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The Top Three Ways To Ensure Data Integrity in the Move to Value-Based Care

Earlier this month, we kicked off our January educational series focused on how providers can best accelerate their journey to value-based care (VBC). In part one of this series, we are exploring the key data considerations providers must take into account to optimize and streamline the transition from fee-for-service to value-based care.

We spoke with Curation Health’s Chief Medical Officer, Dr. Matt Lambert, on this important topic. As a practicing emergency medicine physician, he reinforced the perspective that the primary impediment to value-based care is not one that can be addressed by technology alone. It’s a challenge that stems primarily from the clinical workflow.

If healthcare providers want to simplify value-based care, their best bet is to start with clinicians and patients at the point of care. Clinicians need to be able to easily capture the full complexity of the patient directly within the current electronic health record (EHR) workflow.

What amount of data should providers assess to inform VBC strategy?

When we asked Dr. Lambert to share insights on how providers can determine the right amount and type of data they should assess to best inform VBC infrastructure and strategy, he noted that the ideal amount of data is typically within an 18-month range. If providers are going further back with their data assessment, they are wasting precious time managing duplicative data.

Dr. Lambert also noted that, today, 55,000 diagnosis codes actually don’t map to risk-based models. In order to be sure your organization is capturing data that falls within the current risk-based model codes moving forward, focus on the following three steps:

  1. Assess both clinical and claims data and do so within an 18-month period (as noted above);
  2. Filter out data that does not map to risk-based models; and
  3. Be sure that your data fully align with your quality priorities.

How should data governance evolve to support VBC?

Data collection and governance is a huge, ongoing challenge for healthcare organizations. As an example, an initiative to reduce disparities in cardiac care by the Robert Wood Johnson Foundation asked 10 different hospitals to collect and assess data. The 10 hospitals in the collaborative initially cited the data collection requirement as one of the greatest challenges of the program, yet once they focused their efforts on these goals, they were able to bring together key stakeholders within each institution to effectively collect and apply the data to quality measures. Reinforcing the idea for providers moving to value-based care, having the right data governance team in place is paramount.

Dr. Lambert stressed the vital importance of an integrated data governance team that includes key representation and insights from across the organization — from operations and IT to clinical leadership. Having this full representation of key leadership within an organization will enable smarter, more efficient date governance changes over time — changes that will often directly impact risk-based contracting.

As part of data governance, provider organizations also need to consider three facets of data gathering in order to successfully take on more risk. Based on Dr. Lambert’s work at Curation Health with leading providers like AdventHealth and Monogram Health, these specific areas of data capture and governance can significantly impact a provider organization’s value-based care transition:

  • Pre-visit: A pre-visit view formulated using AI, NLP, and 750+ validated clinical and quality rules that highlights actionable opportunities for HCC recapture and closure of previously undetected care gaps;
  • Point-of-care: A view of verified risk adjustment priorities and clinical insights relating to an individual patient that is shared with physicians and other care team members in the EHR at the point-of-care; and
  • Post-visit and pre-claim review: A post-visit and pre-claim review of clinical evidence, provider documentation, and coding to ensure billing accuracy, revenue integrity, and risk adjustment data validation compliance.

Dr. Lambert stressed the importance of the point-of-care approach to presenting clinicians with the right patient data, at the right time. Clinicians don’t want or need all of the patient data. They need the most important data that conveys patient history and complexity — and they need it within their typical EHR workflow.

Do you have the right EHR partner in place?

Finally, Dr. Lambert emphasized the importance of ensuring that providers have the right EHR partner in place. What is most critical is that your EHR is able to support the organization and presentation of data in a meaningful way. Not all EHRs are created equal, so before providers make a significant investment in value-based care changes, they should assess the capabilities of their current EHR partner. Having all the right data does little for a provider if their EHR solution cannot present data in a way that ensures clinicians can seamlessly gather and report on the most important clinical data that drives improved patient and financial outcomes. It’s equally important to make sure your partner for prospective risk adjustment is functionally integrated within the EHR workflow to bring the most value to patients and providers.

Whether you are focusing on data analysis to inform your VBC strategy or considering how best to present the right data at the right time for clinicians, the best practice to follow is this: less is more. Clearly, big data holds much opportunity to transform healthcare as an industry. When it comes to leveraging data to determine your path forward with VBC to empower clinicians with the full value of care, it’s the right data that aligns with risk-based contracts that matters most.

To learn more, contact us.

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