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Insights
- Healthcare organizations invest in SaaS for daily operations, storing data in various locations. Integration across systems is crucial for patient care and service delivery.
- Establishing a consensus on a data baseline is critical for effective VBC administration. The lack of a universally agreed-upon data baseline makes it challenging to accurately assess patient outcomes and determine reimbursement under VBCs. This can lead to disputes between payers and providers, hindering the overall effectiveness of VBCs in improving healthcare quality and efficiency.
- Generative AI has the potential to revolutionize VBC administration by enabling the conversion of unstructured data into valuable insights. This information can be used to refine patient risk stratification, improve patient care coordination, and enhance the overall administration of VBCs.
Note: This article has also been published in Electronic Health Reporter.
While VBC (Value based care) is the current focus point for the healthcare industry, it is important for organizations in this sector to ensure successful and efficient management. In this article, I would like to draw your attention to the challenges in effective contract management and how best to overcome these.
Path to value for Value Based Care
The growing markets in healthcare are now centered around government-sponsored programs like Medicare Advantage (MA), the Affordable Care Act (ACA) marketplaces, and Medicaid. This trend is steering healthcare organizations towards more direct patient engagement and the management of high-risk, high-acuity patients. As healthcare organizations increasingly focus on Medicare Advantage, ACA, and Medicaid, they encounter a unique set of challenges, encompassing system integration, data interoperability, and effective data handling, among other critical aspects.
Addressing the SaaS Sprawl
Over the years, healthcare organizations have made significant investments in a variety of SaaS solutions to facilitate their day-to-day operations. These solutions, each housing data in different data centers or cloud environments, have become integral to their business processes. However, as the focus intensifies on managing high-risk and high-acuity patients, along with an increased emphasis on direct consumer engagement, there arises a critical need to integrate data and processes across this sprawling landscape of disparate SaaS systems. This integration is essential for a holistic view of patient care and efficient service delivery.
Smart Contracts in Healthcare
While the title is called Smart Contracts, I am not necessarily talking about Smart contracts written into code leveraging blockchain technology. (However, I do not rule this possibility in future made possible by complete digitization of a healthcare enterprise and mass scale adoption of blockchain technology (whew!)
A value-based contract between a payer and a provider is inherently intricate, with structures ranging from Pay for Performance (P4P) to models incorporating both upside and downside risks. These contracts often include diverse performance metrics based on transactional aspects such as wellness visit frequencies and long-term outcomes derived from evidence-based guidelines. Further complexity is added by state-specific variations in ACA and Medicaid programs, along with the tailored management required for specialty high-risk cohorts such as kidney patients, diabetes, heart disease, etc.,).
Today, these contracts are manually written, interpreted, and administered. An effective configurable smart contract solution becomes imperative for healthcare enterprises to be able to administer this effectively.
Establishing a data baseline
Administering value-based contracts effectively hinges on a critical challenge: reaching a consensus on a data baseline acceptable to both payers and providers. This task is daunting in the current healthcare environment, where a universally agreed-upon baseline is rare, and the relationship between payers and providers is often marred by trust issues. Providers typically depend on the detailed clinical data in Electronic Health Records (EHR), whereas payers have a broader view through claims data aggregated from various providers for the same patient. A considerable amount of data is still locked in manually coded medical charts and unstructured physician notes, complicating effective integration and analysis.
In this context, the ingestion of clinical data into the payer’s ecosystem is essential for effective contract management. It becomes crucial to create data models that blend administrative data from payers with clinical data from providers. Navigating through the intricacies of patient attribution, varying data structures, and establishing trumping logic are key challenges in this process. Moreover, the handling of unstructured data, a domain where Generative AI is making notable strides, is increasingly critical. These AI advancements show great potential in converting unstructured data into valuable insights, thus playing a pivotal role in refining value based care administration.
New, similar, and same use cases – executed in a data-enabled environment.
Healthcare enterprises must significantly invest in defining new and similar use cases to be able to successfully administer new-age value-based contracts. A few examples that are gaining serious importance are quoted below.
- Enterprise Provider Performance Management: Bringing together a 360-degree view of providers across quality, cost, consumer engagement, and effectively engaging with the provider appropriately.
- Member Care gaps Management: Care gaps generated from regulatory commitments, contractual commitments, actual care delivery, and care management/risk processes in near real time fashion.
- High-risk cohorts: Establishing basic to sophisticated algorithms to identify and predict high-risk cohorts and introducing meritocratic steerage to the right providers/partners.
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