Streamlining workflow and improving quality for government payers and risk-bearing providers of all sizes
I. Introduction
The definition of risk is the possibility of loss or injury, or “the chance of loss or the perils to the subject matter of an insurance contract.” An opportunity-based risk comes from taking one opportunity over others, while an uncertainty-based one is from unpredictability around unknown or unexpected events.
In healthcare, the process of risk adjustment takes into account the underlying health status and spending of the enrollees in an insurance plan when looking at their healthcare outcomes or costs. It’s a methodology that equates the health status of a person to a number, called a risk score, to predict healthcare costs.¹
The Centers for Medicare & Medicaid Services (CMS) refers to risk adjustment as the process of modifying payments and benchmarks to reflect the degree of illness, which in turn allows the agency to estimate future spending and enables providers to understand the health characteristics of their managed population.² Over the past few years, many healthcare payers have been shifting risk to providers, resulting in more of them entering into risk-bearing arrangements.
Due to shifting models and regulations to emphasize value-based care, risk adjustment can be complex. As a process for compensation, it is dependent on complete and accurate reporting of patient data. It’s utilized by CMS to ensure health plans won’t turn down enrollees with more complex and therefore costly conditions. The more high-risk members a health plan enrolls, the greater the compensation they receive.
Risk adjustment models used in healthcare include U.S. News rankings (3M-APR-DRGs), Medicare Advantage contract rates (CMS-HCC), health plan prescription rates (RxHCC), CMS value-based purchasing programs, and Affordable Care Act health plan premiums (HHS-HCC). One of the primary models CMS uses in figuring capitated payments made to Medicare Advantage (MA) plans focuses on hierarchical condition categories (HCCs).
First introduced in 2004, the CMS HCC model concentrates on chronic conditions that impact future healthcare costs for a patient. The agency has been refining it ever since, especially with the shift to value-based payment.
II. Risk Adjustment for Increased Reimbursement
Three fundamentals of successful risk adjustment are high-quality member/provider connections, accurate medical charting and coding, and complete encounter and supplemental data.³ When the process is conducted in a timely and accurate manner, it leads to higher reimbursement, helping healthcare providers meet and exceed financial benchmarks.
Risk adjustment helps to ensure that plans receive adequate payments when rating restrictions limit the extent to which premiums
are allowed to vary by known risk factors.⁴ When strategies for risk adjustment are fully integrated, the healthcare industry overall achieves numerous advantages, including revenue accuracy, improved care and outcomes, cost reductions, improved clinical workflow, and reduced financial risk from audits.
For accountable care organizations (ACOs), risk adjustment allows them to account for severity over a specific time period, as well as set and track targets for performance. In addition to identifying high-risk patients, determining reimbursement level and accurately predicting costs, the process helps them understand their patients’ risk adjustment scores and acts as a tool for evaluating their performance.
III. The Technology Effect
As is true within many areas of the healthcare industry, technology is increasingly being employed to bolster risk adjustment processes. A report from KLAS Research indicates that risk adjustment technologies with quality analytics are effective solutions for payers when these tools can structure claims and clinical information into actionable models, identify multiple risk indicators, and foster provider collaboration.⁵
For a healthcare payer to ensure its population’s risk burden is accurately represented, optimal technology tools must be used to monitor encounter data, isolate aberrancies, and quickly and efficiently address any errors. For providers, patient-specific analytics can be used to better assess, chart, and document patients’ medical conditions and health status. This leads to better care and ensures that a payer’s risk adjustment needs are met.
Using technologies such as artificial intelligence (AI) and machine learning (ML) enables payers and providers to eliminate manual, paper-based administrative, and clinical processes that are often repetitive, labor-intensive and cost-ineffective.
AI is defined as the capability of a machine to imitate intelligent human behavior or a branch of computer science dealing with the simulation of intelligent behavior in computers. A subfield of AI is natural language processing (NLP), which is the process of using computer algorithms to identify key elements in everyday language and extract meaning from unstructured spoken or written input. Healthcare payers can leverage NLP technology to derive high-value insights across claims and unstructured clinical data and enable prospective risk adjustment.⁶
For risk-adjustment factor (RAF) management, employing NLP to help review members’ RAF scores lets payers better
manage revenue targets and provides detailed provider education to ensure members are receiving the proper treatment and care. For guiding ongoing improvement efforts, the technology offers visibility into documentation trends by the
provider, specialty, or at a global level. Using a combination of NLP and human processes, coders can help organizations achieve
greater productivity and accuracy at a lower cost.
