How do Risk Adjustment and Quality Management Impact Profitability and Compliance?
Risk Adjustment (RA) is a predictive algorithm used to ensure that health insurance companies get sufficient funding for the healthcare spending of the population they cover. Risk Adjustment and Artificial Intelligence (AI) analytics discourage insurance providers from taking actions to prevent unhealthy individuals from registering; insurers are reimbursed for risk adjustment for patient populations. When it comes to RA and quality management, there appears to be a big potential for collaboration in healthcare plans. The collaboration potential is especially relevant in the highly competitive healthcare market, as Accountable Care Organizations (ACOs) and health insurance companies that operate in the ACA exchanges continue to proliferate. Many healthcare plans consider Risk Adjustment and quality management as autonomous units with purposefully separate objectives and indicators. However, a paradigm that links the two actually enables the true compliance from data to analytics, may yield a remarkable array of benefits, including:
• Financial growth • Improved health outcomes • Lower healthcare costs Role of HEDIS for Risk Adjustment and Quality Management The Healthcare Effectiveness Data and Information Set (HEDIS) is a commonly used device for assessing healthcare quality. It is the leading technology for healthcare performance reporting. HEDIS is a robust set of integrated performance metrics intended to provide potential buyers and users with the data they need to assess the performance of healthcare plans in a legitimate way. HEDIS performance data enables the identification of performance gaps, track progress and setting of realistic improvement objectives of care programs. HEDIS covers more than 90 indicators scattered throughout six domains of care: Care Efficacy Access/Availability of Care Experience of Care Utilization and Risk-Adjusted Utilization. Health Plan Descriptive Information Metrics Collected Using Electronic Clinical Data Systems Several HEDIS metrics are clearly related to the objective of risk adjustment programs, which attempt to appropriately evaluate the health condition of specific individuals.
What is the process of cost-cutting alignment? Continuous evaluation and intensive coding training for clinicians also contribute to correct identification and recordkeeping. Insurance providers are combining chart retrieval requests to remove redundancy and reduce provider abrasion. Data technologies are used to assist, detecting anticipated care gaps in advance for both risk adjustment and quality improvement.
Interoperability of data collection and data analysis is required to ensure accurate condition entry. It reduces the number of provider visits and helps in avoiding provider and member abrasion. Users have found this kind of data accessibility quite beneficial in driving performance. It is critical to monitor all touchpoints to achieve comprehensive transparency throughout the health plans.