Medicare risk adjustment – Opportunity to use technology in risk adjustment
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Risk Adjustment
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Medicare risk adjustment - Opportunity to use technology in risk adjustment
August 4, 2022
Risk Adjustment is a mechanism that represents the overall risk profile of the health membership. Medicare risk adjustment is used in the risk adjustment model, which is related to the Medicare advantage to the organizations. The Medicare health insurance plan is generally contracted with the CMS, which offers beneficiaries insurance. It covers the institutional and outpatient services along with the optional prescription benefits.
Calculation of Medicare Risk Adjustment – RAF Score
Medicare risk adjustment utilizes the CMS-HCC to calculate the annual risk score of the members based on the chronic, and severity of the acute conditions. These conditions impact the overall costs of healthcare in the long term.
Like the other risk adjustment models, each HCC is a collection of one payment group with a similar diagnosis. If particular diseases are unspecified and have similar risk scores, they are mapped under the same code. As the process used to go manually or less digital intervention, many flaws, and inappropriate coding outcomes impact the Medicare risk adjustment.
Legacy ways are raising the mess!
Legacy methods aren’t working accurately in this domain. Coders are combing through thousands of patient charts to document chronic conditions. But the process is not as effective as it should be. It was consuming much time and became highly expensive.
Providers and payers are facing significant challenges here. It is tough to ensure the quality outcome as there are too many to review in fewer time frames. Analyzing this activity is also tricky as it’s tough to identify ways to improve the organization.
Providers are not receiving access to the patients’ health information, which raises ambiguity in decision-making due to missing critical information. Payers are bothering providers to get charts, and both are facing complex processes affecting their relationship.
Challenges in Risk Adjustment
Delays in chart retrieval
Payers are having difficulty retrieving the charts onsite and may be unable to do that in the future. Especially, it is happened with most providers regarding the critical information during and post-pandemic period.
Inappropriate Coding and audit timelines
Due to the compressed submission timelines, the chart retrieval activities aren’t happening appropriately. The coding and auditing projects ae also won’t be able to start due to pressure.
Decrease in the productivity and capacity of coding vendor
Lack of productivity, unclear code mapping, and vendors’ capacity become the biggest challenges in a pandemic, and it is still the same scenario happening in most cases.
Consequences
- Payers miss 30% of reimbursement on average due to inadequate HCC capture and improper documentation.
- Low-quality ICD 10 codes and medical charting
- Inaccurate reports lead to high costs, legal actions, and reputation damage
- Irregular data submissions cause payers to miss a mid-cycle sweep.
- Disruptions in the revenue cycle.
Opportunity to use technology in Risk Adjustment
Technology cannot be a solution for every problem, but it helps teams to address the issues. Artificial Intelligence, (NLP) Natural language processing and Machine learning technologies have already made footprints in the risk adjustment world and they made considerable impact in this domain. Today they have become well known in this domain. But, what are these technologies, and why do we need them in the risk adjustment?
Advantages of Technology in Risk Adjustment
- Improves the coding accuracy and efficiency
- It helps in maintaining tight turnarounds and defensibility.
- AI-generated HCC predictions help reviewers focus more on high-value charts.
- Some AI models can help compare the known codes to support documentation in the patient charts and flat the potential unsupported HCCS which need remediation.
- Cloud-based coding platforms help streamline the task management for remote coding teams.
- Automating reviews and audit assignments helps teams reduce workloads and improve efficiency and accuracy.
Things to consider for successful implementation of the risk adjustment program
Quality Connections
The early intervention and prevention of illness can be possible. If you can establish active engagement between the members and providers, it will help in delivering appropriate care with timely delivery. Also, it will help in robust documentation on health status.
Charting and Coding
Ensure that the member’s health status is charted and coded accurately by using the best practices to chart patient visits, documentation of actual status and conditions, identification and addressable coding, and over-coding trends. The overall exercise can positively impact an organization’s finances.
Encounter Submission
Coordination between the stakeholders, Data reconciliation and monitoring, and CMS and HHS resource mechanisms ensures the appropriate payments.
Things to understand before choosing a Risk adjustment technology partner
Not every technology can fulfill the requirements. While bringing a new technology partner into the process, it is essential to understand if they can meet your program needs in the future.
Here are the few things you should look for in a technology partner:
- Check if the technology can handle high data processing volumes and concurrent users.
- Check on how the technology is employed in the solutions.
- Some use rule-based algorithms, locate the potential HCCs in the charts, and surface many précised results which helps in generating the accurate reports.
- Make sure you choose the right technology provider or platform to connect the dots and gaps in the processes.
- The solution should reduce the medical coding operations costs to maximum Always choose HIPAA compliant cloud-based platform to ensure data security and privacy.
Summing it up
The risk adjustment technologies with quality analytics are the best solutions for the payers. These tools will help structure the clinical and claims information into actionable models. Technology helps in the identification of multiple risk indicators and fosters collaboration. Payers utilizing machine learning, Ai, and predictive analytics can have the solutions to reduce costs and empower proactive interventions and outcomes.
For payers, it ensures the accurate representation of the population risk burden and helps monitor the encounter data quickly and efficiently in addressing any errors. For providers, patient-specific analytics helps better assess charts and documentation of medical conditions and health status. Hence, it leads to better care and ensures that risk adjustment needs are met in the right direction with an innovative technology platform.
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