IV. Comprehensive Risk Adjustment Coding
Technology also aids in ensuring thorough and accurate risk adjustment coding, which is a key method used by payers to deal with risk. In this process, diagnosis and procedure codes that are billed must exactly match each chronic condition reported along with the level of service described in a patient’s medical records. When documentation and coding are incomplete and inaccurate, it can negatively affect reimbursement and compliance.
Risk adjustment coding enables payers to analyze the health status and certain characteristics of a member to determine payment information. By implementing a robust audit and monitoring program, they have the capability to fix common documentation errors and standardize coding procedures. The American Academy of Family Physicians (AAFP) offers three tips for better risk-adjustment coding:⁷
Accurate risk adjustment coding affects provider payments and settlement outcomes and increases the accuracy of a member’s risk score, while reducing the need to request medical records and/or audit provider’s claims. It promotes compliance with various rules and regulations, as well as minimizes disruptions to practice flow and assorted administrative burdens.
V. The Importance of a Single Platform
By moving to a single technology platform, payers and providers have the ability to manage their entire risk adjustment initiative in one area, rather than vendor by vendor. This promotes more flexibility while reducing the number of reports.
A reputable risk adjustment vendor can not only perform a variety of risk adjustment tasks on a regular basis but conduct even more tracking. They also often have more data that can be used in conjunction with other resources, making their targeting process more accurate. When adding risk adjustment staffing might not make financial sense, risk adjustment vendors collaborate with payers to build and manage a team and establish key processes.
A vendor is able to precisely calculate risk scores and recognize any issues that may be negatively affecting the plan. Plus, such an expert resource can put measures in place to help gather additional data and ensure health insurers aren’t paying a provider solely based on how many members it has.
VI. Essential Risk Adjustment Services
There are multiple components necessary to achieve risk adjustment best practices. If one of these facets of the process isn’t included, it can negatively impact payers and providers both operationally and financially. Therefore, it’s essential that each risk adjustment service is performed at the highest level using the most up-to-date guidelines, technology, and expertise.
Risk Adjustment Chart Review and HCC Coding
There are two types of chart review: concurrent and retrospective. Concurrent chart review should provide an immediate review of the record, review risk adjustment conditions at the time of visit, and include a real-time query for provider clarification. Retrospective chart review should identify opportunities for provider education and training and consist of blind coding reviews and claims data validation. It’s best to procure chart review options that give providers flexibility and allow them to affect
RAF score and documentation improvement.
Risk adjustment chart review is a central part of HCC risk scoring. Medicare Advantage Plans, health insurance exchanges, commercial health plans (capitations), hospitals, and providers all are impacted by HCC risk scores.
The CMS HCC model relies on a provider’s ICD-10 codes to map the HCC codes that risk adjusts patients based on their health. Payers utilize this model to understand the risk level of patients and predict their costs.
HCC models organize the disease process and conditions into body systems and diagnostic groups. The diagnostic groups are separated into condition categories. Not all diagnoses are mapped to an HCC code, only the diagnoses that are costly to manage.
Performing HCC risk scoring and coding might seem cumbersome. However, it offers multiple benefits by leading to maximum reimbursement, helping to achieve financial benchmarks, assisting in the development of programs for population health management to improve outcomes, and maintaining a practice’s financial viability.
RAF Score Reporting
According to the American Academy of Professional Coder, a risk score is a numeric value an enrollee in a risk adjustment program is assigned each calendar year based on demographics and diagnoses. Often referred to as an RAF score, it’s officially calculated by the state or government entity overseeing the risk adjustment program in which the member is enrolled. The risk score of an enrollee resets every January 1.
RAF scores were initially designed to prevent payers from selecting only healthy patients to enroll in their plans. They encourage payers to take a risk by spreading government reimbursement evenly and appropriately. Demographic factors used in
addition to diagnoses for risk score calculation include age, sex, Medicaid eligibility and socioeconomic, disability, and
institutional status.¹
Higher risk scores result in a higher burden or cost to the payer and provider. Lower risk scores, conversely, represent a healthier
patient. If a physician does not code appropriately or to the highest level, though, a low-risk score can be falsely
indicated.
Ultimately, payers and providers should partner to ensure clinical documentation is accurate and justifies the proper risk score. Nevertheless, variations in RAF scores correlate with a plan’s revenue, meaning a payer that doesn’t have a risk score that reflects actual member diagnoses will probably miss out on reimbursements, and patients may not receive the best care available.
