In this blog post
Value Based Care and Data Management
In modern day healthcare where patients require holistic care and attention beyond their specific medical conditions, Value Based Care (VBC) shifts the emphasis from the traditional fee-for-service model to rewarding healthcare providers for achieving positive patient outcomes. Data management is vital for Value Based Care, enabling healthcare organizations to collect, analyze, and leverage data to improve patient care and reduce costs. GS Lab | GAVS conducted a webinar that explores the challenges, provides insights and establishes a roadmap to achieving excellence in care delivery. This blog captures vital discussion points and takeaways from the webinar Value Based Care and Data Management.
The webinar panelists were healthcare industry leaders Mr. Suman Mishra – Healthcare CTO at GS Lab | GAVS and Dr. Nick Patel – Founder and CEO of Stealth Consulting.
Introduction to Value Based Care
VBC is a healthcare delivery model focusing on improving patient outcomes while controlling costs and holding providers accountable. Some key enablers are strong government involvement in change, focus on information technology improvement, instituting a VBC culture among providers, and adopting a time- driven activity-based costing model. VBC is necessary as it helps improve patient outcomes, contains costs, promotes population health, aligns incentives, enables continuous quality improvement, and drives payment reform.
Understanding Data Journey
Data is a key component of VBC. An organization needs enough patient data to offer personalized care. The term “data journey” refers to the various stages through which data moves from collection to usage by business. It starts with identifying siloed and separate data sources. Once that is done, the next step is to consider a centralized data lakehouse. Now that all the data is in a single place, the third step is to share it with internal and external sources. Finally, it is time for data governance, where the lineage and quality of data, security, and privacy are evaluated before data is made available for predictive or prescriptive analytical (AI/ML) services.
Key Data Components of Value Based Care
Here are the main data points that need to be collected for VBC:
Understanding and leveraging Hierarchical Condition Category (HCC) and Risk Adjustment Factors (RAF) scores are vital for reimbursement and load balancing schedules and optimizing patient care. Healthcare providers can allocate appropriate time and resources by categorizing patients based on risk. For instance, two patients with diabetes may have different risk profiles based on complications and comorbidities. Proper coding affects the RAF score, which, in turn, influences reimbursement.
Healthcare Effectiveness Data and Information Set (HEDIS) measures are also crucial components of value-based care, with approximately 90 measures across six domains: effectiveness of care, access and availability, care experience, utilization, relative resource use, health plan components, and reporting. Comprehending these measures and their subgroups helps healthcare organizations monitor and improve care quality.
Social Determinants of Health (SDOH) are significant for patient care and outcomes. Transportation access, broadband availability, and socioeconomic challenges impact patient engagement and health outcomes. Understanding the patient’s social determinants enables healthcare providers to tailor care plans, support unique needs, and enhance overall well-being.
When building a data management framework, it is critical to integrate and centralize various data sources, such as claims, Electronic Health Records (EHRs), and IoT (Internet of Things) devices. Automation and AI tools can leverage this consolidated data to drive personalized care and engage patients effectively. A centralized system, often called a command center, is a hub for monitoring and coordinating patient movement across different care settings (for example, hospital, post-acute, ambulatory).
Data Reference Architecture for Value Based Care
In the healthcare industry, there are diverse recipients of data, each with specific needs and roles. A key aspect of the framework is data governance, which ensures that data is not siloed and is uniformly interpreted across all business units. For example, data claims and health plan aspects are viewed and analyzed similarly, providing consistency and coherence. This unified approach can meet the requirements of different entities, such as CMS and regulatory agencies, which have specific data needs and formatting preferences.
In the context of value-based care, patient-centered data management becomes crucial. Patients are increasingly interested in accessing their health information, monitoring their progress, and making informed decisions about their well-being. Remote Patient Monitoring (RPM) is critical in providing real-time insights into their health status and empowering them to manage their health proactively.
GS Lab | GAVS has established itself as a trusted partner to numerous healthcare organizations. To learn more about our AI powered solutions and services for healthcare transformation, please visit https://www.gavstech.com/healthcare.