if the coding team isn’t up-to-date on the latest requirements, the claim could be denied.
- Challenges Managing Coding Complexity: The range of CPT codes for cardiovascular procedures ranges from minimally invasive to complex surgical, and The American Medical Association changes CPT codes every year.1 It’s important to consistently revisit codes to ensure accurate coding and limit denials.
- Unclear Communication with Providers: Illegible handwriting or hard-to-decipher notes in EMRs make it difficult for coders.1 Coding can be further muddied by inputs from multiple providers, as well as physician notes lacking in clinical detail.
- Poor Provider Coding Education: Providers may not fully understand the importance of accurate coding to the organization’s financial bottom line, making it crucial to educate providers on the necessity of using accurate codes and communicating with coders.1
- Privacy: Patient privacy protections may limit the amount of information that can be included in claims data and – as a result – difficult to rely on claims data for revenue insights.
- High Turnover for Medical Coders: In 2023, coders took the lead as the most difficult group to hire in the billing office.2 Managing high staff turnover and the associated learning curves only exacerbate coders’ already challenging jobs of tracking changing payer requirements, coding complexity, and learning provider communication styles.
Revenue and Compliance Issues as a Result of Coding Gaps
Coding gaps can produce several revenue and compliance issues, including:
Overbilling: Overbilling, a revenue and compliance issue, may happen when a coder accidentally uses multiple codes instead of a single code for a procedure, potentially putting themselves at risk for insurance fraud.3 hbRecon reduces overbilling through its ability to identify plausible miscoded DRGs and maximize procedure coding with higher or lower-weighted DRG codes where appropriate.
Missed Reimbursement Opportunities: A service, procedure, or condition (a CC or MCC) during a patient encounter being left out of a claim due to a missing code or skewed data can lead to a loss in revenue. hbRecon’s phased approach to integrating clinical registry and claims data results in increased reimbursement driven by identified factors in clinical registry data.
Faulty Re-Bill Processes: Faulty rebilling occurs when a claim is rebilled due to a medical or coding error. In Phase 3 of the hbRecon integration – reconciliation and process review – cases are reviewed by the clinical team and then submitted for secondary review by the hospital coding and compliance teams. This process will vary from site to site and network to network, but one of the primary objectives of this is to recode and re-bill as indicated by the findings.
The Importance of Comprehensive Medical Coding Audits for Heart Care
These challenges with claims data collection due to coding gaps, and subsequent pitfalls in revenue and compliance, point to the necessity of undergoing comprehensive coding audits that can successfully identify coding gaps in cardiovascular care and address them to support revenue cycle optimization.
However, claims audits focused on financial data inherently miss the other side of the coin – clinical registry data.
hbRecon maximizes accurate revenue capture through the integration of hospital clinical registry & coding data sources. Through this integration, hbRecon can identify cases where coding may be incorrect and identify thousands of dollars in services per case that would have otherwise gone unbilled. With claims data, if conditions are not coded, such as Acute Heart Failure, it is not possible to identify them. With clinical registry data and hbRecon, we can extrapolate those values, maximizing the revenue capture.4
Because clinical registry data uses discrete data elements that contain detailed clinical information about patients, diagnoses, procedures, and outcomes, and claims data uses a coded data source that includes details about procedures performed, diagnoses, medications prescribed, and associated costs, hbRecon provides a more comprehensive and accurate assessment of healthcare quality, outcomes, and financial performance. The hbRecon platform then employs an algorithm to determine a recommended DRG code using this combined dataset.
The higher levels of specificity produced by hbRecon lead to improved revenue capture through more accurate documentation and coding through education and process-improvements; enhanced quality and efficiency of care delivery; and a better reflection of patient acuity, all of which benefit the cardiovascular population.
hbRecon: The Combined Impact of Combining Clinical Registry Data with Claims Data
hbRecon’s integrated approach to coding audits is a valuable tool for increasing revenue capture as it relies on both the discrete data elements found in clinical registry data as well as the coded data sources found in claims data.
Is your healthcare organization ready to discover alternate revenue streams through the hbRecon toolkit? Our platform can integrate clinical registry and coding data sources to algorithmically analyze and determine recommended billing codes and identify probable coding mismatches and rebilling opportunities.
Schedule a discovery call today: https://www.heartbase.net/social-discovery-call
Sources
1. Conifer Health Solutions. (2023, August 7). Common coding challenges hospitals face and how to fix them. Healthcare Financial Management Association. https://www.hfma.org/revenue-cycle/coding/common-coding-challenges-hospitals-face-and-how-to-fix-them/
2. MGMA. (2023, March 23). Bottom line impacts from revenue cycle staffing challenges. MGMA. https://www.mgma.com/mgma-stats/bottom-line-impacts-from-revenue-cycle-staffing-challenges
3. Physicians Revenue Group. (2024, August 26). What is Unbundling in Medical Billing? | PRGMD. Physicians Revenue Group. https://prgmd.com/what-is-unbundling-in-medical-billing/
4. Enhancing CC and MCC Code Capture: Three Real-World Scenarios for Maximizing Reimbursement Revenue. (2024, November 25). heartbase. https://www.heartbase.net/news/2024/11/25/enhancing-cc-and-mcc-code-capture-three-real-world-scenarios-for-maximizing-reimbursement-revenue/