Employing risk adjustment coding enables providers to normalize medical risk and make sure the correct RAF score is applied to their patients. Accurate clinical documentation also is important because it positively affects RAFs and helps payers and providers better manage their patient population. There are best practices to follow to increase RAF scores and corresponding reimbursement, including establishing appropriate staffing, correctly identifying code gaps, performing thorough reviews, and implementing advanced technology. Without the correct technology in place, a higher number of missed or inaccurate codes may occur.
Using a real-time risk adjustment dashboard and detailed reporting, payers can illustrate their plan and group, all the way down to its members’ total RAF score. By showing additions and deletions of diagnoses and how they affect the overall RAF score, payers can work with an expert resource to improve it through proper education and documentation.
Medical Record/Chart Retrieval
There are multiple challenges to conducting chart retrieval and abstraction of data, from issues in working with providers to aggregate data from disparate electronic medical records (EMR) systems and paper charts to getting them to respond and release records upon request. Previously, it required manual outreach methods, such as phone and fax, to get needed medical records.
With the emergence of numerous automated self-service tools, providers and payers can save time and resources while getting the medical records data they need. Using a platform that lets providers share records using EMR integration and an advanced dashboard that offers real-time data can help address those medical records retrieval obstacles encountered by payers.
Also, working with the right vendor can make sharing records fast and easy with full EMR integration, drag and drop capabilities, and a dashboard that provides real-time retrieval data for ongoing improvement and enhanced communication. This vendor should offer powerful tools that feature dynamic provider databases to help improve engagement for addressing irretrievable charts. Secure, HIPAA-compliant chart recovery methods give providers much-needed flexibility and reduce provider abrasion.
HEDIS Abstraction
HEDIS (the Healthcare Effectiveness Data and Information Set) is a collection of health plan performance measures used for public reporting and accreditation. Utilized by 90% of health plans in the United States, they’re crucial to the overall healthcare system because they ensure that payers are collecting and analyzing data related to performance.⁸
For payers and providers in value-based care arrangements, documenting quality data is especially important because a large portion of their revenue is reliant on meeting these quality measures.⁹ High quality HEDIS solutions offer payers a real-time look at their performance, allowing them to improve care delivery, quality, and member satisfaction.
HEDIS quality is one of the five most popular NLP application areas for payers.¹⁰ The technology assists in maintaining cost-effective practices and providing a best-record approach to finding the correct measures in the right place.
By partnering with vendors to retrieve, abstract, and analyze the data needed, all while keeping an eye on HEDIS performance, payers can reduce numerous challenges. It gives them an opportunity to leave these processes to the experts who have the tools, teams, and technology to streamline the process.
Provider Education and Support
It’s important for providers to employ an appropriate level of trained and certified coders knowledgeable about ICD coding guidelines for risk adjustment processes, something that often necessitates regular and updated training. These risk adjustment experts can review completed risk adjustment coding to check for accuracy, detail, and consistency. If these reviews identify consistent errors in any area, they can examine the root cause(s) of any gaps in documentation.
Top-level risk adjustment vendors provide platforms that offer a comprehensive view to identify opportunities for provider education and feedback. Such a platform should give users the capability to review trending reports and education by the provider, specialty, or HCC category, thereby highlighting recommended areas for provider education and displaying results to compare to other health plans.
VII. The Benefits of an Enterprise Risk Adjustment Solution
As these services indicate, the risk adjustment process is a comprehensive one requiring a high level of accuracy, timeliness, and expertise. Otherwise, providers and payers risk lower levels of reimbursement, which threatens their financial sustainability and ability to compete in a healthcare industry transitioning to value-based care.
By utilizing a platform backed by advanced technology, such as AI and NLP, both providers and payers can achieve a multitude of advantages, including:
This type of intelligent workflow tool allows payers to perform risk adjustment and quality initiatives through a scalable and customizable self-service tool. It provides the ability to manage internal and vendor teams and processes through one enterprise
technology platform.
Getting the most out of shared risk programs requires a continued, expert focus on risk adjustment. This comes with an indepth evaluation and understanding of a payer or provider’s data, and an outside look is often the most effective way to truly get it
right. For payer and provider organizations of any size and specialty, conducting risk adjustment using an advanced technology platform allows them to bolster internal workflows and realize operational continuity and visibility, all of which elicits improved results.
