This is the final part of a three-part blog series exploring from both a provider and payer perspective the topic of data integrity in value-based payments—including the various challenges it poses and how best to address those challenges. You can read part one here. and part two here.
Part 3: Addressing Data Integrity in Value-Based Care Arrangements—For Payers
Like providers, payers need data from a variety of sources to impact change and advance in value-based care arrangements. Payers excel in processing claims data, but do not have the capabilities or expertise needed to take advantage of clinical data. Payers need that clinical data to deliver effective care management and coordination, in addition to facilitating quality improvement, cost reduction, and member satisfaction.
Data gaps, inconsistencies, and overall poor data integrity can significantly impact a payer’s bottom line. Consequences include financial loses due to improper care coordination, lower quality scores, miscalculation of a member’s risk profile, lack of identification of costly members/patients, an inability to model contracts successfully, and reduced member satisfaction scores. So how do payers entering into value-based care arrangements make sure that they have clean, relevant data to create actionable insights and succeed as they enable their provider networks to take on greater risk?
To begin, they need robust data mapping, validation, and warehousing capabilities which will allow for the integration of claims and clinical data. Actionable insight pulled from integrated data is what really drives the transition to value-based care and succeeding in value-based arrangements, so the importance of integrated data can’t be underscored enough. In addition to claims and clinical data, other sources of data, including social determinants of health, medication data, ADT, lab data, behavioral health, and HIE, are increasingly coming in to play in the value-based care landscape. Having a comprehensive library of data quality reports will additionally help to effectively manage and review data for quality and completeness.
Creating a detailed list of the data sets needed for key lines of business and performing maintenance of data processing operations are keys to regularly maintaining clean data. Payers should also be thinking about coordinating their data and data support processes with an enterprise-wide strategy to be adopted by all parties. It can also help to automate aspects of data collection and reporting where applicable by using tools like natural language processing and artificial intelligence.
To gain valid insights from the data, modern analytics solutions are required. Payers though often lack the ability to generate actionable insights that advance value-based contracts from integrated data sets. Key benefits that payers and their network providers should expect to derive from their data include:- insights to model, standardize, evaluate, and reconcile contract types, including pay for quality, shared savings, shared risk, MLR arrangements, total cost of care, and capitation arrangements
- cost, utilization, and financial performance analytics that enable network providers to meet contract terms
- improved quality and risk adjustment capabilities, including the ability to demonstrate ROI in risk adjustment and quality scores
- integration of behavioral health, SDoH and health equity into value-based care arrangements, especially in CMS contracting initiatives for government-sponsored plans (Medicare, Medicare Advantage, and Medicaid)
- the ability to build high-performance networks by determining a common measure set, quality benchmarks, cost benchmarks, and anchoring them to contracts.
Please feel free to email me at raj.lakhanpal@spectramedix.com with any questions or thoughts on this blog or any of the previous blogs in this series.
- [1]https://www2.deloitte.com/us/en/insights/industry/health-care/health-data-management-for-health-plans.html
- [2]https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/tech-forward/getting-data-architecture-right-a-guide-for-healthcare-payers
- [3]https://healthitanalytics.com/news/four-ehr-optimization-steps-for-healthcare-data-integrity
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