VIII. iCode Risk Adjustment™
GeBBS’ iCode platform helps payers perform risk adjustment and HEDIS initiatives utilizing a self-service tool. With real-time dynamic reporting, actionable data, and full transparency, our risk adjustment technology streamlines the workflow, improves productivity and quality for Government payers and riskbearing providers. Our technology addresses critical pain points for payers with its chart retrieval feature, concurrent review capabilities, and ability to capture HEDIS and STAR measures.
At GeBBS Healthcare Solutions, we designed our iCode Risk Adjustment™ technology to streamline the workflow and improve quality for government payers and risk-bearing providers of all sizes. Through our single enterprise solution, these healthcare entities are able to improve productivity, increase accuracy, and provide real-time analytic reporting and control on projects.
Our scalable and secure technology addresses critical pain points for payers with its chart retrieval feature, concurrent review capabilities, and ability to capture HEDIS and other quality measures. It integrates NLP and AI-driven coding, RAF score
validation, chart management, and provider education. Our clients have access to our web-based, interactive
client portal to achieve real-time transparency into project progress and obtain views of operational data at each stage of the project.
By providing payers and providers with a single platform to perform risk adjustment, we offer them a comprehensive approach to quality improvement and cost control that contributes directly to their bottom line. Plus, our proven service delivery model takes chart review to the highest level, ensuring timeliness, quality, accurate documentation, and optimal results.
Learn how our iCode platform delivers you the tools and other resources to increase visibility into your data, automate your processes, streamline your workflows, and provide business intelligence to enhance your decision-making processes. Along with iCode Risk Adjustment™, it includes iCode Workflow™, our enterprise-wide coding workflow solution, and iCode Assurance®, our fully customizable SaaS coding audit
solution.
Request a consultation today!
IX. The GeBBS Advantage
GeBBS Healthcare Solutions is a KLAS-rated leading provider of technology-enabled Revenue Cycle Management (RCM) services and solutions in Health Information Management (HIM), Accounts Receivable (A/R), and Risk Adjustment outsourcing. GeBBS’ innovative technology, combined with its over 9,500-strong global workforce, helps clients improve financial performance, adhere to compliance, and enhance the patient experience. Headquartered in Los Angeles, CA, GeBBS has won numerous accolades
for its medical coding and medical billing outsourcing, including being ranked in Modern Healthcare’s Top 10 Largest RCM Firms, Black Book Market Research’s Top 20 RCM Outsourcing Services, and Inc. 5000’s Fastest-Growing Private Companies in the US.
References
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- Yeatts, J., and Sangvai, D. (2016, Sep-Oct). HCC Coding, Risk Adjustment, and Physician Income:
What You Need to Know. Retrieved from https://www.aafp.org/fpm/2016/0900/p24.html - Darnall, R. (2020, April). The 3 Fundamentals of Risk Adjustment Success. Retrieved from
https://www.risehealth.org/insights-articles/the-3-fundamentals-of-risk-adjustment-success/ - American Academy of Actuaries. (2010, May). Risk Assessment and Risk Adjustment. Retrieved
from
https://www.actuary.org/sites/default/files/pdf/health/Risk_Adjustment_Issue_Brief_Final_5-
26-10.pdf - Beaton, T. (2018, June). Quality Analytics, Risk Adjustment Tools Prep Payers for Success.
Retrieved from https://healthpayerintelligence.com/news/quality-analytics-risk-adjustmenttools-prep-payers-for-success - Kobelski, K. (2020, December). Contributor: 3 Ways Health Plans Can Leverage Natural Language
Processing Technology. Retrieved from https://www.ajmc.com/view/contributor-3-ways-healthplans-can-leverage-natural-language-processing-technology - American Academy of Family Physicians. (2019, February). Three tips for better risk-adjustment
coding. Retrieved from
https://www.aafp.org/journals/fpm/blogs/inpractice/entry/risk_adjustment.html - Hetler, J. (2021, March-April). Technology: Need for Quality Measures and Reporting Remain a
Top Priority Post Pandemic. Retrieved from
https://www.todaysgeriatricmedicine.com/archive/MA21p6.shtml - CareSignal. (2021, February). How to Close Gaps in Care and Gather Quality Data During and
After the Pandemic. Retrieved from https://www.caresignal.health/news/how-to-close-gaps-incare-and-gather-quality-data-during-and-after-the-pandemic - Moore, M. (2020, April). Health Plans and Payers: Top Five Natural Language Processing
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